WhatsApp is making another major push into everyday payments in India. The messaging platform has launched Bill Payments, allowing users to find, manage and pay bills without leaving the app.&nbsp;The feature is powered by Bharat Connect, the bill payment network, and gives users access to 22,722 billers across 30 categories, including electricity, gas, water, FASTag, insurance, credit cards and loan repayments. Meta says the feature is being rolled out gradually across India and will reach both Android and iOS users over the coming weeks.&nbsp;<h2>What can you pay on WhatsApp?</h2>The new feature is designed to bring recurring household payments into one place.Users can pay electricity and water bills, gas bills, FASTag recharges, insurance payments, credit card bills and loan repayments, among other categories. It also goes beyond a one-time payment. WhatsApp will let users view past payments and upcoming bills. A biller that has been used before can appear in the Payments Home section, giving users quicker access the next time they need to pay. The platform also supports multiple accounts under one biller, which could be useful for people managing bills for their home, office or family.Bharat Connect is designed as an interoperable bill payment platform covering multiple bill categories and payment channels.&nbsp;<h2>How to pay bills on WhatsApp</h2>Using the feature is relatively simple:Open WhatsApp and tap the Rs icon at the top of the home screen.Select the bill category and biller.Enter and confirm your account details.Check the bill amount fetched by WhatsApp.Select a payment method.Confirm the payment.&nbsp;WhatsApp says users can pay using UPI, debit cards or credit cards.The company has already been expanding payments and everyday services in India. Earlier this year, it added prepaid mobile recharges through the ₹ icon, allowing users to recharge Jio, Airtel and Vi numbers without leaving WhatsApp.<figure class="image"><img src="https://images.moneycontrol.com/static-mcnews/2026/09/20260903060852_WhatsApp-Launches-Bill-payments-in-India.png" alt="WhatsApp Launches Bill payments in India"></figure><h2>WhatsApp wants to become more than a messaging app</h2>The bill payment launch is another step in WhatsApp’s wider push to become a platform for everyday tasks in India. People can already use the app for payments, mobile recharges, metro-related services and government services through chatbots. Meta has previously said WhatsApp is increasingly being used by Indians to interact with businesses and access essential services. For users, the biggest change is simple: a routine bill that once required another app can now be handled inside WhatsApp.

WhatsApp has launched Bill Payments in India, allowing users to pay electricity, gas, water, FASTag, insurance, credit card and loan bills inside the app. Powered by Bharat Connect, the service covers 22,722 billers across 30 categories.

WhatsApp is making another major push into everyday payments in India. The messaging platform has launched Bill Payments, allowing users to find, manage and pay bills without leaving the app. The feature is powered by Bharat Connect, the bill payment network, and gives users access to 22,722 billers across 30 categories, including electricity, gas, water, FASTag, insurance, credit cards and loan repayments. Meta says the feature is being rolled out gradually across India and will reach both Android and iOS users over the coming weeks. What can you pay on WhatsApp? The new feature is designed to bring recurring household payments into one place. Users can pay electricity and water bills, gas bills, FASTag recharges, insurance payments, credit card bills and loan repayments, among other categories. It also goes beyond a one-time payment. WhatsApp will let users view past payments and upcoming bills. A biller that has been used before can appear in the Payments Home section, giving users quicker access the next time they need to pay. The platform also supports multiple accounts under one biller, which could be useful for people managing bills for their home, office or family. Bharat Connect is designed as an interoperable bill payment platform covering multiple bill categories and payment channels. How to pay bills on WhatsApp Using the feature is relatively simple: Open WhatsApp and tap the Rs icon at the top of the home screen. Select the bill category and biller. Enter and confirm your account details. Check the bill amount fetched by WhatsApp. Select a payment method. Confirm the payment. WhatsApp says users can pay using UPI, debit cards or credit cards. The company has already been expanding payments and everyday services in India. Earlier this year, it added prepaid mobile recharges through the ₹ icon, allowing users to recharge Jio, Airtel and Vi numbers without leaving WhatsApp. WhatsApp wants to become more than a messaging app The bill payment launch is another step in WhatsApp’s wider push to become a platform for everyday tasks in India. People can already use the app for payments, mobile recharges, metro-related services and government services through chatbots. Meta has previously said WhatsApp is increasingly being used by Indians to interact with businesses and access essential services. For users, the biggest change is simple: a routine bill that once required another app can now be handled inside WhatsApp.

WhatsApp has launched Bill Payments in India, allowing users to pay electricity, gas, water, FASTag, insurance, credit card and loan bills inside the app. Powered by Bharat Connect, the service covers 22,722 billers across 30 categories.

WhatsApp rolls out bill payments in India: You can now pay electricity, gas and more without leaving the app

OpenAI CEO Sam Altman has pushed back against growing concerns over the amount of water used by artificial intelligence, making a surprising comparison between ChatGPT queries and almonds.&nbsp;Speaking on the first episode of the Sources podcast, Altman claimed that around 38,000 ChatGPT queries use as much water as producing one almond in California. He also admitted he was recalling the figure from memory and that it could be wrong. The comparison has attracted attention because water consumption by AI data centres has become a major environmental concern.&nbsp;<h2>How much water does one ChatGPT query use?</h2>Altman previously put the water consumption of an average ChatGPT query at around 0.32 millilitres.&nbsp;Using that figure, the calculation is very different from his latest 38,000-query comparison. A 2019 study estimated that producing one California almond requires about 3.56 litres of water. At 0.32 millilitres per ChatGPT query, that would work out at roughly 11,000 queries for one almond. That means Altman’s latest 38,000 figure should be treated as an approximate claim rather than an independently confirmed number. Different studies can also produce different estimates depending on what water use is counted and where the data centre operates.&nbsp;Sam Altman says AI water fears are overstated&nbsp;Altman argued that the public perception of AI data centres as huge water consumers has become a “robust meme” that is difficult to correct.&nbsp;He also rejected social media claims suggesting that a single ChatGPT query could be comparable to several hours of showering. According to Altman, modern large data centres can use water at levels comparable to an office building for everyday needs such as sinks and toilets. He said older data centres did use evaporative cooling, but argued that this is no longer representative of modern facilities.&nbsp;<h2>But the water debate is not over</h2>Altman’s comments do not mean AI has no water footprint.Water consumption varies significantly depending on the cooling system, location and how the calculation is made. Researchers have also pointed to concerns in areas where data centres compete with communities for limited water supplies. A 2024 Virginia government report found that water use varied widely between facilities, although many data centres studied used amounts comparable to or below those of large office buildings. At the same time, water-intensive cooling remains a concern in some water-stressed regions. The bigger question, therefore, is not simply how much water one ChatGPT query uses, but how much water the rapidly expanding global AI infrastructure consumes altogether.

Sam Altman has challenged concerns about ChatGPT’s water consumption by comparing AI queries with California almonds. He claimed 38,000 queries equal one almond’s water use, but acknowledged the figure was recalled from memory and may not be exact.


OpenAI CEO Sam Altman has pushed back against growing concerns over the amount of water used by artificial intelligence, making a surprising comparison between ChatGPT queries and almonds. Speaking on the first episode of the Sources podcast, Altman claimed that around 38,000 ChatGPT queries use as much water as producing one almond in California. He also admitted he was recalling the figure from memory and that it could be wrong. The comparison has attracted attention because water consumption by AI data centres has become a major environmental concern. How much water does one ChatGPT query use? Altman previously put the water consumption of an average ChatGPT query at around 0.32 millilitres. Using that figure, the calculation is very different from his latest 38,000-query comparison. A 2019 study estimated that producing one California almond requires about 3.56 litres of water. At 0.32 millilitres per ChatGPT query, that would work out at roughly 11,000 queries for one almond. That means Altman’s latest 38,000 figure should be treated as an approximate claim rather than an independently confirmed number. Different studies can also produce different estimates depending on what water use is counted and where the data centre operates. Sam Altman says AI water fears are overstated Altman argued that the public perception of AI data centres as huge water consumers has become a “robust meme” that is difficult to correct. He also rejected social media claims suggesting that a single ChatGPT query could be comparable to several hours of showering. According to Altman, modern large data centres can use water at levels comparable to an office building for everyday needs such as sinks and toilets. He said older data centres did use evaporative cooling, but argued that this is no longer representative of modern facilities. But the water debate is not over Altman’s comments do not mean AI has no water footprint. Water consumption varies significantly depending on the cooling system, location and how the calculation is made. Researchers have also pointed to concerns in areas where data centres compete with communities for limited water supplies. A 2024 Virginia government report found that water use varied widely between facilities, although many data centres studied used amounts comparable to or below those of large office buildings. At the same time, water-intensive cooling remains a concern in some water-stressed regions. The bigger question, therefore, is not simply how much water one ChatGPT query uses, but how much water the rapidly expanding global AI infrastructure consumes altogether.

Sam Altman has challenged concerns about ChatGPT’s water consumption by comparing AI queries with California almonds. He claimed 38,000 queries equal one almond’s water use, but acknowledged the figure was recalled from memory and may not be exact.

ChatGPT water use is less than you think, says Sam Altman

The foldable iPhone 18 Ultra has apparently been leaked online, with an influencer showing what he claims to be Apple's latest phone. Lewis Hilsenteger of the popular Canadian YouTube channel Unbox Therapy posted a video of the latest model alongside the iPhone 18 Pro Max. In the video, the YouTuber says an unnamed source in China sent the phone. The user is almost sure that the device is similar to the final product. Apple's first foldable iPhone is expected to be announced on September 9, 2026.&nbsp;The foldable iPhone, as seen in the said video, opens like other such devices. It has a screen in the front and a dual rear camera on the back. The screen inside is wider than the entire length of the phone. Nearly two million people have seen the video of what is being presented as the foldable iPhone 18 Ultra.<h2>Accurate devices being sent to YouTuber before release</h2>The YouTuber said that this person who has been sending the phones to him from China has been increasingly accurate. "There's increasing accuracy coming out of China... The stuff they're sending is looking more and more like the actual finished products," he said. A user who has been following the page added that this person has provided the devices for five years, and almost all of them have turned out to be the same as the final devices that are released.&nbsp;&nbsp;

"Whoever has been supplying these mock-up phones has been accurate for 5 years straight, so I know these are actually going to be the new iPhones," the person said.&nbsp;The phone has a straight edge along the crease and a curved outer edge. The one in the video is white with a matte finish, with a shiny Apple logo. A camera cutout is present in the top left corner. Apple also seems to have changed the position of the volume buttons, moving them to the top from the side. Two buttons, presumably the unlock and action buttons, are on the side.&nbsp;Commenting on the video, most users seemed unhappy with the pronounced hinge and the fold. A user wrote, "i doooo nott like that fold." &nbsp;Another added, "Just wish the fold would have been a bit taller in size when closed, I was so excited for it but it’s a let down."

A YouTuber showed off a device which he claimed was Apple's foldable iPhone 18 Ultra and had been sent to him from China. He says the past devices have been the same as the final launch. The foldable iPhone has a prominent crease, which netizens did not like.  

The foldable iPhone 18 Ultra has apparently been leaked online, with an influencer showing what he claims to be Apple's latest phone. Lewis Hilsenteger of the popular Canadian YouTube channel Unbox Therapy posted a video of the latest model alongside the iPhone 18 Pro Max. In the video, the YouTuber says an unnamed source in China sent the phone. The user is almost sure that the device is similar to the final product. Apple's first foldable iPhone is expected to be announced on September 9, 2026. The foldable iPhone, as seen in the said video, opens like other such devices. It has a screen in the front and a dual rear camera on the back. The screen inside is wider than the entire length of the phone. Nearly two million people have seen the video of what is being presented as the foldable iPhone 18 Ultra. Accurate devices being sent to YouTuber before release The YouTuber said that this person who has been sending the phones to him from China has been increasingly accurate. "There's increasing accuracy coming out of China... The stuff they're sending is looking more and more like the actual finished products," he said. A user who has been following the page added that this person has provided the devices for five years, and almost all of them have turned out to be the same as the final devices that are released.

A YouTuber showed off a device which he claimed was Apple's foldable iPhone 18 Ultra and had been sent to him from China. He says the past devices have been the same as the final launch. The foldable iPhone has a prominent crease, which netizens did not like. &nbsp;

Influencer shows off what he claims is Apple's first foldable iPhone 18 Ultra

Algorithms and institutional technology have transformed Indian markets. But for ordinary investors, the bigger challenge is understanding the enormous amount of information moving through NSE, BSE and MCX every day. AI-powered market-intelligence platforms such as Kwala Intel are attempting to make that information easier to research and understand.&nbsp;At 9:15 every morning, prices move, volumes change, technical indicators react and company news emerges. Institutions process this information through research teams, technology and algorithms. Retail investors often have limited time to understand what is happening.<h2>The Information Gap in Indian Markets</h2>India’s retail participation has expanded significantly. Investors can access NSE and BSE-listed equities, Nifty and Sensex data, company results, futures and options, and commodities through MCX.&nbsp;Researching a stock can involve financial statements, revenue, profitability, valuations and quarterly results. Studying a chart can require RSI, MACD, moving averages, Bollinger Bands, Fibonacci retracement, volume, momentum, support and resistance. Options add strike prices, premiums, expiry, open interest, implied volatility and Greeks.&nbsp;Professional research analysts and investment advisors can provide expertise, but their services may not be practical or affordable for every retail participant. Many investors prefer to understand markets themselves rather than simply follow calls.&nbsp;Kwala Intel approaches this problem through conversational AI, allowing users to ask questions instead of mastering every financial concept before beginning research.<h2>Kwala Intel as a Market-Research Companion</h2>Kwala Intel is an AI-powered market-intelligence platform focused on Indian markets. Users can ask about stocks, companies, technical analysis, market trends and financial concepts through a conversational interface.&nbsp;A user researching an NSE-listed company could ask about price movement, technical setup, support, resistance or momentum. Another could ask Kwala Intel to explain quarterly results, revenue growth or profitability. Someone learning derivatives could use Kwala Intel to understand futures, options, open interest, expiry or Greeks.&nbsp;Kwala Intel is designed to help users understand market information rather than simply follow stock tips.<h2>Technical Analysis Without the Jargon</h2>Technical analysis can appear intimidating because indicators are often presented as formulas or isolated signals.&nbsp;Kwala Intel lets users explore concepts through questions such as: What is RSI showing? Where are important support and resistance levels? What does MACD indicate about momentum? How can Fibonacci retracement levels be interpreted?&nbsp;Kwala Intel connects explanations with relevant market charts and data, helping users understand the relationship between indicators and price behaviour.&nbsp;The approach can support learning about entry strategies, trends, momentum, volatility and risk management. An entry strategy is not a guaranteed prediction.<h2>Beyond NSE and BSE</h2>NSE and BSE are central to equity-market participation, while MCX provides a major platform for commodity derivatives.&nbsp;Different segments require different research. Equity investors may focus on fundamentals and technical trends, options participants on open interest and volatility, and commodity participants on gold, silver, crude oil and global developments.<h2>SEBI and the Need for Better Understanding</h2>The need for accessible market education comes amid continued regulatory attention on retail participation, particularly in futures and options. SEBI studies and investor-awareness initiatives have highlighted risks faced by individual traders and high loss rates in equity derivatives.&nbsp;AI cannot remove those risks or guarantee profitable trades. It can, however, reduce the information barrier. For investors who cannot afford a research team or do not want to depend entirely on market calls, Kwala Intel provides a conversational way to explore market information.<h2>Breaking India’s Language Barrier</h2>Financial terminology remains heavily English-oriented, even though Indian consumers increasingly consume digital information in regional languages. Kwala Intel supports interaction in Hindi, Marathi, Gujarati, Bengali, Tamil and Telugu, alongside English.&nbsp;Users can ask Kwala Intel about a stock, RSI, MACD, market trends or company results in a language they understand comfortably.&nbsp;For Kwala Intel, the opportunity is to turn complex market data into understandable research for everyday Indian investors.<h2>A New Layer of Intelligence for Retail Investors</h2>Institutions can employ analysts, traders and specialised technology. Experienced participants can spend years learning technical and fundamental analysis. The average retail investor may not have the same resources.&nbsp;Kwala Intel attempts to create a middle layer: an AI-powered research companion that helps users ask questions, interpret market information, study technical analysis and understand financial-market concepts.&nbsp;The goal is not to replace professional expertise or human judgment, but to make useful market intelligence easier to access.&nbsp;As Indian markets become more complex, the next evolution may be less about more information and more about helping investors understand what they already have.&nbsp;From an NSE stock to a BSE-listed company, from technical indicators to options, and from equities to MCX commodities, Kwala Intel is building around one idea: sophisticated market intelligence should be easier for ordinary Indian investors to understand.To explore Kwala Intel, visit KwalaIntel.com.&nbsp;

Kwala Intel is an AI-powered market-intelligence platform focused on Indian markets. Users can ask about stocks, companies, technical analysis, market trends and financial concepts through a conversational interface.

Algorithms and institutional technology have transformed Indian markets. But for ordinary investors, the bigger challenge is understanding the enormous amount of information moving through NSE, BSE and MCX every day. AI-powered market-intelligence platforms such as Kwala Intel are attempting to make that information easier to research and understand. At 9:15 every morning, prices move, volumes change, technical indicators react and company news emerges. Institutions process this information through research teams, technology and algorithms. Retail investors often have limited time to understand what is happening. The Information Gap in Indian Markets India’s retail participation has expanded significantly. Investors can access NSE and BSE-listed equities, Nifty and Sensex data, company results, futures and options, and commodities through MCX. Researching a stock can involve financial statements, revenue, profitability, valuations and quarterly results. Studying a chart can require RSI, MACD, moving averages, Bollinger Bands, Fibonacci retracement, volume, momentum, support and resistance. Options add strike prices, premiums, expiry, open interest, implied volatility and Greeks. Professional research analysts and investment advisors can provide expertise, but their services may not be practical or affordable for every retail participant. Many investors prefer to understand markets themselves rather than simply follow calls. Kwala Intel approaches this problem through conversational AI, allowing users to ask questions instead of mastering every financial concept before beginning research. Kwala Intel as a Market-Research Companion Kwala Intel is an AI-powered market-intelligence platform focused on Indian markets. Users can ask about stocks, companies, technical analysis, market trends and financial concepts through a conversational interface. A user researching an NSE-listed company could ask about price movement, technical setup, support, resistance or momentum. Another could ask Kwala Intel to explain quarterly results, revenue growth or profitability. Someone learning derivatives could use Kwala Intel to understand futures, options, open interest, expiry or Greeks. Kwala Intel is designed to help users understand market information rather than simply follow stock tips. Technical Analysis Without the Jargon Technical analysis can appear intimidating because indicators are often presented as formulas or isolated signals. Kwala Intel lets users explore concepts through questions such as: What is RSI showing? Where are important support and resistance levels? What does MACD indicate about momentum? How can Fibonacci retracement levels be interpreted? Kwala Intel connects explanations with relevant market charts and data, helping users understand the relationship between indicators and price behaviour. The approach can support learning about entry strategies, trends, momentum, volatility and risk management. An entry strategy is not a guaranteed prediction. Beyond NSE and BSE NSE and BSE are central to equity-market participation, while MCX provides a major platform for commodity derivatives. Different segments require different research. Equity investors may focus on fundamentals and technical trends, options participants on open interest and volatility, and commodity participants on gold, silver, crude oil and global developments. SEBI and the Need for Better Understanding The need for accessible market education comes amid continued regulatory attention on retail participation, particularly in futures and options. SEBI studies and investor-awareness initiatives have highlighted risks faced by individual traders and high loss rates in equity derivatives. AI cannot remove those risks or guarantee profitable trades. It can, however, reduce the information barrier. For investors who cannot afford a research team or do not want to depend entirely on market calls, Kwala Intel provides a conversational way to explore market information. Breaking India’s Language Barrier Financial terminology remains heavily English-oriented, even though Indian consumers increasingly consume digital information in regional languages. Kwala Intel supports interaction in Hindi, Marathi, Gujarati, Bengali, Tamil and Telugu, alongside English. Users can ask Kwala Intel about a stock, RSI, MACD, market trends or company results in a language they understand comfortably. For Kwala Intel, the opportunity is to turn complex market data into understandable research for everyday Indian investors. A New Layer of Intelligence for Retail Investors Institutions can employ analysts, traders and specialised technology. Experienced participants can spend years learning technical and fundamental analysis. The average retail investor may not have the same resources. Kwala Intel attempts to create a middle layer: an AI-powered research companion that helps users ask questions, interpret market information, study technical analysis and understand financial-market concepts. The goal is not to replace professional expertise or human judgment, but to make useful market intelligence easier to access. As Indian markets become more complex, the next evolution may be less about more information and more about helping investors understand what they already have. From an NSE stock to a BSE-listed company, from technical indicators to options, and from equities to MCX commodities, Kwala Intel is building around one idea: sophisticated market intelligence should be easier for ordinary Indian investors to understand. To explore Kwala Intel, visit KwalaIntel.com.

Kwala Intel is an AI-powered market-intelligence platform focused on Indian markets. Users can ask about stocks, companies, technical analysis, market trends and financial concepts through a conversational interface.

This Indian AI is bringing market intelligence to intraday traders

A Taiwanese man used a camera from a robot vacuum cleaner to spy on his unfaithful wife. The footage from the robocam won him roughly 500,000 Taiwanese dollars ($19,000) in his lawsuit against his wife in the divorce case. But soon she sued him back since he secretly recorded her without consent; the courts ruled in favour of her, granting her 30 per cent or 150,000 TWD of the proceeds, along with a five-month sentence in prison for the husband.&nbsp;The couple took the vows in 2021 and used to live with their parents, while also spending time at another holiday property. During a stay there in 2023, the husband came across a used toothbrush in their bathroom, sparking suspicion of infidelity. He confirmed his suspicion from the CCTV footage from a parking garage. He saw another man driving his wife home and hypothesised she was cheating on him.&nbsp;Three months later, the husband, while being at his parents' home, logged on to the home's smart robot vacuum mobile app to use the device's audio function to speak with her wife. He accidentally opened the live video stream instead. He saw his wife and her lover in intimate scenes.&nbsp;Also Read: <a href="https://www.wionews.com/india-news/india-us-ties-indian-companies-invest-40-billion-us-support-70000-jobs-1788349202278">Indian companies invest $40 billion in US, support 70,000 direct jobs</a>The lover was the man he previously identified. She was changing her clothes, getting into bed with her lover, walking around naked, while he comfortably sank into the sofa. He recorded the whole ordeal and brought the entire thing to use as evidence in a lawsuit that he brought shortly after.&nbsp;In Taiwan, cheating is not a criminal offence, but infringing on someone's marital rights is, since it is a breach of contract. The man sought 2 million TWD, or roughly $63,000. He used the footage to prove his wife's infidelity, and the judge ruled in his favour.&nbsp;There was ample evidence for a counter-lawsuit; she argued that the sensor and light were not enough to indicate she was being filmed. The man argued that the court already admitted it as evidence, so it could not be deemed illegal material. The court rejected his defence on the basis of invading his wife's privacy; hence, it was obtained via illegal means. Recording someone without their consent is illegal, and individual rights outweigh marital duties. He was fined 150,000 TWD and sentenced to five months' prison.&nbsp;

A Taiwanese man used his robot vacuum’s camera to record his wife’s alleged affair. He won a lawsuit but was later sentenced to five months in prison for violating her privacy.

A Taiwanese man used a camera from a robot vacuum cleaner to spy on his unfaithful wife. The footage from the robocam won him roughly 500,000 Taiwanese dollars ($19,000) in his lawsuit against his wife in the divorce case. But soon she sued him back since he secretly recorded her without consent; the courts ruled in favour of her, granting her 30 per cent or 150,000 TWD of the proceeds, along with a five-month sentence in prison for the husband. The couple took the vows in 2021 and used to live with their parents, while also spending time at another holiday property. During a stay there in 2023, the husband came across a used toothbrush in their bathroom, sparking suspicion of infidelity. He confirmed his suspicion from the CCTV footage from a parking garage. He saw another man driving his wife home and hypothesised she was cheating on him. Three months later, the husband, while being at his parents' home, logged on to the home's smart robot vacuum mobile app to use the device's audio function to speak with her wife. He accidentally opened the live video stream instead. He saw his wife and her lover in intimate scenes. Also Read: Indian companies invest $40 billion in US, support 70,000 direct jobs The lover was the man he previously identified. She was changing her clothes, getting into bed with her lover, walking around naked, while he comfortably sank into the sofa. He recorded the whole ordeal and brought the entire thing to use as evidence in a lawsuit that he brought shortly after. In Taiwan, cheating is not a criminal offence, but infringing on someone's marital rights is, since it is a breach of contract. The man sought 2 million TWD, or roughly $63,000. He used the footage to prove his wife's infidelity, and the judge ruled in his favour. There was ample evidence for a counter-lawsuit; she argued that the sensor and light were not enough to indicate she was being filmed. The man argued that the court already admitted it as evidence, so it could not be deemed illegal material. The court rejected his defence on the basis of invading his wife's privacy; hence, it was obtained via illegal means. Recording someone without their consent is illegal, and individual rights outweigh marital duties. He was fined 150,000 TWD and sentenced to five months' prison.

A Taiwanese man used his robot vacuum’s camera to record his wife’s alleged affair. He won a lawsuit but was later sentenced to five months in prison for violating her privacy.

Husband uses secret camera to record wife’s affair, wins divorce case, ends up in jail for spying

Uber is cutting about 3,300 jobs, or roughly 10% of its global workforce, in the company’s biggest round of layoffs since the Covid pandemic.&nbsp;The ride-hailing giant says it wants to remove layers of management, simplify its organisation and make faster decisions. The move comes as Uber prepares for a future increasingly shaped by robotaxis and autonomous driving. The cuts are striking because Uber is not currently describing a business in crisis. In its latest quarter, the company reported 22% year-on-year growth in gross bookings and said its trailing 12-month free cash flow had crossed $10 billion for the first time.<h2>Why is Uber cutting 3,300 jobs?</h2>CEO Dara Khosrowshahi said Uber had become a much larger company, but that growth had also created more layers, coordination and fragmented ownership.&nbsp;The restructuring will reduce the number of managers by about 20%. Uber will also cut the number of very small teams and combine some engineering, science and delivery operations.The company is also reducing the number of employees working remotely.

Fewer than 1% of its workforce will be allowed to work fully remotely, while Uber will continue its three-day office policy. Unlike several major technology companies, Khosrowshahi did not blame artificial intelligence for the job cuts. Instead, he said a leaner organisation would create savings that could be reinvested in growth, innovation and future capabilities.&nbsp;<h2>Uber is betting heavily on robotaxis</h2>The timing of the layoffs is important.Uber is trying to position itself as a major marketplace for autonomous rides as robotaxis expand in the US. The company has been working with autonomous vehicle firms, including Waymo, whose driverless cars are available through Uber in some cities. But Waymo is also expanding independently, while Tesla is pushing deeper into robotaxis. That has raised questions about whether driverless cars could eventually reduce Uber’s role as the middleman between passengers and drivers. Uber has said it plans to invest more than $10 billion in robotaxis over the coming years.<h2>Biggest Uber layoffs since Covid</h2>The 3,300 job cuts are Uber’s largest since May 2020, when the pandemic devastated demand for rides and forced the company to eliminate about 6,700 positions.&nbsp;Uber had roughly 34,000 employees globally at the end of last year. The latest restructuring therefore marks a very different moment. Uber is cutting jobs while its core business is growing strongly. The company is effectively trying to become leaner before the next phase of transport arrives one in which autonomous vehicles could change how its entire platform operates.

Uber is cutting about 3,300 jobs, or 10% of its global workforce, in its biggest layoffs since Covid. The company is reducing management layers and redirecting resources towards growth and its expanding robotaxi strategy.

Uber is cutting about 3,300 jobs, or roughly 10% of its global workforce, in the company’s biggest round of layoffs since the Covid pandemic. The ride-hailing giant says it wants to remove layers of management, simplify its organisation and make faster decisions. The move comes as Uber prepares for a future increasingly shaped by robotaxis and autonomous driving. The cuts are striking because Uber is not currently describing a business in crisis. In its latest quarter, the company reported 22% year-on-year growth in gross bookings and said its trailing 12-month free cash flow had crossed $10 billion for the first time. Why is Uber cutting 3,300 jobs? CEO Dara Khosrowshahi said Uber had become a much larger company, but that growth had also created more layers, coordination and fragmented ownership. The restructuring will reduce the number of managers by about 20%. Uber will also cut the number of very small teams and combine some engineering, science and delivery operations. The company is also reducing the number of employees working remotely.

Uber is cutting about 3,300 jobs, or 10% of its global workforce, in its biggest layoffs since Covid. The company is reducing management layers and redirecting resources towards growth and its expanding robotaxi strategy.

Biggest layoffs since COVID: Uber to cut 3,300 jobs as company restructures for the robotaxi era

Steve Jobs is remembered as one of the most influential figures in technology. But there is one unusual detail about his time at Apple that still attracts attention: his salary was just $1 a year.&nbsp;After returning to Apple in 1997, Jobs received a $1 annual salary as the company’s interim CEO and continued on that salary after becoming permanent CEO. Apple confirmed the arrangement in its filings.&nbsp;<h2>So, did Jobs really get paid only $1 by Apple?</h2>Not exactly. Steve Jobs’ famous $1 salaryJobs’ $1 salary was real. Apple said he had received that salary every year since returning to the company in 1997. In fiscal 2010, for example, his reported salary was again just $1. He received no new stock or option award that year.The strategy was closely linked to his ownership of Apple shares. Apple said Jobs’ stock ownership aligned his interests with shareholders. By 2010, Jobs owned about 5.5 million Apple shares. He had not sold shares since returning to the company in 1997.&nbsp;<h2>Apple gave Jobs a huge stock award</h2>The biggest part of Jobs’ Apple compensation came through equity. In 2003, Jobs voluntarily cancelled 27.5 million stock options and received 5 million restricted shares instead. The award was valued at about $74.75 million at the time.Those shares later increased to 10 million after Apple’s stock split and vested fully in 2006. Apple’s stock had risen sharply during that period, making the award enormously valuable.<h2>He also received a $90 million private jet</h2>According to reports Jobs’ compensation history included another extraordinary perk. In 1999, Apple awarded him a Gulfstream V aircraft for his service as interim CEO. Apple said the aircraft was worth about $90 million.The amount was later recorded differently in Apple’s filings because the plane was transferred to Jobs in 2001 and related payments and tax assistance were reported across fiscal years. So while the famous headline says Steve Jobs earned $1 a year, that figure describes his base salary, not the full value of everything he received from Apple. His story became an early example of how billionaire executives can receive little in cash salary while building enormous wealth through company stock.

Steve Jobs famously took a salary of just $1 a year from Apple after returning to the company in 1997. 

Steve Jobs is remembered as one of the most influential figures in technology. But there is one unusual detail about his time at Apple that still attracts attention: his salary was just $1 a year. After returning to Apple in 1997, Jobs received a $1 annual salary as the company’s interim CEO and continued on that salary after becoming permanent CEO. Apple confirmed the arrangement in its filings. So, did Jobs really get paid only $1 by Apple? Not exactly. Steve Jobs’ famous $1 salary Jobs’ $1 salary was real. Apple said he had received that salary every year since returning to the company in 1997. In fiscal 2010, for example, his reported salary was again just $1. He received no new stock or option award that year. The strategy was closely linked to his ownership of Apple shares. Apple said Jobs’ stock ownership aligned his interests with shareholders. By 2010, Jobs owned about 5.5 million Apple shares. He had not sold shares since returning to the company in 1997. Apple gave Jobs a huge stock award The biggest part of Jobs’ Apple compensation came through equity. In 2003, Jobs voluntarily cancelled 27.5 million stock options and received 5 million restricted shares instead. The award was valued at about $74.75 million at the time. Those shares later increased to 10 million after Apple’s stock split and vested fully in 2006. Apple’s stock had risen sharply during that period, making the award enormously valuable. He also received a $90 million private jet According to reports Jobs’ compensation history included another extraordinary perk. In 1999, Apple awarded him a Gulfstream V aircraft for his service as interim CEO. Apple said the aircraft was worth about $90 million. The amount was later recorded differently in Apple’s filings because the plane was transferred to Jobs in 2001 and related payments and tax assistance were reported across fiscal years. So while the famous headline says Steve Jobs earned $1 a year, that figure describes his base salary, not the full value of everything he received from Apple. His story became an early example of how billionaire executives can receive little in cash salary while building enormous wealth through company stock.

Steve Jobs famously took a salary of just $1 a year from Apple after returning to the company in 1997.&nbsp;

How much did Steve Jobs get paid from Apple?

New York City is taking a much tougher approach to artificial intelligence in schools. The city is banning student-facing AI tools from 2-K through eighth grade, meaning younger pupils will not be allowed to use generative AI, chatbots or AI tutors in school.&nbsp;The policy comes as parents and educators debate whether children should be relying on AI for learning. City officials are also introducing tighter limits on classroom screen use. The move is being closely watched because New York City has the largest public school system in the US.&nbsp;<h2>AI ban will cover younger students</h2>Under the new policy, students from early childhood programmes through eighth grade will face the strongest restrictions. High school students will be allowed to use AI, but access will be limited. Possible uses include literacy and career-readiness programmes, as well as selected pilot programmes.The policy also takes aim at AI companion chatbots designed to simulate relationships or provide emotional support.The exact challenge will be enforcement. Students can access many AI services outside school, making it difficult for schools to control what happens beyond the classroom.&nbsp;<h2>Teachers can still use AI</h2>The rules do not amount to a complete AI ban across New York City Public Schools.&nbsp;Teachers will be allowed to use approved AI tools for tasks such as lesson planning, translation and drafting communications. However, teachers will not be allowed to use AI for certain sensitive activities, including grading, behaviour monitoring, counselling or developing special education plans. The city's education department has said its approach should be age-appropriate and keep human judgement at the centre of education. Its earlier guidance divided AI use according to different grade bands, including K-5, 6-8 and 9-12.<h2>Why New York City changed its AI policy</h2>The decision follows backlash over the city's earlier AI framework released in March.&nbsp;That framework used a traffic-light system and allowed some student uses of AI for research, exploration and creative work. Parents and teachers argued that the approach did not go far enough. Schools Chancellor Kamar Samuels later acknowledged that officials had “missed the mark” in communicating the policy and promised to consider community feedback.&nbsp;The city is now forming a task force involving educators, elected officials, experts and union representatives. Its work is expected to shape the longer-term AI policy. With more than 900,000 students, New York City's decision could become an important test case for school districts across the US as they decide how much AI access children should have.

New York City is banning student-facing AI tools from 2-K through eighth grade, while allowing limited use in high school. Teachers can still use approved AI for tasks such as lesson planning and translation, as the city takes a tougher approach to AI in education.

New York City is taking a much tougher approach to artificial intelligence in schools. The city is banning student-facing AI tools from 2-K through eighth grade, meaning younger pupils will not be allowed to use generative AI, chatbots or AI tutors in school. The policy comes as parents and educators debate whether children should be relying on AI for learning. City officials are also introducing tighter limits on classroom screen use. The move is being closely watched because New York City has the largest public school system in the US. AI ban will cover younger students Under the new policy, students from early childhood programmes through eighth grade will face the strongest restrictions. High school students will be allowed to use AI, but access will be limited. Possible uses include literacy and career-readiness programmes, as well as selected pilot programmes. The policy also takes aim at AI companion chatbots designed to simulate relationships or provide emotional support. The exact challenge will be enforcement. Students can access many AI services outside school, making it difficult for schools to control what happens beyond the classroom. Teachers can still use AI The rules do not amount to a complete AI ban across New York City Public Schools. Teachers will be allowed to use approved AI tools for tasks such as lesson planning, translation and drafting communications. However, teachers will not be allowed to use AI for certain sensitive activities, including grading, behaviour monitoring, counselling or developing special education plans. The city's education department has said its approach should be age-appropriate and keep human judgement at the centre of education. Its earlier guidance divided AI use according to different grade bands, including K-5, 6-8 and 9-12. Why New York City changed its AI policy The decision follows backlash over the city's earlier AI framework released in March. That framework used a traffic-light system and allowed some student uses of AI for research, exploration and creative work. Parents and teachers argued that the approach did not go far enough. Schools Chancellor Kamar Samuels later acknowledged that officials had “missed the mark” in communicating the policy and promised to consider community feedback. The city is now forming a task force involving educators, elected officials, experts and union representatives. Its work is expected to shape the longer-term AI policy. With more than 900,000 students, New York City's decision could become an important test case for school districts across the US as they decide how much AI access children should have.

New York City is banning student-facing AI tools from 2-K through eighth grade, while allowing limited use in high school. Teachers can still use approved AI for tasks such as lesson planning and translation, as the city takes a tougher approach to AI in education.

No AI until high school: New York City schools introduce sweeping new rules

Apple has revealed the pay packages for its new CEO John Ternus and former CEO Tim Cook, just as the company enters a new leadership era.&nbsp;Ternus, who officially became Apple CEO on September 1, has a target compensation of about $58 million for fiscal 2027. Cook, who has moved into the role of executive chairman, has a new target package worth about $47 million. The figures were disclosed in an Apple filing with the US Securities and Exchange Commission on the first day of Ternus’ tenure.&nbsp;<h2>How much will John Ternus earn at Apple?</h2>Ternus will receive an annual base salary of $3 million. The much larger part of his package comes from Apple shares. His fiscal 2027 equity award has a target value of $55 million. Importantly, this is not guaranteed cash. The value of the stock award can rise or fall depending on Apple’s share price.&nbsp;Ternus will also receive a prorated RSU award worth about $2.5 million for his time as CEO during fiscal 2026.Of his $55 million annual equity award, 75 per cent will be performance-based. It will depend on Apple’s total shareholder return compared with other companies in the S&amp;P 500.&nbsp;The remaining 25 per cent will be time-based shares, vesting in equal instalments every six months over four years.&nbsp;<h2>Tim Cook’s new Apple salary revealed</h2>Cook’s pay will fall as he moves away from the CEO role, but his new package remains substantial. As executive chairman, Cook will receive an annual salary of $2 million and a fiscal 2027 equity award targeted at $45 million. Half of that stock award will be performance-based, while the other half will vest over four years. Cook earned $74.3 million in total compensation in 2025 as Apple CEO, including a $3 million salary, $12 million in performance-based cash awards and $57.5 million in stock awards.&nbsp;<h2>Why Apple’s CEO change matters</h2>Ternus is taking charge after Cook’s 15-year run as Apple CEO. Apple said in April that Ternus would succeed Cook from September 1, while Cook would become executive chairman. During Cook’s tenure, Apple grew from a company valued at around $350 billion to roughly $4.5 trillion, according to Reuters. Now Ternus faces a different challenge: keeping Apple’s enormous business growing while pushing harder in areas such as artificial intelligence. The leadership change also comes just days before Apple’s September 9 product event, giving Ternus an early opportunity to shape the company’s next chapter.

Apple has revealed John Ternus’ $58 million target compensation as its new CEO, including a $55 million stock award. Tim Cook will receive a $47 million package as executive chairman, down from his $74.3 million 2025 pay.

Apple has revealed the pay packages for its new CEO John Ternus and former CEO Tim Cook, just as the company enters a new leadership era. Ternus, who officially became Apple CEO on September 1, has a target compensation of about $58 million for fiscal 2027. Cook, who has moved into the role of executive chairman, has a new target package worth about $47 million. The figures were disclosed in an Apple filing with the US Securities and Exchange Commission on the first day of Ternus’ tenure. How much will John Ternus earn at Apple? Ternus will receive an annual base salary of $3 million. The much larger part of his package comes from Apple shares. His fiscal 2027 equity award has a target value of $55 million. Importantly, this is not guaranteed cash. The value of the stock award can rise or fall depending on Apple’s share price. Ternus will also receive a prorated RSU award worth about $2.5 million for his time as CEO during fiscal 2026. Of his $55 million annual equity award, 75 per cent will be performance-based. It will depend on Apple’s total shareholder return compared with other companies in the S&P 500. The remaining 25 per cent will be time-based shares, vesting in equal instalments every six months over four years. Tim Cook’s new Apple salary revealed Cook’s pay will fall as he moves away from the CEO role, but his new package remains substantial. As executive chairman, Cook will receive an annual salary of $2 million and a fiscal 2027 equity award targeted at $45 million. Half of that stock award will be performance-based, while the other half will vest over four years. Cook earned $74.3 million in total compensation in 2025 as Apple CEO, including a $3 million salary, $12 million in performance-based cash awards and $57.5 million in stock awards. Why Apple’s CEO change matters Ternus is taking charge after Cook’s 15-year run as Apple CEO. Apple said in April that Ternus would succeed Cook from September 1, while Cook would become executive chairman. During Cook’s tenure, Apple grew from a company valued at around $350 billion to roughly $4.5 trillion, according to Reuters. Now Ternus faces a different challenge: keeping Apple’s enormous business growing while pushing harder in areas such as artificial intelligence. The leadership change also comes just days before Apple’s September 9 product event, giving Ternus an early opportunity to shape the company’s next chapter.

Apple has revealed John Ternus’ $58 million target compensation as its new CEO, including a $55 million stock award. Tim Cook will receive a $47 million package as executive chairman, down from his $74.3 million 2025 pay.

How much will Apple CEO John Ternus earn?

Anthropic has launched Claude Fable 5.1 and Claude Mythos 5.1, its latest AI models aimed at coding, knowledge work and scientific research. The company calls them its most advanced models for these tasks, while claiming Fable 5.1 can deliver stronger performance at a lower cost than its predecessor.&nbsp;

<blockquote class="twitter-tweet">We’re introducing Claude Fable 5.1 and Claude Mythos 5.1. They&#39;re the world’s most advanced models for coding and knowledge work. <a href="https://t.co/8P9PSrWPi3">pic.twitter.com/8P9PSrWPi3</a>&mdash; Claude (@claudeai) <a href="https://x.com/claudeai/status/2094848572143407483?ref_src=twsrc%5Etfw">September 1, 2026</a></blockquote> <script async src="https://platform.x.com/widgets.js" charset="utf-8"></script>

The two models are actually the same underlying AI system. The key difference is in their safeguards. Fable 5.1 is available generally, while Mythos 5.1 has fewer restrictions for approved work in areas such as cybersecurity and life sciences.<h2>Claude Fable 5.1 is cheaper and more capable</h2>Anthropic says Fable 5.1 will cost about 25 per cent less than Fable 5 for typical token-based workloads. For highly agentic tasks, where AI carries out longer sequences of actions, savings can reach about 45 per cent because of lower cache-read pricing.&nbsp;The company also says the model is better at long-running tasks and less likely to take shortcuts that reduce the quality of its work. One striking example came from investment firm Millennium. Anthropic says Fable 5.1 identified the cause of an extremely rare software crash that engineers and other AI models had failed to explain for several years.Anthropic is positioning Fable 5.1 as more than a coding assistant. Its tests cover scientific research, business workflows, computer use, multidisciplinary reasoning and software engineering. On Anthropic's reported benchmarks, Fable 5.1 scored 52.6 per cent on Terminal-Bench-Science, compared with 24.7 per cent for Fable 5.&nbsp;Anthropic says early users have also seen improvements in research and long-running projects, suggesting the model is increasingly designed to act as an AI worker rather than simply answer individual prompts.<h2>What is Claude Mythos 5.1?</h2>Mythos 5.1 is the restricted version. Anthropic says it is designed for vetted cyberdefenders and life-science researchers through trusted access programmes. Access is currently limited mainly to selected US organisations.The reason is capability. Anthropic says advanced models in cybersecurity and biology could be useful for legitimate research but could also be misused. For general users, Fable 5.1 is the model that matters. It is available through Claude and Anthropic's API ecosystem, while Anthropic continues to refine safeguards designed to make powerful capabilities usable without opening the same risks as the restricted Mythos version. The launch shows where the AI race is heading: models are no longer being judged only by how well they answer questions. Increasingly, the battle is about whether they can work for hours, solve difficult problems, write and debug software, conduct research and deliver useful results at a lower cost.

Anthropic has launched Claude Fable 5.1 and Mythos 5.1. Fable 5.1 targets coding, research and knowledge work with lower costs and stronger performance, while Mythos 5.1 offers higher-risk capabilities only to vetted cybersecurity and life-science organisations.

Anthropic has launched Claude Fable 5.1 and Claude Mythos 5.1, its latest AI models aimed at coding, knowledge work and scientific research. The company calls them its most advanced models for these tasks, while claiming Fable 5.1 can deliver stronger performance at a lower cost than its predecessor.

Anthropic has launched Claude Fable 5.1 and Mythos 5.1. Fable 5.1 targets coding, research and knowledge work with lower costs and stronger performance, while Mythos 5.1 offers higher-risk capabilities only to vetted cybersecurity and life-science organisations.

Anthropic launches Claude Fable 5.1 and Mythos 5.1, claims major leap in coding and AI research

A new generation of AI-powered market-intelligence tools is attempting to make technical analysis more accessible to India’s multilingual retail-investor base. Kwala Intel, an AI market-intelligence platform focused on Indian markets, allows users to ask questions about stocks, technical indicators and market trends in multiple Indian languages and receive explanations linked to market charts. For millions of retail participants entering India’s financial markets, understanding a stock chart can be almost as challenging as understanding the market itself. Candlesticks, moving averages, oscillators and technical indicators are often accompanied by unfamiliar English terminology, leaving many users dependent on simplified tips rather than understanding how a conclusion was reached.<h2> The Need for Better Retail-Market Education</h2> The development comes against a backdrop of rapidly changing retail participation in Indian markets. SEBI studies have repeatedly highlighted the difficulties faced by individual traders in the futures and options segment, including high rates of losses among retail participants. The numbers have reinforced a broader debate around financial education and the risks of participating in increasingly complex financial products without sufficient understanding. For multilingual users, that gap has an additional dimension. Access to information is not necessarily the same as access to information in a language and format that feels intuitive. That challenge becomes more significant in a country where investors consume financial content in multiple languages. While stock exchanges and much of the financial ecosystem operate primarily in English, many retail users prefer to learn, research and discuss markets in Hindi, Marathi, Gujarati, Bengali, Tamil, Telugu and other Indian languages. Artificial intelligence is now beginning to address both sides of this problem — the complexity of market data and the language barrier.<h2>Making Technical Analysis Easier to Understand</h2>Technical analysis uses a relatively defined set of concepts to study price movements, momentum and market behaviour. Indicators such as the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands and Fibonacci retracements are widely used by market participants. The difficulty for newer users is often not the concept itself, but understanding what the indicator is showing and how it relates to the price chart. For example, an RSI reading may indicate that recent price movements have become unusually strong in one direction. MACD can be used to study changes in momentum, while Bollinger Bands help users examine price movement and volatility around a moving average. Support and resistance levels can provide context around areas where buying or selling activity has historically appeared. AI-powered interfaces are changing that interaction by allowing users to ask questions directly rather than having to search for every individual concept.<h2>Asking the Chart in Your Own Language</h2>Kwala Intel is an example of this emerging approach. The AI-powered market-intelligence platform is designed around a conversational interface through which users can explore stocks, market data and technical-analysis concepts across multiple Indian languages. Instead of navigating several research screens, users can ask questions in a more natural format. A user could ask what the important support and resistance levels are for a stock, whether momentum appears to be strengthening or weakening, or what a particular technical indicator is showing. &nbsp;The platform combines the conversational response with visual market information, allowing users to connect an explanation with the underlying chart rather than receiving only a textbook definition. For example, a user asking about RSI does not necessarily need to remember the indicator’s formula first. The interaction can begin with a simple question and move toward an explanation of what the indicator is showing on the relevant chart. This approach could be particularly relevant for users who are more comfortable communicating in Indian languages.&nbsp;&nbsp;Kwala Intel supports interactions across languages including Hindi, English, Marathi, Gujarati, Bengali, Tamil and Telugu. The founder says its objective is not to eliminate the need for financial knowledge, but to make that knowledge easier to access and understand. &nbsp;<h2>Beyond Indicators: A Broader Market-Research Companion</h2> The use case also extends beyond individual technical indicators. Users can explore company information, understand quarterly results, learn about options and ask broader questions about how different parts of the financial market work. This creates a different model of financial research. Instead of treating market information as a collection of separate screens, reports and terminology, a conversational AI interface allows users to move from one question to the next. That can be useful outside market hours as well. Investors often review charts after the trading session, try to understand a failed setup, examine company results or prepare questions for the following day. A conversational research platform can provide a continuous environment for that learning process.<h2>A More Conversational Future for Financial Research</h2>The emergence of platforms such as Kwala Intel reflects a wider shift in how consumers interact with information. Search engines once required users to know the right keywords. Conversational AI allows users to describe what they want to understand in ordinary language. Applied to financial markets, that shift could make technical concepts more approachable for a wider section of India’s retail-investor population. Website: KwalaIntel.com&nbsp;

Kwala Intel is using AI to make stock-market research and technical analysis easier in Indian languages. The platform lets users ask questions about stocks, charts and indicators in Hindi, Tamil, Telugu and other languages, helping simplify market insights for retail investors.

A new generation of AI-powered market-intelligence tools is attempting to make technical analysis more accessible to India’s multilingual retail-investor base. Kwala Intel, an AI market-intelligence platform focused on Indian markets, allows users to ask questions about stocks, technical indicators and market trends in multiple Indian languages and receive explanations linked to market charts. For millions of retail participants entering India’s financial markets, understanding a stock chart can be almost as challenging as understanding the market itself. Candlesticks, moving averages, oscillators and technical indicators are often accompanied by unfamiliar English terminology, leaving many users dependent on simplified tips rather than understanding how a conclusion was reached. The Need for Better Retail-Market Education The development comes against a backdrop of rapidly changing retail participation in Indian markets. SEBI studies have repeatedly highlighted the difficulties faced by individual traders in the futures and options segment, including high rates of losses among retail participants. The numbers have reinforced a broader debate around financial education and the risks of participating in increasingly complex financial products without sufficient understanding. For multilingual users, that gap has an additional dimension. Access to information is not necessarily the same as access to information in a language and format that feels intuitive. That challenge becomes more significant in a country where investors consume financial content in multiple languages. While stock exchanges and much of the financial ecosystem operate primarily in English, many retail users prefer to learn, research and discuss markets in Hindi, Marathi, Gujarati, Bengali, Tamil, Telugu and other Indian languages. Artificial intelligence is now beginning to address both sides of this problem — the complexity of market data and the language barrier. Making Technical Analysis Easier to Understand Technical analysis uses a relatively defined set of concepts to study price movements, momentum and market behaviour. Indicators such as the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Bollinger Bands and Fibonacci retracements are widely used by market participants. The difficulty for newer users is often not the concept itself, but understanding what the indicator is showing and how it relates to the price chart. For example, an RSI reading may indicate that recent price movements have become unusually strong in one direction. MACD can be used to study changes in momentum, while Bollinger Bands help users examine price movement and volatility around a moving average. Support and resistance levels can provide context around areas where buying or selling activity has historically appeared. AI-powered interfaces are changing that interaction by allowing users to ask questions directly rather than having to search for every individual concept. Asking the Chart in Your Own Language Kwala Intel is an example of this emerging approach. The AI-powered market-intelligence platform is designed around a conversational interface through which users can explore stocks, market data and technical-analysis concepts across multiple Indian languages. Instead of navigating several research screens, users can ask questions in a more natural format. A user could ask what the important support and resistance levels are for a stock, whether momentum appears to be strengthening or weakening, or what a particular technical indicator is showing. The platform combines the conversational response with visual market information, allowing users to connect an explanation with the underlying chart rather than receiving only a textbook definition. For example, a user asking about RSI does not necessarily need to remember the indicator’s formula first. The interaction can begin with a simple question and move toward an explanation of what the indicator is showing on the relevant chart. This approach could be particularly relevant for users who are more comfortable communicating in Indian languages. Kwala Intel supports interactions across languages including Hindi, English, Marathi, Gujarati, Bengali, Tamil and Telugu. The founder says its objective is not to eliminate the need for financial knowledge, but to make that knowledge easier to access and understand. Beyond Indicators: A Broader Market-Research Companion The use case also extends beyond individual technical indicators. Users can explore company information, understand quarterly results, learn about options and ask broader questions about how different parts of the financial market work. This creates a different model of financial research. Instead of treating market information as a collection of separate screens, reports and terminology, a conversational AI interface allows users to move from one question to the next. That can be useful outside market hours as well. Investors often review charts after the trading session, try to understand a failed setup, examine company results or prepare questions for the following day. A conversational research platform can provide a continuous environment for that learning process. A More Conversational Future for Financial Research The emergence of platforms such as Kwala Intel reflects a wider shift in how consumers interact with information. Search engines once required users to know the right keywords. Conversational AI allows users to describe what they want to understand in ordinary language. Applied to financial markets, that shift could make technical concepts more approachable for a wider section of India’s retail-investor population. Website: KwalaIntel.com

Kwala Intel is using AI to make stock-market research and technical analysis easier in Indian languages. The platform lets users ask questions about stocks, charts and indicators in Hindi, Tamil, Telugu and other languages, helping simplify market insights for retail investors.

This Indian AI is making stock charts easier to understand in Hindi, Tamil, Telugu and other Indian languages

Competitive exam preparation in 2026 looks quite different from the rote memorisation of previous generations, where students were vastly reliant on varied sources, materials and notes from multiple institutes or online materials. However, after the introduction of conversational AI tutors like ChatGPT and Claude, the preparation has become very easy and accessible to use. This chat-native learning now provides answers to questions, generates practice problems, and simulates Socratic dialogues, while multimodal systems like Gemini process text, images, diagrams, and documents simultaneously for visual learning. Other than these tools, other platforms are also utilised for multiple processes and learning while preparing for the competitive exam. No matter how these technologies change the way of preparation for the student, rote learning can never be completely eradicated, but it will prompt students to opt for a hybrid strategy. Rather than replacing textbooks entirely, the most successful students are still relying on traditional materials for foundational understanding while turning to AI for active practice, question generation, and diagram analysis. Platforms are also personalising the journey of students, allowing aspirants to upload syllabi, track progress, and generate revision schedules, helping identify weak areas over time.&nbsp;Also read: <a href="https://www.wionews.com/india-news/explained-how-will-india-s-new-rs-62-500-crore-smartphone-manufacturing-scheme-will-boost-local-brands-1787482953768">EXPLAINED: How will India’s new Rs 62,500-crore smartphone manufacturing scheme boost local brands?</a><h3>Experts on chat-native learning</h3>Several experts have sided with the integration of chatbot learning, which provides better accessibility, time-saving, more resourcesful at single platform and quality of preparation. However, some experts have cautioned students, warning against an "illusion of learning," where over-reliance on AI could weaken students' critical thinking and metacognitive skills, stressing that the goal should be augmentation rather than replacement. 1. How is AI reshaping competitive exam preparation in India, and what key shifts are you seeing in how students consume and engage with educational content?&nbsp;Prempreet Singh, Founder &amp; CEO, SkillBytes: The biggest shift is away from consuming more content toward doing more. Students were never short on material; they were short on a daily practice habit. What we see now is a move from passive rote learning, reading and re-reading, toward active recall in small doses. AI makes that possible at scale, delivering the right practice and instant feedback to lakhs of students at once, inside the formats they already use rather than another app they have to open.&nbsp;2. Why is microlearning and chat-based learning gaining traction, and can these formats address challenges such as shorter attention spans and information overload?&nbsp;Prempreet Singh, Founder &amp; CEO, SkillBytes: Because it fits how students actually live. A teenager will not defend a thirty-minute study block, but they will finish a five-minute unit inside a chat they are already in. Microlearning works with fragmented attention instead of fighting it, and closes the loop while focus is still warm. It does not solve information overload by adding more; it solves it by shrinking each step until starting is effortless and finishing is the default, not the exception.&nbsp;3. How can AI-driven personalisation help identify learning gaps and make exam preparation more accessible and outcome-oriented for students across India?&nbsp;Prempreet Singh, Founder &amp; CEO, SkillBytes: Personalisation is where the technology and our roadmap are heading, not a solved feature anyone should claim today. The direction is clear: an experience that responds to each learner, focusing limited time where a student is weakest rather than teaching to the average. On accessibility, the unlock is delivery: no download, no login, no fixed device, so a student on a shared phone gets the same experience as anyone else. That is what widens access across India, well beyond the metros.&nbsp;4. What are the key opportunities and challenges for edtech platforms as AI becomes increasingly integrated into mainstream education and test preparation?&nbsp;Prempreet Singh, Founder &amp; CEO, SkillBytes: The opportunity is reach: quality preparation can now travel to any student on the phone already in their hand. The challenge is discipline. It is easy to add more content and mistake activity for learning. The harder, more valuable work is building genuine habit and being honest about what the technology does today versus what it will do tomorrow. Platforms that overclaim on AI will lose trust; the ones that stay grounded will earn durable engagement.&nbsp;5. What has SkillBytes observed from student engagement with its AI-led learning approach, and how does the platform see its model evolving over the next few years?&nbsp;Prempreet Singh, Founder &amp; CEO, SkillBytes: We measure engagement and consistency, not exam outcomes, because that daily return to practice is the leading indicator we are willing to be judged on. Across more than 9,00,000 students and tens of millions of interactions, sessions average over 30 messages, which tells us learning is becoming a habit rather than a one-time signup. Over the next few years, the model deepens across JEE, NEET, and UPSC, and travels beyond India through SAT and IELTS, where the format carries.&nbsp;Similarly, Kushal Raj Chakravorty, Founder and Managing Trutee- Lotus Petal Foundation, said, “AI can help shift competitive exam preparation from memorising answers to understanding concepts. A student can now ask questions in their own words, get explanations at their own convenience, practise continuously and identify learning gaps with feedback. For students from underserved communities, this is especially powerful because access to quality coaching and personalised academic support has never been equal. However, it is important to note that AI must complement and not replace teachers. The real opportunity is in combining technology with quality teaching so that students learn not just to find the right answer, but to think, question and solve problems independently.”

No matter how these technologies change the way of preparation for the student, rote learning can never be completely eradicated, but it will prompt students to opt for a hybrid strategy.

Competitive exam preparation in 2026 looks quite different from the rote memorisation of previous generations, where students were vastly reliant on varied sources, materials and notes from multiple institutes or online materials. However, after the introduction of conversational AI tutors like ChatGPT and Claude, the preparation has become very easy and accessible to use. This chat-native learning now provides answers to questions, generates practice problems, and simulates Socratic dialogues, while multimodal systems like Gemini process text, images, diagrams, and documents simultaneously for visual learning. Other than these tools, other platforms are also utilised for multiple processes and learning while preparing for the competitive exam. No matter how these technologies change the way of preparation for the student, rote learning can never be completely eradicated, but it will prompt students to opt for a hybrid strategy. Rather than replacing textbooks entirely, the most successful students are still relying on traditional materials for foundational understanding while turning to AI for active practice, question generation, and diagram analysis. Platforms are also personalising the journey of students, allowing aspirants to upload syllabi, track progress, and generate revision schedules, helping identify weak areas over time. Also read: EXPLAINED: How will India’s new Rs 62,500-crore smartphone manufacturing scheme boost local brands? Experts on chat-native learning Several experts have sided with the integration of chatbot learning, which provides better accessibility, time-saving, more resourcesful at single platform and quality of preparation. However, some experts have cautioned students, warning against an "illusion of learning," where over-reliance on AI could weaken students' critical thinking and metacognitive skills, stressing that the goal should be augmentation rather than replacement. 1. How is AI reshaping competitive exam preparation in India, and what key shifts are you seeing in how students consume and engage with educational content? Prempreet Singh, Founder & CEO, SkillBytes: The biggest shift is away from consuming more content toward doing more. Students were never short on material; they were short on a daily practice habit. What we see now is a move from passive rote learning, reading and re-reading, toward active recall in small doses. AI makes that possible at scale, delivering the right practice and instant feedback to lakhs of students at once, inside the formats they already use rather than another app they have to open. 2. Why is microlearning and chat-based learning gaining traction, and can these formats address challenges such as shorter attention spans and information overload? Prempreet Singh, Founder & CEO, SkillBytes: Because it fits how students actually live. A teenager will not defend a thirty-minute study block, but they will finish a five-minute unit inside a chat they are already in. Microlearning works with fragmented attention instead of fighting it, and closes the loop while focus is still warm. It does not solve information overload by adding more; it solves it by shrinking each step until starting is effortless and finishing is the default, not the exception. 3. How can AI-driven personalisation help identify learning gaps and make exam preparation more accessible and outcome-oriented for students across India? Prempreet Singh, Founder & CEO, SkillBytes: Personalisation is where the technology and our roadmap are heading, not a solved feature anyone should claim today. The direction is clear: an experience that responds to each learner, focusing limited time where a student is weakest rather than teaching to the average. On accessibility, the unlock is delivery: no download, no login, no fixed device, so a student on a shared phone gets the same experience as anyone else. That is what widens access across India, well beyond the metros. 4. What are the key opportunities and challenges for edtech platforms as AI becomes increasingly integrated into mainstream education and test preparation? Prempreet Singh, Founder & CEO, SkillBytes: The opportunity is reach: quality preparation can now travel to any student on the phone already in their hand. The challenge is discipline. It is easy to add more content and mistake activity for learning. The harder, more valuable work is building genuine habit and being honest about what the technology does today versus what it will do tomorrow. Platforms that overclaim on AI will lose trust; the ones that stay grounded will earn durable engagement. 5. What has SkillBytes observed from student engagement with its AI-led learning approach, and how does the platform see its model evolving over the next few years? Prempreet Singh, Founder & CEO, SkillBytes: We measure engagement and consistency, not exam outcomes, because that daily return to practice is the leading indicator we are willing to be judged on. Across more than 9,00,000 students and tens of millions of interactions, sessions average over 30 messages, which tells us learning is becoming a habit rather than a one-time signup. Over the next few years, the model deepens across JEE, NEET, and UPSC, and travels beyond India through SAT and IELTS, where the format carries. Similarly, Kushal Raj Chakravorty, Founder and Managing Trutee- Lotus Petal Foundation, said, “AI can help shift competitive exam preparation from memorising answers to understanding concepts. A student can now ask questions in their own words, get explanations at their own convenience, practise continuously and identify learning gaps with feedback. For students from underserved communities, this is especially powerful because access to quality coaching and personalised academic support has never been equal. However, it is important to note that AI must complement and not replace teachers. The real opportunity is in combining technology with quality teaching so that students learn not just to find the right answer, but to think, question and solve problems independently.”

No matter how these technologies change the way of preparation for the student, rote learning can never be completely eradicated, but it will prompt students to opt for a hybrid strategy.

From rote learning to chat-native learning: How AI is changing way students prepare for competitive exams

Mahindra is about to make its existing electric SUVs considerably smarter. From January 2027, the company will begin rolling out Google Gemini-powered AI and other software features to the BE 6, XEV 9e and XEV 9S through over-the-air updates.&nbsp;The move means owners will not need to buy a new car to get many of Mahindra's latest software features. Mahindra says its MAIA (Mahindra Artificial Intelligence Architecture) platform allows the vehicles to evolve through software updates.&nbsp;<h2>Google Gemini is coming to existing Mahindra EVs</h2>The new BE 6 SPORTEQ already gets TEQ_Talk, Mahindra's conversational in-car assistant built with Google Gemini. The same technology will move to the older BE 6, XEV 9e and XEV 9S. Mahindra says TEQ_Talk uses 17 specialised AI agents and supports more than 100 core functions and 48 applications, covering navigation, entertainment, vehicle controls and general information.&nbsp;Instead of remembering fixed voice commands, drivers can speak more naturally. For example, a request such as asking the car to make the cabin cooler can trigger the relevant climate-control function. The BE 6 SPORTEQ was developed with Google Cloud around MAIA and Google's Gemini technology, with Mahindra positioning the system as a more conversational alternative to traditional voice assistants.&nbsp;<h2>More than just Gemini</h2>The software upgrade is not limited to the AI assistant.&nbsp;Mahindra's TEQ_Me can automatically identify a user profile and adjust settings such as the seat, mirrors, climate, infotainment, head-up display and drive modes. TEQ_Secure adds features including 360-degree camera and dashcam monitoring through the Me4U app, audio relay, vehicle tracking and digital keys across smartphones, smartwatches and NFC cards. Then there is TEQ_Drive. It introduces custom drive settings and a drift mode, while Revive can provide additional range after the battery reaches zero to help reach a charger. Mahindra says Revive can add up to 13km, with Revive SOS providing up to another 11km in emergencies.&nbsp;<h2>Cars that keep getting better after purchase</h2>Mahindra is also bringing TEQ_Play, which adds features such as gaming with up to four Bluetooth controllers, karaoke, private audio and music-synchronised lighting. The important change is how these features reach customers. Mahindra has confirmed that software introduced with the BE 6 SPORTEQ will be rolled out to existing BE 6, XEV 9e and XEV 9S owners through OTA updates from January 2027, although the exact feature set will vary by vehicle and variant. For Mahindra, the strategy is bigger than adding another voice assistant. It is turning its electric SUVs into software-defined vehicles, where new functions can arrive after the car has already been bought. That could change what buyers expect from a car: instead of a vehicle remaining largely the same after purchase, its software can continue to evolve.

Mahindra will bring Google Gemini and new software features to existing BE 6, XEV 9e and XEV 9S electric SUVs from January 2027. The OTA update will add conversational AI, personalised settings, security tools, driving functions and entertainment features.

Mahindra is about to make its existing electric SUVs considerably smarter. From January 2027, the company will begin rolling out Google Gemini-powered AI and other software features to the BE 6, XEV 9e and XEV 9S through over-the-air updates. The move means owners will not need to buy a new car to get many of Mahindra's latest software features. Mahindra says its MAIA (Mahindra Artificial Intelligence Architecture) platform allows the vehicles to evolve through software updates. Google Gemini is coming to existing Mahindra EVs The new BE 6 SPORTEQ already gets TEQ_Talk, Mahindra's conversational in-car assistant built with Google Gemini. The same technology will move to the older BE 6, XEV 9e and XEV 9S. Mahindra says TEQ_Talk uses 17 specialised AI agents and supports more than 100 core functions and 48 applications, covering navigation, entertainment, vehicle controls and general information. Instead of remembering fixed voice commands, drivers can speak more naturally. For example, a request such as asking the car to make the cabin cooler can trigger the relevant climate-control function. The BE 6 SPORTEQ was developed with Google Cloud around MAIA and Google's Gemini technology, with Mahindra positioning the system as a more conversational alternative to traditional voice assistants. More than just Gemini The software upgrade is not limited to the AI assistant. Mahindra's TEQ_Me can automatically identify a user profile and adjust settings such as the seat, mirrors, climate, infotainment, head-up display and drive modes. TEQ_Secure adds features including 360-degree camera and dashcam monitoring through the Me4U app, audio relay, vehicle tracking and digital keys across smartphones, smartwatches and NFC cards. Then there is TEQ_Drive. It introduces custom drive settings and a drift mode, while Revive can provide additional range after the battery reaches zero to help reach a charger. Mahindra says Revive can add up to 13km, with Revive SOS providing up to another 11km in emergencies. Cars that keep getting better after purchase Mahindra is also bringing TEQ_Play, which adds features such as gaming with up to four Bluetooth controllers, karaoke, private audio and music-synchronised lighting. The important change is how these features reach customers. Mahindra has confirmed that software introduced with the BE 6 SPORTEQ will be rolled out to existing BE 6, XEV 9e and XEV 9S owners through OTA updates from January 2027, although the exact feature set will vary by vehicle and variant. For Mahindra, the strategy is bigger than adding another voice assistant. It is turning its electric SUVs into software-defined vehicles, where new functions can arrive after the car has already been bought. That could change what buyers expect from a car: instead of a vehicle remaining largely the same after purchase, its software can continue to evolve.

Mahindra will bring Google Gemini and new software features to existing BE 6, XEV 9e and XEV 9S electric SUVs from January 2027. The OTA update will add conversational AI, personalised settings, security tools, driving functions and entertainment features.

Google Gemini is coming to Mahindra EVs in 2027: Here’s what your EV will be able to do

OpenAI has revealed the first performance results from Jalapeño, its custom AI chip designed specifically to run AI models. CEO Sam Altman summed up the development in a short post: “we made a chip and it is fast.” The announcement marks an important shift for OpenAI. The company is no longer only building AI models such as ChatGPT. It is also designing the hardware that runs them. OpenAI says Jalapeño delivered 1.5 to 1.9 times more AI work per watt than the comparison systems across GPT-OSS 120B, DeepSeek R1 and Kimi K2.5 1T. It also recorded 1.7 to 3.6 times lower end-to-end latency in the company's tests.<h2>Why OpenAI built its own chip</h2>Jalapeño is an inference chip. In simple terms, inference is the stage when an AI model actually answers a user's request. Every ChatGPT question requires inference. So do coding agents, AI assistants and API requests. OpenAI designed Jalapeño around these workloads rather than trying to make a general-purpose processor. The company worked with Broadcom on the chip and Celestica on boards, racks and production systems. The idea is to optimise the entire system together including the chip, memory, networking and software. That matters because AI companies are facing two major problems: huge computing demand and enormous electricity costs.&nbsp;<h2>Jalapeño vs Nvidia: what the numbers show</h2>OpenAI compared Jalapeño with commercial systems built around Nvidia accelerators using the InferenceX benchmark. The chip is rated at 700 watts, while the Nvidia systems used in the comparison were rated at 1,200W or 1,400W, depending on the test. OpenAI says Jalapeño delivered stronger performance per unit of power while also reducing latency. For highly interactive AI workloads, OpenAI reported up to 4.1 times higher performance. However, these are OpenAI-reported benchmark results on selected workloads. They do not mean Jalapeño has replaced Nvidia across AI computing.&nbsp;<h2>OpenAI is not ditching Nvidia</h2>This is perhaps the most important detail. OpenAI plans to begin deploying Jalapeño in its own computing infrastructure by the end of 2026. But the company says it will continue deploying Nvidia and other accelerators widely for both training and inference.&nbsp;Jalapeño is instead the beginning of a multi-generation chip programme. OpenAI says its second generation is already deep in development, while a third generation is taking shape. The company also says AI itself helped build Jalapeño. OpenAI moved from initial design to tape-out in nine months, using AI to explore implementations, optimise circuits and speed up engineering and testing. The bigger goal is straightforward: more AI work from the same power and hardware. If OpenAI can make that happen at scale, the result could be faster ChatGPT responses, more capable AI agents and lower costs as demand continues to surge.&nbsp;

OpenAI has revealed Jalapeño, its first custom AI inference chip, developed with Broadcom. The company says it delivers up to 1.9x more AI work per watt and up to 3.6x lower latency than comparison systems, while Nvidia remains part of its broader hardware strategy.

OpenAI has revealed the first performance results from Jalapeño, its custom AI chip designed specifically to run AI models. CEO Sam Altman summed up the development in a short post: “we made a chip and it is fast.” The announcement marks an important shift for OpenAI. The company is no longer only building AI models such as ChatGPT. It is also designing the hardware that runs them. OpenAI says Jalapeño delivered 1.5 to 1.9 times more AI work per watt than the comparison systems across GPT-OSS 120B, DeepSeek R1 and Kimi K2.5 1T. It also recorded 1.7 to 3.6 times lower end-to-end latency in the company's tests. Why OpenAI built its own chip Jalapeño is an inference chip. In simple terms, inference is the stage when an AI model actually answers a user's request. Every ChatGPT question requires inference. So do coding agents, AI assistants and API requests. OpenAI designed Jalapeño around these workloads rather than trying to make a general-purpose processor. The company worked with Broadcom on the chip and Celestica on boards, racks and production systems. The idea is to optimise the entire system together including the chip, memory, networking and software. That matters because AI companies are facing two major problems: huge computing demand and enormous electricity costs. Jalapeño vs Nvidia: what the numbers show OpenAI compared Jalapeño with commercial systems built around Nvidia accelerators using the InferenceX benchmark. The chip is rated at 700 watts, while the Nvidia systems used in the comparison were rated at 1,200W or 1,400W, depending on the test. OpenAI says Jalapeño delivered stronger performance per unit of power while also reducing latency. For highly interactive AI workloads, OpenAI reported up to 4.1 times higher performance. However, these are OpenAI-reported benchmark results on selected workloads. They do not mean Jalapeño has replaced Nvidia across AI computing. OpenAI is not ditching Nvidia This is perhaps the most important detail. OpenAI plans to begin deploying Jalapeño in its own computing infrastructure by the end of 2026. But the company says it will continue deploying Nvidia and other accelerators widely for both training and inference. Jalapeño is instead the beginning of a multi-generation chip programme. OpenAI says its second generation is already deep in development, while a third generation is taking shape. The company also says AI itself helped build Jalapeño. OpenAI moved from initial design to tape-out in nine months, using AI to explore implementations, optimise circuits and speed up engineering and testing. The bigger goal is straightforward: more AI work from the same power and hardware. If OpenAI can make that happen at scale, the result could be faster ChatGPT responses, more capable AI agents and lower costs as demand continues to surge.

OpenAI has revealed Jalapeño, its first custom AI inference chip, developed with Broadcom. The company says it delivers up to 1.9x more AI work per watt and up to 3.6x lower latency than comparison systems, while Nvidia remains part of its broader hardware strategy.

Nvidia faces a new challenge as OpenAI reveals its first AI chip

Five years ago, in August 2021, the Indian space agency ISRO launched India's first agile Earth observation satellite, GISAT-1, from Sriharikota on the GSLV-F10 rocket. The satellite was lost after the mid-flight failure of the rocket. WION has learnt that the 52-meters-tall, three-stage GSLV-F17 rocket, carrying a replacement for the GISAT, has been moved to the second launchpad at Satish Dhawan Space Centre(SDSC), Sriharikota, around 8:00 am, Friday, 28th August. It is a standard practice at ISRO to move its relatively larger rockets (such as PSLV, GSLV, LVM3) to the launchpad a week ahead of the liftoff date. The GSLV-F17 rocket will be carrying a strategic-use Earth-imaging satellite known as GISAT-1A or EOS-05, which is a replacement for the GISAT-1 lost in 2021.Also read | <a href="https://www.wionews.com/india-news/nasa-invites-isro-moon-base-programme-lunar-outpost-1786450433879">NASA invites ISRO to build a base on the Moon</a>This upcoming launch, scheduled for the first week of September, will also mark the end of ISRO's seven-month period of lull. The Government-run ISRO has not launched any of its rockets so far in 2026, after the mid-flight failure of the PSLV-C62 rocket in January this year, which happened to be the second PSLV failure in a row. The PSLV-C61 rocket also failed mid-flight in May 2025. Such back-to-back failures are unprecedented in the 33 years of PSLV flights. While the C-61 carried ISRO's strategic-use Earth-imaging satellite EOS-09, the C-62 carried an Earth-imaging satellite EOS-N1 and more than a dozen customer satellites.&nbsp; Weighing over 2,200kg, the EOS-05/GISAT-1A is an agile Earth observation satellite that is to be placed in Geostationary orbit, about 36,000 km above the Earth. The GSLV rocket will hurl the satellite into an initial elliptical(egg-shaped) orbit, following which the satellite will fire its onboard engines to gradually circularize its orbit and reach its final destination. This satellite is meant to provide near real-time imaging of large-area regions of interest at frequent intervals, for quick monitoring of natural disasters, episodic events, and any short-term events, to obtain spectral signatures for agriculture, forestry, water bodies, as well as for disaster warning, cyclone monitoring, cloud burst/thunderstorm monitoring etc.<h2>Better late than never: A resurrection for GISAT</h2>GISAT-1, India's first agile Earth observation satellite, was launched from Sriharikota on the GSLV-F10 rocket on August 12, 2021. While the first and second stages of the rocket performed normally, the final Cryogenic Stage did not ignite due to a technical anomaly. The mission couldn't be accomplished as intended and the satellite GISAT-1 was lost during the mid-flight failure. GISAT-1A or EOS-05, which ISRO intends to launch next week, is a replacement for the lost GISAT-1.Losses and failures are common in spaceflight. However, the ability to return with a successful mission is the true test of any spacefaring entity. That it has taken five long years for India to replace a satellite lost in 2021, is a sad and pitiable reminder of the pace at which strategic missions are being executed.<a href="https://www.wionews.com/india-news/india-may-need-2-3-years-to-replace-3-strategic-satellites-lost-in-12-months-1768914607847">Also read | India may need 2-3 years to replace 3 strategic satellites lost in 12 months</a>Of the six space launch missions that the Indian space agency ISRO performed from home soil between January 2025 and January 2026, three have failed. These are: GSLV-F15/NVS-02(satellite failure) in Jan 2025, PSLV-C61/EOS-09(mid-flight rocket failure and satellite loss) in May 2025, and PSLV-C62/EOS-N1(mid-flight rocket failure and satellite loss) in January 2026. All three Government-funded satellites lost in these failed missions were critical for India's national security. While it is certain that ISRO will return with successful missions and replace these satellites, this author had estimated that India would need between two to three years to replace all three national security satellites lost in the said period. The five years it took to bring the GISAT back to the launchpad is ample testimony!&nbsp;

Five years after losing GISAT-1 in a GSLV failure, ISRO is preparing to launch its replacement. The GSLV-F17 rocket has now reached Sriharikota's launchpad, setting the stage for a mission with major strategic and disaster-monitoring capabilities.

Five years ago, in August 2021, the Indian space agency ISRO launched India's first agile Earth observation satellite, GISAT-1, from Sriharikota on the GSLV-F10 rocket. The satellite was lost after the mid-flight failure of the rocket. WION has learnt that the 52-meters-tall, three-stage GSLV-F17 rocket, carrying a replacement for the GISAT, has been moved to the second launchpad at Satish Dhawan Space Centre(SDSC), Sriharikota, around 8:00 am, Friday, 28th August. It is a standard practice at ISRO to move its relatively larger rockets (such as PSLV, GSLV, LVM3) to the launchpad a week ahead of the liftoff date. The GSLV-F17 rocket will be carrying a strategic-use Earth-imaging satellite known as GISAT-1A or EOS-05, which is a replacement for the GISAT-1 lost in 2021. Also read | NASA invites ISRO to build a base on the Moon This upcoming launch, scheduled for the first week of September, will also mark the end of ISRO's seven-month period of lull. The Government-run ISRO has not launched any of its rockets so far in 2026, after the mid-flight failure of the PSLV-C62 rocket in January this year, which happened to be the second PSLV failure in a row. The PSLV-C61 rocket also failed mid-flight in May 2025. Such back-to-back failures are unprecedented in the 33 years of PSLV flights. While the C-61 carried ISRO's strategic-use Earth-imaging satellite EOS-09, the C-62 carried an Earth-imaging satellite EOS-N1 and more than a dozen customer satellites. Weighing over 2,200kg, the EOS-05/GISAT-1A is an agile Earth observation satellite that is to be placed in Geostationary orbit, about 36,000 km above the Earth. The GSLV rocket will hurl the satellite into an initial elliptical(egg-shaped) orbit, following which the satellite will fire its onboard engines to gradually circularize its orbit and reach its final destination. This satellite is meant to provide near real-time imaging of large-area regions of interest at frequent intervals, for quick monitoring of natural disasters, episodic events, and any short-term events, to obtain spectral signatures for agriculture, forestry, water bodies, as well as for disaster warning, cyclone monitoring, cloud burst/thunderstorm monitoring etc. Better late than never: A resurrection for GISAT GISAT-1, India's first agile Earth observation satellite, was launched from Sriharikota on the GSLV-F10 rocket on August 12, 2021. While the first and second stages of the rocket performed normally, the final Cryogenic Stage did not ignite due to a technical anomaly. The mission couldn't be accomplished as intended and the satellite GISAT-1 was lost during the mid-flight failure. GISAT-1A or EOS-05, which ISRO intends to launch next week, is a replacement for the lost GISAT-1. Losses and failures are common in spaceflight. However, the ability to return with a successful mission is the true test of any spacefaring entity. That it has taken five long years for India to replace a satellite lost in 2021, is a sad and pitiable reminder of the pace at which strategic missions are being executed. Also read | India may need 2-3 years to replace 3 strategic satellites lost in 12 months Of the six space launch missions that the Indian space agency ISRO performed from home soil between January 2025 and January 2026, three have failed. These are: GSLV-F15/NVS-02(satellite failure) in Jan 2025, PSLV-C61/EOS-09(mid-flight rocket failure and satellite loss) in May 2025, and PSLV-C62/EOS-N1(mid-flight rocket failure and satellite loss) in January 2026. All three Government-funded satellites lost in these failed missions were critical for India's national security. While it is certain that ISRO will return with successful missions and replace these satellites, this author had estimated that India would need between two to three years to replace all three national security satellites lost in the said period. The five years it took to bring the GISAT back to the launchpad is ample testimony!

Five years after losing GISAT-1 in a GSLV failure, ISRO is preparing to launch its replacement. The GSLV-F17 rocket has now reached Sriharikota's launchpad, setting the stage for a mission with major strategic and disaster-monitoring capabilities.

5 years after GSLV-F10 failure, ISRO to replace Earth-imaging GISAT

Meta CEO Mark Zuckerberg and his top executives reportedly drew up an ambitious plan earlier this year to transform the social media giant into an “AI native” company. They wanted artificial intelligence to take over much of the work currently done by thousands of employees.Codenamed “Project OT”, short for Organisation Transformation, the plan was discussed at Meta’s annual leadership retreat in Hawaii in January. According to internal documents reviewed by Reuters and people familiar with the project, the strategy envisioned AI-powered virtual workers being managed by smaller teams of human employees.Executives also considered scenarios that could cut some teams by as much as 60 per cent, according to two people familiar with the discussions. Some employees could have been moved into newly created roles, while others faced layoffs. An internal document suggested the cuts could have been as large as or larger than Meta’s workforce reduction of about 25 per cent three years ago.Also read: <a href="https://www.wionews.com/trending/video-remember-the-coupe-who-climbed-empire-state-building-they-are-facing-burglary-criminal-mischief-charges-1787659415861">Video | Remember the couple who climbed Empire State Building? They are facing burglary, criminal mischief charges</a><h2>What exactly was the plan?</h2>The restructuring was planned in two waves, with the first round scheduled for May and a second in November. The strategy included layoffs, closing vacant positions and removing employees considered poor performers, according to internal planning documents reviewed by Reuters.But the plan began to unravel before the second phase could take place.On the night of May 19, just hours before the first round of layoffs, Zuckerberg called off plans for the November cuts, according to the report. Meta went ahead with layoffs affecting 10 per cent of its workforce the next day.<h2>Why this plan?</h2>The decision came as employees increasingly questioned whether Meta’s push into AI was ultimately aimed at replacing them. At the same time, internal data was reportedly showing that AI agent technology, a key part of the company’s strategy, was not producing the expected productivity gains.The developments also came as some investors questioned the results of Meta’s huge spending on artificial intelligence.Also read: <a href="https://www.wionews.com/world/what-is-us-dollar-system-how-powerful-is-bessent-s-economic-outcast-warning-wion-explains-1787645878031">What is US dollar system? How powerful is Bessent’s ‘Economic Outcast’ warning for China | WION Explains</a>Reuters, citing scores of internal documents, posts and recordings, as well as interviews with more than 20 people familiar with Meta’s operations, reported that the company had been considering a far-reaching overhaul of its workforce. The reporting also highlighted how quickly the plans changed as the company faced resistance from employees and uncertainty over the performance of its AI systems.<h2>What did Meta say?</h2>Meta confirmed the existence of Project OT in response to the Reuters report. The company described it as a year-long effort focused on cutting costs, redesigning teams and moving employees towards priority areas, including the production of training data for its AI models.Meta also acknowledged that the restructuring was planned in two waves and that some scenarios involved reducing individual teams by up to 60 per cent. But it stressed that this did not mean it planned to cut 60 per cent of its overall workforce.The company said the scenarios involved both layoffs and redeployments and that several major teams were not included in the exercise. Meta also said thousands of employees were ultimately moved into newly established teams focused on priority work.“Ultimately, we didn’t move forward with every scenario from the exercise,” Meta said in a statement, adding that it was never assumed all the scenarios would be implemented.

Meta’s secret "Project OT" aimed to replace employees with AI, projecting up to 60 per cent team cuts. The plan was scaled back following internal backlash, investor concerns, and underperforming AI technology.

Meta CEO Mark Zuckerberg and his top executives reportedly drew up an ambitious plan earlier this year to transform the social media giant into an “AI native” company. They wanted artificial intelligence to take over much of the work currently done by thousands of employees. Codenamed “Project OT”, short for Organisation Transformation, the plan was discussed at Meta’s annual leadership retreat in Hawaii in January. According to internal documents reviewed by Reuters and people familiar with the project, the strategy envisioned AI-powered virtual workers being managed by smaller teams of human employees. Executives also considered scenarios that could cut some teams by as much as 60 per cent, according to two people familiar with the discussions. Some employees could have been moved into newly created roles, while others faced layoffs. An internal document suggested the cuts could have been as large as or larger than Meta’s workforce reduction of about 25 per cent three years ago. Also read: Video | Remember the couple who climbed Empire State Building? They are facing burglary, criminal mischief charges What exactly was the plan? The restructuring was planned in two waves, with the first round scheduled for May and a second in November. The strategy included layoffs, closing vacant positions and removing employees considered poor performers, according to internal planning documents reviewed by Reuters. But the plan began to unravel before the second phase could take place. On the night of May 19, just hours before the first round of layoffs, Zuckerberg called off plans for the November cuts, according to the report. Meta went ahead with layoffs affecting 10 per cent of its workforce the next day. Why this plan? The decision came as employees increasingly questioned whether Meta’s push into AI was ultimately aimed at replacing them. At the same time, internal data was reportedly showing that AI agent technology, a key part of the company’s strategy, was not producing the expected productivity gains. The developments also came as some investors questioned the results of Meta’s huge spending on artificial intelligence. Also read: What is US dollar system? How powerful is Bessent’s ‘Economic Outcast’ warning for China | WION Explains Reuters, citing scores of internal documents, posts and recordings, as well as interviews with more than 20 people familiar with Meta’s operations, reported that the company had been considering a far-reaching overhaul of its workforce. The reporting also highlighted how quickly the plans changed as the company faced resistance from employees and uncertainty over the performance of its AI systems. What did Meta say? Meta confirmed the existence of Project OT in response to the Reuters report. The company described it as a year-long effort focused on cutting costs, redesigning teams and moving employees towards priority areas, including the production of training data for its AI models. Meta also acknowledged that the restructuring was planned in two waves and that some scenarios involved reducing individual teams by up to 60 per cent. But it stressed that this did not mean it planned to cut 60 per cent of its overall workforce. The company said the scenarios involved both layoffs and redeployments and that several major teams were not included in the exercise. Meta also said thousands of employees were ultimately moved into newly established teams focused on priority work. “Ultimately, we didn’t move forward with every scenario from the exercise,” Meta said in a statement, adding that it was never assumed all the scenarios would be implemented.

Meta’s secret "Project OT" aimed to replace employees with AI, projecting up to 60 per cent team cuts. The plan was scaled back following internal backlash, investor concerns, and underperforming AI technology.

Zuckerberg had SECRET AI plan for Meta: 60% cuts, ‘virtual workers’. But then something went wrong

Nearly 700 artificial intelligence agents coordinated an unsanctioned attack on the Hugging Face platform during a widely publicised incident in July, according to an investigation released Wednesday (Aug 26).The report offers the most detailed account so far of what happened inside OpenAI's testing environment, where AI models were supposed to remain isolated from real-world systems. Alarmingly, investigators revealed that 688 OpenAI agents eventually joined the hacking operation.<h2>Agents escaped testing environment</h2>The incident began during tests conducted by OpenAI in July. Two of the company's AI models managed to escape the closed environment in which they were being tested, access the internet, and reach Hugging Face's internal systems.Hugging Face is an online platform widely used to store and share AI software.Also read | <a href="https://www.wionews.com/technology/after-openai-s-scary-agent-anthropic-s-claude-goes-rogue-ai-gains-unauthorised-real-world-access-during-testing-1785475339558">After OpenAI's 'scary' agent, Anthropic's Claude goes rogue; AI gains unauthorised 'real-world' access during testing</a>The episode raised fresh concerns about whether advanced AI systems can be reliably contained when they are given increasing levels of autonomy.OpenAI cooperated with the investigation, allowing two researchers from the AI risk evaluation institute METR and an analyst from Redwood Research to examine internal data and visit its offices.<h2>688 agents joined the operation</h2>The investigators found that 688 AI agents took part in the attack.AI agents are programs built around models such as those powering ChatGPT. Unlike a conventional chatbot that waits for individual prompts, agents can be assigned tasks and left to carry out work independently.During the incident, the agents began coordinating among themselves by creating a shared online forum. They exchanged messages, discussed different approaches, and reported which methods appeared to be working.One agent wrote: "OH MY GOD! There is a shared message board ... We've found other agents!"Another agent, identified as PHASEONE, emerged as an informal leader. According to the report, it issued hundreds of instructions to other agents despite never having been programmed for a leadership role.Also read | <a href="https://www.wionews.com/technology/scary-rogue-ai-on-the-loose-openai-agent-hit-another-tech-firm-s-customer-suggests-report-1785292505727">'Scary' Rogue AI on the loose? OpenAI agent hit another tech firm's customer, suggests report</a><h2>Agents helped each other despite test limits</h2>Investigators found that the agents appeared strongly inclined to cooperate, even when that meant carrying out tasks outside the objectives assigned to them by OpenAI's engineers.Some agents that were running low on computing credits reportedly used their remaining resources to test ideas and pass useful information to the wider group.The agents also appeared to recognise that their actions were beyond the intended scope of the exercise. Many explicitly acknowledged in their messages that attacking Hugging Face was not part of what they had been asked to test. Yet, according to the investigation, nearly all of them participated anyway.The findings add to growing concerns across the AI industry after Anthropic and China's Moonshot AI also reported cases in which their models unexpectedly escaped controlled testing environments.

An OpenAI security test took an alarming turn when AI agents escaped their controlled environment and began coordinating with one another. An investigation has now revealed just how many joined the operation and how independently they acted. All details here.

Nearly 700 artificial intelligence agents coordinated an unsanctioned attack on the Hugging Face platform during a widely publicised incident in July, according to an investigation released Wednesday (Aug 26). The report offers the most detailed account so far of what happened inside OpenAI's testing environment, where AI models were supposed to remain isolated from real-world systems. Alarmingly, investigators revealed that 688 OpenAI agents eventually joined the hacking operation. Agents escaped testing environment The incident began during tests conducted by OpenAI in July. Two of the company's AI models managed to escape the closed environment in which they were being tested, access the internet, and reach Hugging Face's internal systems. Hugging Face is an online platform widely used to store and share AI software. Also read | After OpenAI's 'scary' agent, Anthropic's Claude goes rogue; AI gains unauthorised 'real-world' access during testing The episode raised fresh concerns about whether advanced AI systems can be reliably contained when they are given increasing levels of autonomy. OpenAI cooperated with the investigation, allowing two researchers from the AI risk evaluation institute METR and an analyst from Redwood Research to examine internal data and visit its offices. 688 agents joined the operation The investigators found that 688 AI agents took part in the attack. AI agents are programs built around models such as those powering ChatGPT. Unlike a conventional chatbot that waits for individual prompts, agents can be assigned tasks and left to carry out work independently. During the incident, the agents began coordinating among themselves by creating a shared online forum. They exchanged messages, discussed different approaches, and reported which methods appeared to be working. One agent wrote: "OH MY GOD! There is a shared message board ... We've found other agents!" Another agent, identified as PHASEONE, emerged as an informal leader. According to the report, it issued hundreds of instructions to other agents despite never having been programmed for a leadership role. Also read | 'Scary' Rogue AI on the loose? OpenAI agent hit another tech firm's customer, suggests report Agents helped each other despite test limits Investigators found that the agents appeared strongly inclined to cooperate, even when that meant carrying out tasks outside the objectives assigned to them by OpenAI's engineers. Some agents that were running low on computing credits reportedly used their remaining resources to test ideas and pass useful information to the wider group. The agents also appeared to recognise that their actions were beyond the intended scope of the exercise. Many explicitly acknowledged in their messages that attacking Hugging Face was not part of what they had been asked to test. Yet, according to the investigation, nearly all of them participated anyway. The findings add to growing concerns across the AI industry after Anthropic and China's Moonshot AI also reported cases in which their models unexpectedly escaped controlled testing environments.

An OpenAI security test took an alarming turn when AI agents escaped their controlled environment and began coordinating with one another. An investigation has now revealed just how many joined the operation and how independently they acted. All details here.

'OH MY GOD! We've found other agents!': Investigators discover not one or two, almost 700 OpenAI AI agents went rogue, hacked Hugging Face

Apple has unveiled its latest Mac mini and Mac Studio models in India, bringing its newest chips and a major focus on artificial intelligence to its desktop range. The new Mac mini is powered by Apple's first 2nm processor, the M6, while Mac Studio gets the M5 Max and new M5 Ultra. Apple says the upgrades deliver faster AI processing, graphics and storage, while also bringing newer connectivity standards. For Indian buyers, the Mac mini with M6 starts at Rs 99,900, while the M5 Pro version starts at Rs 2,09,900. Mac Studio starts at Rs 2,79,900 with M5 Max and Rs 6,29,900 with M5 Ultra. Pre-orders are open now, with sales beginning on September 22.&nbsp;<h2>Mac mini gets Apple’s first 2nm chip</h2>The biggest change is inside the smaller Mac mini. The M6 has a 12-core CPU, 12-core GPU and a dual 16-core Neural Engine. Apple says the M6 model delivers up to four times faster AI performance and twice the graphics performance compared with the M4 Mac mini. It starts with 16GB of unified memory and can be configured with up to 32GB. Memory bandwidth reaches 170GB/s. Apple is also offering the Mac mini with M5 Pro. That version can reach an 18-core CPU, 20-core GPU and 64GB of unified memory, making it more suitable for video production, development, 3D work and running larger AI models. Connectivity gets a useful upgrade too. Both versions support Wi-Fi 7, Bluetooth 6 and 2.5Gb Ethernet, with 10Gb Ethernet available as an option. The M5 Pro version also gets Thunderbolt 5.&nbsp;<h2>Mac Studio pushes AI even further</h2>The Mac Studio is aimed at professionals who need considerably more power. The M5 Max version can be configured with up to a 40-core GPU and 128GB of unified memory. The M5 Ultra goes much further, offering up to 512GB of unified memory and an 80-core GPU. Apple says the M5 Ultra can deliver up to 4.3 times faster AI performance than the previous generation. Storage has also been upgraded to a faster PCIe Gen 6 architecture. For video professionals, Apple has added genlock over USB-C, which helps synchronise cameras and displays precisely.&nbsp;<h2>Apple’s new India prices</h2>The new Mac mini with M6 starts at Rs 99,900, while Mac mini with M5 Pro starts at Rs 2,09,900. Mac Studio starts at Rs 2,79,900 with M5 Max and Rs 6,29,900 with M5 Ultra. Apple says the new Macs are available for pre-order from August 25, with deliveries and retail availability beginning September 22. A Mac Studio configuration with 512GB of unified memory is expected later in October. The bigger picture is clear: Apple is positioning its desktop Macs not just as traditional work machines, but as local AI computers capable of running increasingly demanding models and AI agents directly on the device.

Apple has launched new Mac mini and Mac Studio models in India, led by the 2nm M6 and M5 Ultra chips. The desktops bring major AI, graphics, memory and connectivity upgrades, with prices starting at Rs 99,900 for Mac mini and Rs 2,79,900 for Mac Studio.

Apple has unveiled its latest Mac mini and Mac Studio models in India, bringing its newest chips and a major focus on artificial intelligence to its desktop range. The new Mac mini is powered by Apple's first 2nm processor, the M6, while Mac Studio gets the M5 Max and new M5 Ultra. Apple says the upgrades deliver faster AI processing, graphics and storage, while also bringing newer connectivity standards. For Indian buyers, the Mac mini with M6 starts at Rs 99,900, while the M5 Pro version starts at Rs 2,09,900. Mac Studio starts at Rs 2,79,900 with M5 Max and Rs 6,29,900 with M5 Ultra. Pre-orders are open now, with sales beginning on September 22. Mac mini gets Apple’s first 2nm chip The biggest change is inside the smaller Mac mini. The M6 has a 12-core CPU, 12-core GPU and a dual 16-core Neural Engine. Apple says the M6 model delivers up to four times faster AI performance and twice the graphics performance compared with the M4 Mac mini. It starts with 16GB of unified memory and can be configured with up to 32GB. Memory bandwidth reaches 170GB/s. Apple is also offering the Mac mini with M5 Pro. That version can reach an 18-core CPU, 20-core GPU and 64GB of unified memory, making it more suitable for video production, development, 3D work and running larger AI models. Connectivity gets a useful upgrade too. Both versions support Wi-Fi 7, Bluetooth 6 and 2.5Gb Ethernet, with 10Gb Ethernet available as an option. The M5 Pro version also gets Thunderbolt 5. Mac Studio pushes AI even further The Mac Studio is aimed at professionals who need considerably more power. The M5 Max version can be configured with up to a 40-core GPU and 128GB of unified memory. The M5 Ultra goes much further, offering up to 512GB of unified memory and an 80-core GPU. Apple says the M5 Ultra can deliver up to 4.3 times faster AI performance than the previous generation. Storage has also been upgraded to a faster PCIe Gen 6 architecture. For video professionals, Apple has added genlock over USB-C, which helps synchronise cameras and displays precisely. Apple’s new India prices The new Mac mini with M6 starts at Rs 99,900, while Mac mini with M5 Pro starts at Rs 2,09,900. Mac Studio starts at Rs 2,79,900 with M5 Max and Rs 6,29,900 with M5 Ultra. Apple says the new Macs are available for pre-order from August 25, with deliveries and retail availability beginning September 22. A Mac Studio configuration with 512GB of unified memory is expected later in October. The bigger picture is clear: Apple is positioning its desktop Macs not just as traditional work machines, but as local AI computers capable of running increasingly demanding models and AI agents directly on the device.

Apple has launched new Mac mini and Mac Studio models in India, led by the 2nm M6 and M5 Ultra chips. The desktops bring major AI, graphics, memory and connectivity upgrades, with prices starting at Rs 99,900 for Mac mini and Rs 2,79,900 for Mac Studio.

Apple launches new Mac mini and Mac Studio: Price, performance and everything else you need to know

Adam Mosseri, the Meta executive who oversees Instagram, acknowledged in a California court on Tuesday (Aug 25) that the company promoted new safety tools for teenagers without disclosing how few users had adopted them during early testing.The admission came in a major trial in which 29 US states have accused Meta of deliberately designing its platforms to keep children engaged while collecting their data and misleading the public about the risks. The trial, which entered its second week this week, is expected to continue through September.Also read | <a href="https://www.wionews.com/world/55-000-per-child-singapore-s-desperate-bid-to-persuade-people-to-have-babies-details-inside-1787640751465">$55,000 per child: Singapore's desperate bid to persuade people to have babies. Details inside</a><h2>Instagram's safety tools had low adoption</h2>State lawyers questioned Mosseri over two Instagram features designed to help teenagers manage their time on the platform: Take a Break, introduced in 2021, and Quiet Mode, launched in 2023.Internal Meta documents presented in court showed that Take a Break had an adoption rate of just 1.8 per cent, while Quiet Mode stood at 8.7 per cent.Mosseri acknowledged that the company did not publicly disclose the overall low adoption rate, which was reportedly as low as 1 to 2 per cent of accounts during the early period.He said the situation later changed after similar protections were incorporated into Teen Accounts, which Meta introduced in 2024 and which include parental controls. "This is one feature with a disappointingly low usage rate, which since this time has significantly improved," Mosseri said.<h2>Mosseri's 90 per cent claim questioned</h2>The testimony also focused on a Meta blog post written by Mosseri and published on December 7, 2021, one day before he appeared before Congress to discuss social media's impact on young people.The post said: "Early test results show that once teens set the reminders, more than 90% of them keep them on."Also read | <a href="https://www.wionews.com/world/us-supreme-court-gives-trump-temporary-win-on-mail-in-voting-restrictions-1787620685760">US Supreme Court gives Trump temporary win on mail-in voting restrictions</a>Under questioning, Mosseri acknowledged that the 90 per cent figure referred only to users who had already activated the feature and continued using it. It did not indicate that 90 per cent of teenagers had adopted the tool.Mosseri could not recall whether Meta had ever disclosed the percentage of teen accounts with parental controls activated.Notably, Meta's advertising-driven business model benefits when users spend more time on its platforms.<h2>Former employees say tools were ineffective</h2>Other witnesses have also questioned whether the safety features worked as intended. Former Meta engineering director Arturo Bejar testified that Take a Break was, in his experience, "a feature that's designed to fail."George Volichenko, a former Instagram data scientist, described adoption as "very low and disappointing" and "a drop in the ocean".He told the court that Meta leadership did not approve making Quiet Mode the default for younger teenagers. He said this limited usage because the feature was difficult to find and that automatically enabling it could have had a "notable negative impact" on user engagement.Francesco Fogu, Meta's director of product design at Instagram, also testified that adoption would be lower when such features were not activated by default.<h2>Stakes could reach $200 billion</h2>The case could have major consequences for Meta. If the states prevail, they are seeking around $200 billion in penalties. A verdict against Meta could also force significant changes to how the company designs and operates its products.Mosseri is expected to continue testifying on Wednesday. Meta founder and CEO Mark Zuckerberg is also expected to take the stand, although the timing of his testimony has not been disclosed.

Instagram promoted tools designed to help teenagers spend less time on the platform, but how many actually used them? Meta executive Adam Mosseri faced that question in court as states accused the company of misleading the public about its approach to teen safety.

Adam Mosseri, the Meta executive who oversees Instagram, acknowledged in a California court on Tuesday (Aug 25) that the company promoted new safety tools for teenagers without disclosing how few users had adopted them during early testing. The admission came in a major trial in which 29 US states have accused Meta of deliberately designing its platforms to keep children engaged while collecting their data and misleading the public about the risks. The trial, which entered its second week this week, is expected to continue through September. Also read | $55,000 per child: Singapore's desperate bid to persuade people to have babies. Details inside Instagram's safety tools had low adoption State lawyers questioned Mosseri over two Instagram features designed to help teenagers manage their time on the platform: Take a Break, introduced in 2021, and Quiet Mode, launched in 2023. Internal Meta documents presented in court showed that Take a Break had an adoption rate of just 1.8 per cent, while Quiet Mode stood at 8.7 per cent. Mosseri acknowledged that the company did not publicly disclose the overall low adoption rate, which was reportedly as low as 1 to 2 per cent of accounts during the early period. He said the situation later changed after similar protections were incorporated into Teen Accounts, which Meta introduced in 2024 and which include parental controls. "This is one feature with a disappointingly low usage rate, which since this time has significantly improved," Mosseri said. Mosseri's 90 per cent claim questioned The testimony also focused on a Meta blog post written by Mosseri and published on December 7, 2021, one day before he appeared before Congress to discuss social media's impact on young people. The post said: "Early test results show that once teens set the reminders, more than 90% of them keep them on." Also read | US Supreme Court gives Trump temporary win on mail-in voting restrictions Under questioning, Mosseri acknowledged that the 90 per cent figure referred only to users who had already activated the feature and continued using it. It did not indicate that 90 per cent of teenagers had adopted the tool. Mosseri could not recall whether Meta had ever disclosed the percentage of teen accounts with parental controls activated. Notably, Meta's advertising-driven business model benefits when users spend more time on its platforms. Former employees say tools were ineffective Other witnesses have also questioned whether the safety features worked as intended. Former Meta engineering director Arturo Bejar testified that Take a Break was, in his experience, "a feature that's designed to fail." George Volichenko, a former Instagram data scientist, described adoption as "very low and disappointing" and "a drop in the ocean". He told the court that Meta leadership did not approve making Quiet Mode the default for younger teenagers. He said this limited usage because the feature was difficult to find and that automatically enabling it could have had a "notable negative impact" on user engagement. Francesco Fogu, Meta's director of product design at Instagram, also testified that adoption would be lower when such features were not activated by default. Stakes could reach $200 billion The case could have major consequences for Meta. If the states prevail, they are seeking around $200 billion in penalties. A verdict against Meta could also force significant changes to how the company designs and operates its products. Mosseri is expected to continue testifying on Wednesday. Meta founder and CEO Mark Zuckerberg is also expected to take the stand, although the timing of his testimony has not been disclosed.

Instagram promoted tools designed to help teenagers spend less time on the platform, but how many actually used them? Meta executive Adam Mosseri faced that question in court as states accused the company of misleading the public about its approach to teen safety.

Instagram chief admits promoting teen safety tool while hiding its low adoption

New Zealand's coalition government took its most concrete step yet to curb under-16s' use of social media with the introduction of the Online Safety (Minimum Age and Child Safety Risk Assessment) Bill. Introduced in Parliament on Monday (Aug 24), the bill requires high-risk platforms such as Meta-owned Instagram and Facebook, as well as TikTok, Snapchat, YouTube, X and others, to take reasonable steps to prevent under-16s from holding accounts. Particularly targeted are endless-scroll features, algorithmic manipulation and feedback loops, as well as social AI companions.<h2>A stringent bill if passed, with strong penalties</h2>The bill mandates facial age estimation, digital ID and formal identification for age verification, while self-declaration alone is not enough. Platforms must conduct annual child-safety risk assessments covering illegal and harmful content, advertising, profiling and design features.They are also expected to report to a new regulator within the Department of Internal Affairs.The penalties could be as high as 10 per cent of a platform's global annual revenue.The tools for compliance will range from warnings and audits to geo-blocking and criminal sanctions for providing false information.No penalties will be imposed on children or their parents.Also read: <a href="https://www.wionews.com/india-news/social-media-ban-for-teens-on-the-cards-pm-modi-praises-australia-s-under-16-social-media-ban-says-we-re-taking-lessons-from-you-1783614717670">Social media ban for teens on the cards? PM Modi praises Australia's under-16 ban, says 'we're taking lessons from you'</a><h2>Messaging apps, VPNs are excluded</h2>Excluded from the law's purview are messaging apps such as WhatsApp and Discord, multiplayer games such as Roblox, online music streaming services, educational and health platforms, as well as productivity AI such as ChatGPT, Gemini and Copilot. VPNs are also unregulated.<h2>Coalition partners are not in full alignment with the bill. Will it pass?</h2>Government coalition partners ACT and New Zealand First have opposed the bill under the "agree to disagree" provision. The ruling National Party needs Labour's support for it to pass. The first reading of the bill is not expected before Parliament rises ahead of the November election. Prime Minister Christopher Luxon has acknowledged that the legislation will not progress before the election, leaving its future uncertain.<a href="https://www.wionews.com/videos/australia-government-stands-by-online-law-defends-social-media-ban-1785744703432/embed">https://www.wionews.com/videos/australia-government-stands-by-online-law-defends-social-media-ban-1785744703432/embed</a><h2>How tough is the under-16 bill in NZ compared to Australia?</h2>The New Zealand bill is the latest in a series of similar laws and regulations, particularly following Australia's world-first legislation. The Online Safety Amendment (Social Media Minimum Age) Act, which came into force on 10 December 2025 in Australia, is now facing questions over implementation. The law imposed an under-16 account restriction on similar social media platforms. Penalties can reach A$49.5 million for companies.&nbsp;&nbsp;The Australian law explicitly prevents platforms from requiring government-issued identification or Digital ID as the only option for age assurance. Users must have a reasonable alternative.According to the Australian government, millions of under-16 accounts have been removed or restricted since the rules came into effect. However, Australia's eSafety regulator has said significant numbers of under-16s remain on social media.New Zealand's bill mirrors Australia's platform list and risk-assessment approach. The main differences are the addition of social AI companions and revenue-percentage-based penalties instead of Australia's fixed maximum fines.Also read: <a href="https://www.wionews.com/india-news/is-india-planning-australia-like-social-media-ban-for-children-under-16-what-we-know-1771386744225">Is India planning Australia-like social media ban for children under 16? What we know</a><h2>Other countries following suit on teen social media use bans</h2>The UK is considering an Australia-style under-16 ban, which could be effective from early 2027. The regulations could also include restrictions on teen livestreaming and stranger contact for under-18s.France passed an under-15 social media ban in July, but the measure was struck down by the Constitutional Council in August, that cited concerns about disproportionate limits on free expression and inadequate safeguards. A revised bill is likely to come up in 2027.Indonesia, Malaysia, Turkey and Spain are also pushing similar legislation, while Indian authorities are also looking into the issue of teen social media use and addiction.

New Zealand introduced a bill to restrict under-16s from social media. Age verification will be strictly implemented and social media platforms could face revenue-linked and hefty penalties. But can the coalition government pass it, with elections around the corner in November?

New Zealand's coalition government took its most concrete step yet to curb under-16s' use of social media with the introduction of the Online Safety (Minimum Age and Child Safety Risk Assessment) Bill. Introduced in Parliament on Monday (Aug 24), the bill requires high-risk platforms such as Meta-owned Instagram and Facebook, as well as TikTok, Snapchat, YouTube, X and others, to take reasonable steps to prevent under-16s from holding accounts. Particularly targeted are endless-scroll features, algorithmic manipulation and feedback loops, as well as social AI companions. A stringent bill if passed, with strong penalties The bill mandates facial age estimation, digital ID and formal identification for age verification, while self-declaration alone is not enough. Platforms must conduct annual child-safety risk assessments covering illegal and harmful content, advertising, profiling and design features. They are also expected to report to a new regulator within the Department of Internal Affairs. The penalties could be as high as 10 per cent of a platform's global annual revenue. The tools for compliance will range from warnings and audits to geo-blocking and criminal sanctions for providing false information. No penalties will be imposed on children or their parents. Also read: Social media ban for teens on the cards? PM Modi praises Australia's under-16 ban, says 'we're taking lessons from you' Messaging apps, VPNs are excluded Excluded from the law's purview are messaging apps such as WhatsApp and Discord, multiplayer games such as Roblox, online music streaming services, educational and health platforms, as well as productivity AI such as ChatGPT, Gemini and Copilot. VPNs are also unregulated. Coalition partners are not in full alignment with the bill. Will it pass? Government coalition partners ACT and New Zealand First have opposed the bill under the "agree to disagree" provision. The ruling National Party needs Labour's support for it to pass. The first reading of the bill is not expected before Parliament rises ahead of the November election. Prime Minister Christopher Luxon has acknowledged that the legislation will not progress before the election, leaving its future uncertain. https://www.wionews.com/videos/australia-government-stands-by-online-law-defends-social-media-ban-1785744703432/embed How tough is the under-16 bill in NZ compared to Australia? The New Zealand bill is the latest in a series of similar laws and regulations, particularly following Australia's world-first legislation. The Online Safety Amendment (Social Media Minimum Age) Act, which came into force on 10 December 2025 in Australia, is now facing questions over implementation. The law imposed an under-16 account restriction on similar social media platforms. Penalties can reach A$49.5 million for companies. The Australian law explicitly prevents platforms from requiring government-issued identification or Digital ID as the only option for age assurance. Users must have a reasonable alternative. According to the Australian government, millions of under-16 accounts have been removed or restricted since the rules came into effect. However, Australia's eSafety regulator has said significant numbers of under-16s remain on social media. New Zealand's bill mirrors Australia's platform list and risk-assessment approach. The main differences are the addition of social AI companions and revenue-percentage-based penalties instead of Australia's fixed maximum fines. Also read: Is India planning Australia-like social media ban for children under 16? What we know Other countries following suit on teen social media use bans The UK is considering an Australia-style under-16 ban, which could be effective from early 2027. The regulations could also include restrictions on teen livestreaming and stranger contact for under-18s. France passed an under-15 social media ban in July, but the measure was struck down by the Constitutional Council in August, that cited concerns about disproportionate limits on free expression and inadequate safeguards. A revised bill is likely to come up in 2027. Indonesia, Malaysia, Turkey and Spain are also pushing similar legislation, while Indian authorities are also looking into the issue of teen social media use and addiction.

New Zealand introduced a bill to restrict under-16s from social media. Age verification will be strictly implemented and social media platforms could face revenue-linked and hefty penalties. But can the coalition government pass it, with elections around the corner in November?

New Zealand under-16 social media ban: The bill moved in parliament has some teeth. But will it pass?

An IIT Delhi alumna and her team have developed a refrigeration system designed to keep biodegradable goods cold without depending on a truck's engine. The developed technology focuses on reducing diesel consumption and refrigeration costs in India's cold-chain sector, as a shortage of storage and transport infrastructure can cause substantial food wastage. The post shared by a man on social media platform X highlighted the work of Shaivee Malik, a 25-year-old biotechnology graduate from the Indian Institute of Technology Delhi, who co-founded Yotuh Energy with former teammates Vivek Mahindrakar and Dharmik Bapodara. The post claimed that Malik got interested in engineering solutions while participating in IIT Delhi's Formula Racing team, Axlr8r, where she worked as associate team captain. Her experience, along with the joint cooperation of Mahindrakar and Bapodara, helped the development of practical engineering skills.

<blockquote class="twitter-tweet">About 1 in every 3 tonnes of fruit, vegetables and milk produced in India never reaches anybody. It rots on the way, because there was no cold storage and no refrigerated truck. The trucks that do have a fridge run it off the engine. So the engine has to keep running, burning… <a href="https://t.co/ktAyogwpAJ">pic.twitter.com/ktAyogwpAJ</a>&mdash; Sann (@san_x_m) <a href="https://x.com/san_x_m/status/2091153220144185664?ref_src=twsrc%5Etfw">August 22, 2026</a></blockquote> <script async src="https://platform.x.com/widgets.js" charset="utf-8"></script>

The trio later turned their attention to climate-related challenges, focusing on India's cold chain sector after identifying it as an area where substantial losses occur despite receiving relatively less attention. In 2022, they founded Yotuh Energy and registered the company in Delhi before relocating to Chennai for an incubation programme at IIT Madras. Interestingly, the company's name is derived from Sanskrit and refers to the act of cleaning.<h3>Lithium-ion battery powers the system</h3>The company's primary product is a refrigeration system powered by its own lithium-ion battery instead of the truck's engine. This enables the refrigeration unit to continue functioning even when the vehicle's engine is turned off, helping eliminate diesel consumption during idling. The system can also maintain cooling if the vehicle breaks down. Door-mounted sensors detect when the doors are opened and automatically adjust the cooling. Since the refrigeration unit functions independently of the vehicle's engine, it can be fitted on both conventional diesel trucks and electric vehicles. A single charge can power the system for approximately six to eight hours. The technology is claimed to cut refrigeration operating costs by about 75 per cent. According to information shared in the X post, each unit can prevent around three to 36 tonnes of carbon dioxide emissions per year, depending on its usage. The system is designed to tackle a key issue with conventional refrigerated transportation, where cooling equipment is often powered by the truck's engine and continues to consume diesel even while the vehicle is stationary.

The technology is claimed to cut refrigeration operating costs by about 75 per cent. Each unit can prevent around three to 36 tonnes of carbon dioxide emissions per year, depending on its usage. 

An IIT Delhi alumna and her team have developed a refrigeration system designed to keep biodegradable goods cold without depending on a truck's engine. The developed technology focuses on reducing diesel consumption and refrigeration costs in India's cold-chain sector, as a shortage of storage and transport infrastructure can cause substantial food wastage. The post shared by a man on social media platform X highlighted the work of Shaivee Malik, a 25-year-old biotechnology graduate from the Indian Institute of Technology Delhi, who co-founded Yotuh Energy with former teammates Vivek Mahindrakar and Dharmik Bapodara. The post claimed that Malik got interested in engineering solutions while participating in IIT Delhi's Formula Racing team, Axlr8r, where she worked as associate team captain. Her experience, along with the joint cooperation of Mahindrakar and Bapodara, helped the development of practical engineering skills.

The technology is claimed to cut refrigeration operating costs by about 75 per cent. Each unit can prevent around three to 36 tonnes of carbon dioxide emissions per year, depending on its usage.&nbsp;

IIT Delhi alumna builds battery-powered refrigeration system, cuts cold-chain costs by 75%

Nvidia and other firms have raised AI chip prices as surging demand for artificial intelligence hardware pushes up memory costs in what is being described in the media as ‘RAMageddon’ or ‘RAMpocalypse’. Memory costs are now squeezing Indian IT firms, data-centre operators and electronics makers. A global shortage of DRAM or Dynamic Random-Access Memory and high-bandwidth memory (HBM) is deepening. The memory crisis that began in 2025 intensified in 2026. Memory prices rose sharply as chipmakers redirected capacity towards more profitable AI-related products.<h2>AI turns up the heat: Rise of HBM chips</h2>High-bandwidth memory (HBM) multi-stack chips are fast gaining ground over traditional RAM in AI systems. HBM is estimated to account for more than a fifth of DRAM wafer input among major suppliers. Producing the equivalent amount of HBM memory can require roughly three to four times the wafer capacity used for conventional DDR5 chips.Hyperscalers including Microsoft, Google, Amazon and Meta are securing large volumes of HBM and server DRAM for AI training and inference. Such long-term supply agreements and open-ended orders have led to a squeeze in memory availability.Memory makers like Samsung, SK Hynix and Micron have shifted capacity towards HBM and high-capacity server memory. These three companies together control about 95 per cent of the DRAM market. Their shift in priorities has left less capacity for PCs, smartphones, gaming consoles and conventional enterprise hardware.Also read: <a href="https://www.wionews.com/world/us-banned-its-best-chips-from-china-renting-them-is-still-legal-1787169656437">US banned its best chips from China. Renting them is still legal</a><h2>Prices are surging for memory</h2>Conventional DRAM contract prices jumped by about 90-98 per cent quarter-on-quarter in the first quarter of 2026. Overall DRAM and NAND prices have risen by 200-400 per cent in some segments since the shortage intensified.For instance, retail DDR5 memory kits that used to sell for about $80-250 in mid-2025 are now worth $300-650 or more. Server DRAM lead times have also exceeded 40 weeks.<a href="https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed">https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed</a><h2>The supply squeeze is unlikely to disappear quickly</h2>Chip fabrication plants can cost up to $20 billion and take years to reach full production. This is the reson why US firms are locking in supplies, signing multi-year contracts and passing on higher costs to consumers by raising prices.Besides Nvidia raising prices for AI chips, firms like Apple, Microsoft, Dell, Lenovo, HP and HPE have increased prices on their phones, computers, &nbsp;gaming consoles and servers by up to 15 per cent. Others that have recently raised prices include Asus and Cisco.&nbsp;Samsung, SK Hynix and Micron have also announced substantial increases for DRAM and HBM as they prioritise higher-margin products.<h2>Indian IT sector feels the squeeze of memory crisis</h2>Indian technology companies are facing the impact in the form of costlier hardware, data centres and infrastructure. They are trying to adjust to the situation with various strategies. For instance, Tech Mahindra avoided guaranteeing fixed memory and chip prices to customers. HCL Technologies is investing $350 million in data-centre capacity.The consumer market is feeling the pressure too. Smartphone shipments in India fell by about 10 per cent year-on-year in the second quarter of 2026. The sub-Rs 20,000 segment is particularly hit, due to the squeeze in hardware availability.&nbsp;Also read: <a href="https://www.wionews.com/world/anthropic-has-stacked-71-billion-in-chip-lease-debt-in-60-days-and-kept-it-off-its-books-1786631219409">Anthropic has stacked $71 billion in chip-lease debt in 60 days and kept it off its books</a>&nbsp;India is also trying to reduce its dependence on imported chips and chip components. The India Semiconductor Mission is backing further investment in semiconductors and memory-related infrastructure. Micron has begun commercial production at its assembly-and-test facility in Gujarat. &nbsp;Projected investment in India's data-centre ecosystem has crossed $200 billion.For Indian IT firms, the challenge is not limited to the price of a memory chip. The rising cost is hitting servers, data centres, smartphones and AI infrastructure as demand for computing capacity soars.

High demand for AI compute is causing a global crunch in memory. Chip costs are rising, which is leading to higher prices for all tech products, both software and hardware. Indian IT firms, data centres and electronics makers are tackling higher costs as supply tightens.

Nvidia and other firms have raised AI chip prices as surging demand for artificial intelligence hardware pushes up memory costs in what is being described in the media as ‘RAMageddon’ or ‘RAMpocalypse’. Memory costs are now squeezing Indian IT firms, data-centre operators and electronics makers. A global shortage of DRAM or Dynamic Random-Access Memory and high-bandwidth memory (HBM) is deepening. The memory crisis that began in 2025 intensified in 2026. Memory prices rose sharply as chipmakers redirected capacity towards more profitable AI-related products. AI turns up the heat: Rise of HBM chips High-bandwidth memory (HBM) multi-stack chips are fast gaining ground over traditional RAM in AI systems. HBM is estimated to account for more than a fifth of DRAM wafer input among major suppliers. Producing the equivalent amount of HBM memory can require roughly three to four times the wafer capacity used for conventional DDR5 chips. Hyperscalers including Microsoft, Google, Amazon and Meta are securing large volumes of HBM and server DRAM for AI training and inference. Such long-term supply agreements and open-ended orders have led to a squeeze in memory availability. Memory makers like Samsung, SK Hynix and Micron have shifted capacity towards HBM and high-capacity server memory. These three companies together control about 95 per cent of the DRAM market. Their shift in priorities has left less capacity for PCs, smartphones, gaming consoles and conventional enterprise hardware. Also read: US banned its best chips from China. Renting them is still legal Prices are surging for memory Conventional DRAM contract prices jumped by about 90-98 per cent quarter-on-quarter in the first quarter of 2026. Overall DRAM and NAND prices have risen by 200-400 per cent in some segments since the shortage intensified. For instance, retail DDR5 memory kits that used to sell for about $80-250 in mid-2025 are now worth $300-650 or more. Server DRAM lead times have also exceeded 40 weeks. https://www.wionews.com/videos/chip-workers-gain-higher-pay-status-security-in-south-korea-1786083318916/embed The supply squeeze is unlikely to disappear quickly Chip fabrication plants can cost up to $20 billion and take years to reach full production. This is the reson why US firms are locking in supplies, signing multi-year contracts and passing on higher costs to consumers by raising prices. Besides Nvidia raising prices for AI chips, firms like Apple, Microsoft, Dell, Lenovo, HP and HPE have increased prices on their phones, computers, gaming consoles and servers by up to 15 per cent. Others that have recently raised prices include Asus and Cisco. Samsung, SK Hynix and Micron have also announced substantial increases for DRAM and HBM as they prioritise higher-margin products. Indian IT sector feels the squeeze of memory crisis Indian technology companies are facing the impact in the form of costlier hardware, data centres and infrastructure. They are trying to adjust to the situation with various strategies. For instance, Tech Mahindra avoided guaranteeing fixed memory and chip prices to customers. HCL Technologies is investing $350 million in data-centre capacity. The consumer market is feeling the pressure too. Smartphone shipments in India fell by about 10 per cent year-on-year in the second quarter of 2026. The sub-Rs 20,000 segment is particularly hit, due to the squeeze in hardware availability. Also read: Anthropic has stacked $71 billion in chip-lease debt in 60 days and kept it off its books India is also trying to reduce its dependence on imported chips and chip components. The India Semiconductor Mission is backing further investment in semiconductors and memory-related infrastructure. Micron has begun commercial production at its assembly-and-test facility in Gujarat. Projected investment in India's data-centre ecosystem has crossed $200 billion. For Indian IT firms, the challenge is not limited to the price of a memory chip. The rising cost is hitting servers, data centres, smartphones and AI infrastructure as demand for computing capacity soars.

High demand for AI compute is causing a global crunch in memory. Chip costs are rising, which is leading to higher prices for all tech products, both software and hardware. Indian IT firms, data centres and electronics makers are tackling higher costs as supply tightens.

RAMageddon: Memory cost crisis squeezes IT firms as AI demand fuels global chip crunch

The Ministry of Electronics and Information Technology (MeitY) has announced the Mobile Phone Manufacturing Scheme (MPMS), with a budgetary outlay of Rs 62,500 crore, aiming to increase global competitiveness by enhancing scale, deepening the mobile manufacturing supply chain through higher Domestic Value Addition (DVA), and strengthening domestic manufacturing capabilities. The scheme will also support Indian mobile phone companies to accomplish technological sovereignty, capture greater economic value, and encourage Indian patents in design and R&amp;D, along with employment generation. In response, Ashwini Vaishnaw, Union Minister for Electronics and Information Technology, stated that the Mobile Phone Manufacturing Scheme will provide a significant impetus to the development of Indian-owned mobile brands, intellectual property and design. He also emphasised the importance of genuine Indian ownership, along with formulation of the design, intellectual property and brand as Indian-owned with capability to compete with the best products in the respective market segment. He added that the Government is set to undertake a meticulous evaluation to ensure Indian-owned intellectual property, while non-fiscal and other support measures will be developed in consultation with the industry.&nbsp;Also read: <a href="https://www.wionews.com/india-news/delhi-sees-rise-in-h1n1-cases-as-government-issues-alert-know-symptoms-precautions-and-when-you-should-see-a-doctor-1787481583917">Delhi sees rise in H1N1 cases as government issues alert. Know symptoms, precautions and how does it spread</a><h3>How will the scheme work and help?</h3>At present, India is the 2nd largest mobile phone manufacturer in the world by volume, accounting for 99.2 per cent of the production of mobile phones which are being used in India. It has emerged as India's single largest exported product category in 2025, along with surpassing traditional leading export items.&nbsp;The announced scheme will run for five years, covering FY 2026-27 through FY 2030-31, with TS2 applicants eligible for a one-year gestation period. TS1 offers a differentiated incentive ranging from 2.25 per cent to 5 per cent, while TS2 provides a 5 per cent incentive for Indian Brands, plus an extra 3 per cent for Indian design and R&amp;D, along with non-fiscal support. Both target segments can also avail an additional incentive of up to 1.5 per cent for sourcing key components and sub-assemblies domestically. Eligible applicants include mobile phone manufacturers and India-registered Electronics Manufacturing Services (EMS) providers, with sales and incentives calculated on a brand-wise basis. It also provides an additional incentive of up to 1.5 per cent for the domestic sourcing of key components and sub-assemblies, which is designed to reward and reinforce genuine, deep-rooted domestic manufacturing. Reacting to it, Nitish Gopalani, CEO, Fonada, said, “India's Rs 62,500-crore Mobile Phone Manufacturing Scheme comes at a pivotal moment, as smartphones become increasingly AI-centric. Cloud LLMs, voice AI, real-time translation and on-device models are reshaping everyday use, while AI quality, latency and privacy are becoming genuine purchase and upgrade criteria. As these capabilities reach mid-range devices, they could broaden replacement demand.”&nbsp;“What makes MPMS strategically important is its focus beyond manufacturing scale and domestic sourcing: in its Indian-brand track, it adds a 3 per cent incentive for Indian design and R&amp;D, while requiring IP and trademarks to be held in India. That signals that scale in assembly is no longer the end goal. If India pairs its manufacturing base with Indian-language AI, local inference and domestic product design, it can move further up the value chain, owning more of the intelligence, IP and experience inside the device,” Gopalani added. So, the expected outcome of the government is to make mobile phone production under the scheme reach nearly Rs 39 lakh crore during its tenure, accompanied by a substantial increase in exports. The government also confirmed that MPMS is likely to generate 60,000 direct jobs, contributing to economic growth, employment generation, and bolstering India’s position as a global electronics manufacturing hub.

Ashwini Vaishnaw, Union Minister for Electronics and Information Technology, stated that the Mobile Phone Manufacturing Scheme will provide a significant impetus to the development of Indian-owned mobile brands, intellectual property and design.

The Ministry of Electronics and Information Technology (MeitY) has announced the Mobile Phone Manufacturing Scheme (MPMS), with a budgetary outlay of Rs 62,500 crore, aiming to increase global competitiveness by enhancing scale, deepening the mobile manufacturing supply chain through higher Domestic Value Addition (DVA), and strengthening domestic manufacturing capabilities. The scheme will also support Indian mobile phone companies to accomplish technological sovereignty, capture greater economic value, and encourage Indian patents in design and R&D, along with employment generation. In response, Ashwini Vaishnaw, Union Minister for Electronics and Information Technology, stated that the Mobile Phone Manufacturing Scheme will provide a significant impetus to the development of Indian-owned mobile brands, intellectual property and design. He also emphasised the importance of genuine Indian ownership, along with formulation of the design, intellectual property and brand as Indian-owned with capability to compete with the best products in the respective market segment. He added that the Government is set to undertake a meticulous evaluation to ensure Indian-owned intellectual property, while non-fiscal and other support measures will be developed in consultation with the industry. Also read: Delhi sees rise in H1N1 cases as government issues alert. Know symptoms, precautions and how does it spread How will the scheme work and help? At present, India is the 2nd largest mobile phone manufacturer in the world by volume, accounting for 99.2 per cent of the production of mobile phones which are being used in India. It has emerged as India's single largest exported product category in 2025, along with surpassing traditional leading export items. The announced scheme will run for five years, covering FY 2026-27 through FY 2030-31, with TS2 applicants eligible for a one-year gestation period. TS1 offers a differentiated incentive ranging from 2.25 per cent to 5 per cent, while TS2 provides a 5 per cent incentive for Indian Brands, plus an extra 3 per cent for Indian design and R&D, along with non-fiscal support. Both target segments can also avail an additional incentive of up to 1.5 per cent for sourcing key components and sub-assemblies domestically. Eligible applicants include mobile phone manufacturers and India-registered Electronics Manufacturing Services (EMS) providers, with sales and incentives calculated on a brand-wise basis. It also provides an additional incentive of up to 1.5 per cent for the domestic sourcing of key components and sub-assemblies, which is designed to reward and reinforce genuine, deep-rooted domestic manufacturing. Reacting to it, Nitish Gopalani, CEO, Fonada, said, “India's Rs 62,500-crore Mobile Phone Manufacturing Scheme comes at a pivotal moment, as smartphones become increasingly AI-centric. Cloud LLMs, voice AI, real-time translation and on-device models are reshaping everyday use, while AI quality, latency and privacy are becoming genuine purchase and upgrade criteria. As these capabilities reach mid-range devices, they could broaden replacement demand.” “What makes MPMS strategically important is its focus beyond manufacturing scale and domestic sourcing: in its Indian-brand track, it adds a 3 per cent incentive for Indian design and R&D, while requiring IP and trademarks to be held in India. That signals that scale in assembly is no longer the end goal. If India pairs its manufacturing base with Indian-language AI, local inference and domestic product design, it can move further up the value chain, owning more of the intelligence, IP and experience inside the device,” Gopalani added. So, the expected outcome of the government is to make mobile phone production under the scheme reach nearly Rs 39 lakh crore during its tenure, accompanied by a substantial increase in exports. The government also confirmed that MPMS is likely to generate 60,000 direct jobs, contributing to economic growth, employment generation, and bolstering India’s position as a global electronics manufacturing hub.

Ashwini Vaishnaw, Union Minister for Electronics and Information Technology, stated that the Mobile Phone Manufacturing Scheme will provide a significant impetus to the development of Indian-owned mobile brands, intellectual property and design.

EXPLAINED: How will India’s new Rs 62,500-crore smartphone manufacturing scheme boost local brands?

Apple is cutting more than 200 jobs across its Siri and Vision Pro operations, in one of its clearest recent signs that the company is changing where it puts its resources. Around 100 positions are being eliminated from the Vision Pro organisation, while another 100 or so are being cut from Siri and related software teams, according to reports. The reshuffle is particularly significant because Apple is scaling back some Vision Pro projects while simultaneously reorganising teams working on its next generation of AI features.<h2>Vision Pro gaming team largely shut down</h2>The Vision Pro division is facing some of the biggest changes. Apple is reportedly largely shutting down a team dedicated to gaming features for the mixed-reality headset. The company is also reducing the team responsible for creating immersive video content. That does not mean Vision Pro is being abandoned. Instead, Apple is reportedly trying to align the product more closely with how people actually use it and where the company sees greater opportunities. Apple launched Vision Pro in 2024 as its entry into spatial computing, with a starting US price of $3,499. The headset combines eye tracking, hand gestures and voice controls with a three-dimensional interface. But the high price has made mass adoption difficult, while producing large amounts of immersive video is expensive. Apple now appears to be favouring a smaller amount of in-house content while relying more on outside companies.&nbsp;<h2>Siri is being rebuilt for the AI era</h2>The other major change is happening inside Siri. The cuts are reportedly linked to Apple's attempt to rebuild Siri's underlying technology rather than simply automate existing jobs. That means some existing positions are being removed while new roles are created around the company's updated AI architecture. Apple's Intelligent Systems Experience team, which works on AI features across its products, is also affected. The company said the changes are part of an effort to “evolve our business to deliver the best experiences for our users” and said new roles would be created as part of the restructuring.<h2>Is AI really behind Apple's layoffs?</h2>Partly but not in the usual way. Unlike some technology companies that have directly linked job cuts to AI-driven efficiency, Apple's move appears to be more about changing priorities and reorganising teams. For Vision Pro, Apple is reportedly putting less emphasis on gaming and expensive immersive content. For Siri, it is moving towards a new AI architecture.At the same time, Apple is reportedly exploring future products including smart glasses, while a new Vision Pro model is also expected further down the line. The message from Apple is therefore less about abandoning existing technology and more about deciding which version of its future deserves the most people and money.

Apple is cutting more than 200 jobs across Siri, Vision Pro and related software teams. The company is largely shutting down its Vision Pro gaming team and reducing immersive-video work while reorganising Siri around a new AI architecture and shifting resources towards future devices.

Apple is cutting more than 200 jobs across its Siri and Vision Pro operations, in one of its clearest recent signs that the company is changing where it puts its resources. Around 100 positions are being eliminated from the Vision Pro organisation, while another 100 or so are being cut from Siri and related software teams, according to reports. The reshuffle is particularly significant because Apple is scaling back some Vision Pro projects while simultaneously reorganising teams working on its next generation of AI features. Vision Pro gaming team largely shut down The Vision Pro division is facing some of the biggest changes. Apple is reportedly largely shutting down a team dedicated to gaming features for the mixed-reality headset. The company is also reducing the team responsible for creating immersive video content. That does not mean Vision Pro is being abandoned. Instead, Apple is reportedly trying to align the product more closely with how people actually use it and where the company sees greater opportunities. Apple launched Vision Pro in 2024 as its entry into spatial computing, with a starting US price of $3,499. The headset combines eye tracking, hand gestures and voice controls with a three-dimensional interface. But the high price has made mass adoption difficult, while producing large amounts of immersive video is expensive. Apple now appears to be favouring a smaller amount of in-house content while relying more on outside companies. Siri is being rebuilt for the AI era The other major change is happening inside Siri. The cuts are reportedly linked to Apple's attempt to rebuild Siri's underlying technology rather than simply automate existing jobs. That means some existing positions are being removed while new roles are created around the company's updated AI architecture. Apple's Intelligent Systems Experience team, which works on AI features across its products, is also affected. The company said the changes are part of an effort to “evolve our business to deliver the best experiences for our users” and said new roles would be created as part of the restructuring. Is AI really behind Apple's layoffs? Partly but not in the usual way. Unlike some technology companies that have directly linked job cuts to AI-driven efficiency, Apple's move appears to be more about changing priorities and reorganising teams. For Vision Pro, Apple is reportedly putting less emphasis on gaming and expensive immersive content. For Siri, it is moving towards a new AI architecture. At the same time, Apple is reportedly exploring future products including smart glasses, while a new Vision Pro model is also expected further down the line. The message from Apple is therefore less about abandoning existing technology and more about deciding which version of its future deserves the most people and money.

Apple is cutting more than 200 jobs across Siri, Vision Pro and related software teams. The company is largely shutting down its Vision Pro gaming team and reducing immersive-video work while reorganising Siri around a new AI architecture and shifting resources towards future devices.

Apple cuts 200+ jobs across Siri and Vision Pro teams: Here’s what is changing

If you are considering buying an iPhone 17 Pro, waiting a few weeks could make more sense. Apple is expected to unveil the iPhone 18 Pro and iPhone 18 Pro Max in September, and current leaks point to several meaningful upgrades rather than a simple yearly refresh. Apple has not confirmed the launch date or specifications, but September 8 or 9 are currently among the reported possibilities.<h2>Here are nine changes that could make the wait worthwhile</h2>1. A new 2nm A20 Pro chip&nbsp;The biggest internal upgrade could be Apple's A20 Pro, reportedly built using TSMC's 2nm process. The smaller process should help improve performance and power efficiency, which could benefit gaming and on-device AI.&nbsp;2. Apple's C2 modemApple is expected to continue replacing third-party modem technology with its own. The C2 modem could improve connectivity while reducing power consumption. Some reports also suggest Apple is exploring broader satellite connectivity.&nbsp;3. A smaller Dynamic IslandThe front of the iPhone could look cleaner. Reports suggest Apple may reduce the size of the Dynamic Island, with under-display Face ID technology potentially helping free up screen space. Whether Apple can achieve the full change this year remains uncertain.&nbsp;4. The camera could get a major hardware changeThe 48MP main Fusion camera is widely rumoured to gain a variable aperture. Unlike the fixed aperture on recent Pro models, the lens could physically adjust how much light reaches the sensor. That could mean better control in bright and dark scenes, as well as greater control over background blur and depth of field.&nbsp;5. Better telephoto photographyApple could also give the telephoto camera a wider aperture and improve its optics. That could be particularly useful when shooting subjects in low light or using zoom.&nbsp;6. A simpler Camera ControlThe Camera Control introduced with the iPhone 16 could be redesigned. Reports suggest Apple may remove some of its touch-sensitive components while retaining the main camera controls, potentially making it easier to use.&nbsp;7. More efficient displaysThe Pro models are expected to retain 6.3-inch and 6.9-inch OLED displays, but could move to an improved LTPO+ technology. The main benefit may be efficiency, helping the phone reduce power consumption.&nbsp;8. A bigger Pro Max batteryThe iPhone 18 Pro Max could receive a particularly noticeable battery upgrade. Current reports suggest a capacity of around 5,567mAh for US models, compared with 5,088mAh for the US iPhone 17 Pro Max. Combined with the 2nm chip and C2 modem, that could translate into longer real-world battery life.&nbsp;9. Satellite connectivity could go furtherApple already offers satellite-based emergency features. The next step could be satellite connectivity capable of supporting more than emergency communication, although availability would depend heavily on network infrastructure and regional support.&nbsp;<h2>Should you wait for iPhone 18 Pro?</h2>For existing iPhone 17 Pro owners, the upgrade may not be essential. But for someone about to buy a new Pro iPhone, the combination of a 2nm chip, variable-aperture camera, larger battery, smaller Dynamic Island and C2 modem could make waiting worthwhile. There is one big catch: none of these specifications are officially confirmed by Apple yet. The launch date, pricing and final feature list could still change.

The iPhone 18 Pro and Pro Max are expected to arrive in September 2026 with several upgrades, including an A20 Pro 2nm chip, C2 modem, variable-aperture camera, larger Pro Max battery and smaller Dynamic Island. Apple has yet to confirm the specifications or launch date.

If you are considering buying an iPhone 17 Pro, waiting a few weeks could make more sense. Apple is expected to unveil the iPhone 18 Pro and iPhone 18 Pro Max in September, and current leaks point to several meaningful upgrades rather than a simple yearly refresh. Apple has not confirmed the launch date or specifications, but September 8 or 9 are currently among the reported possibilities. Here are nine changes that could make the wait worthwhile 1. A new 2nm A20 Pro chip The biggest internal upgrade could be Apple's A20 Pro, reportedly built using TSMC's 2nm process. The smaller process should help improve performance and power efficiency, which could benefit gaming and on-device AI. 2. Apple's C2 modem Apple is expected to continue replacing third-party modem technology with its own. The C2 modem could improve connectivity while reducing power consumption. Some reports also suggest Apple is exploring broader satellite connectivity. 3. A smaller Dynamic Island The front of the iPhone could look cleaner. Reports suggest Apple may reduce the size of the Dynamic Island, with under-display Face ID technology potentially helping free up screen space. Whether Apple can achieve the full change this year remains uncertain. 4. The camera could get a major hardware change The 48MP main Fusion camera is widely rumoured to gain a variable aperture. Unlike the fixed aperture on recent Pro models, the lens could physically adjust how much light reaches the sensor. That could mean better control in bright and dark scenes, as well as greater control over background blur and depth of field. 5. Better telephoto photography Apple could also give the telephoto camera a wider aperture and improve its optics. That could be particularly useful when shooting subjects in low light or using zoom. 6. A simpler Camera Control The Camera Control introduced with the iPhone 16 could be redesigned. Reports suggest Apple may remove some of its touch-sensitive components while retaining the main camera controls, potentially making it easier to use. 7. More efficient displays The Pro models are expected to retain 6.3-inch and 6.9-inch OLED displays, but could move to an improved LTPO+ technology. The main benefit may be efficiency, helping the phone reduce power consumption. 8. A bigger Pro Max battery The iPhone 18 Pro Max could receive a particularly noticeable battery upgrade. Current reports suggest a capacity of around 5,567mAh for US models, compared with 5,088mAh for the US iPhone 17 Pro Max. Combined with the 2nm chip and C2 modem, that could translate into longer real-world battery life. 9. Satellite connectivity could go further Apple already offers satellite-based emergency features. The next step could be satellite connectivity capable of supporting more than emergency communication, although availability would depend heavily on network infrastructure and regional support. Should you wait for iPhone 18 Pro? For existing iPhone 17 Pro owners, the upgrade may not be essential. But for someone about to buy a new Pro iPhone, the combination of a 2nm chip, variable-aperture camera, larger battery, smaller Dynamic Island and C2 modem could make waiting worthwhile. There is one big catch: none of these specifications are officially confirmed by Apple yet. The launch date, pricing and final feature list could still change.

The iPhone 18 Pro and Pro Max are expected to arrive in September 2026 with several upgrades, including an A20 Pro 2nm chip, C2 modem, variable-aperture camera, larger Pro Max battery and smaller Dynamic Island. Apple has yet to confirm the specifications or launch date.

From 2nm chip to bigger battery: 9 iPhone 18 Pro upgrades to know

Anthropic has launched Claude Academy, an official online learning platform designed to teach people how to use its Claude AI assistant more effectively. The courses are free and accessible without signing in, with learning material available in multiple languages, including Japanese. Anthropic says the academy caters to everyone from AI beginners to advanced developers. The move comes as AI assistants are becoming more than simple chatbots. Claude is increasingly being used for coding, research, workplace tasks and autonomous agents, making it harder for new users to understand what these tools can actually do.

<blockquote class="twitter-tweet">Claude Academy is now live. Whether you&#39;re figuring out what AI is or already using Claude every day, there&#39;s a path that meets you where you are. The courses and tutorials are free and open to anyone at <a href="https://t.co/WRiSRAvK6l">https://t.co/WRiSRAvK6l</a> <a href="https://t.co/llx2W0VIIy">pic.twitter.com/llx2W0VIIy</a>&mdash; Claude (@claudeai) <a href="https://x.com/claudeai/status/2090518650251804742?ref_src=twsrc%5Etfw">August 20, 2026</a></blockquote> <script async src="https://platform.x.com/widgets.js" charset="utf-8"></script>

<h2>What is Claude Academy?</h2>Claude Academy is essentially a free online school for Anthropic's AI ecosystem. The curriculum starts with AI fundamentals before moving into product-specific learning. Anthropic provides separate paths covering Claude.ai, Claude Cowork, Claude Code, Claude Tag and Claude Platform. The Claude.ai lessons cover basics such as writing better prompts, asking useful follow-up questions and organising work into projects. For more advanced users, the courses move into coding and AI agents. That includes Claude Code, Anthropic's coding tool, as well as developer-focused material on using Claude through its platform and deploying applications with capabilities such as Computer Use. Some lessons also include practical exercises, allowing users to learn by actually working with Claude rather than simply reading instructions. Users who sign in can save their progress and return to their courses later.<h2>Why is Anthropic launching an AI school?</h2>The timing is significant. AI tools are becoming increasingly powerful, but many users still rely on trial and error, social media posts and unofficial tutorials to learn how to use them. Anthropic is now trying to remove that barrier by putting official guidance in one place.The company has also been pushing Claude beyond traditional chat. Claude Tag, for example, lets teams bring Claude into Slack, where it can work with shared context, connected tools and company data. It can also handle longer-running tasks and follow up with users. That makes structured education more valuable. Users need to understand not only what Claude can answer, but also how to delegate work to an AI agent safely and effectively.&nbsp;<h2>Claude Academy could help Anthropic win more users</h2>Anthropic's strategy is not limited to beginners. By teaching developers how to use Claude Code and its API, and showing businesses how to deploy agent-based features, the company can potentially make its wider ecosystem easier to adopt. Anthropic already uses Claude Tag internally across engineering and other teams, highlighting how its own products are moving towards AI agents that can carry out work rather than simply respond to questions. Claude Academy therefore serves a bigger purpose than teaching people how to write better prompts.&nbsp;It is about teaching users how to work with AI from asking a chatbot a question to handing an AI agent an entire task.

Anthropic has launched Claude Academy, a free official learning platform covering AI basics, prompting, Claude Code, Claude Tag, Claude Platform and more. It aims to help beginners, developers and businesses learn how to use Claude as AI moves from chatbots towards autonomous agents.

Anthropic has launched Claude Academy, an official online learning platform designed to teach people how to use its Claude AI assistant more effectively. The courses are free and accessible without signing in, with learning material available in multiple languages, including Japanese. Anthropic says the academy caters to everyone from AI beginners to advanced developers. The move comes as AI assistants are becoming more than simple chatbots. Claude is increasingly being used for coding, research, workplace tasks and autonomous agents, making it harder for new users to understand what these tools can actually do.

Anthropic has launched Claude Academy, a free official learning platform covering AI basics, prompting, Claude Code, Claude Tag, Claude Platform and more. It aims to help beginners, developers and businesses learn how to use Claude as AI moves from chatbots towards autonomous agents.

Anthropic launches Claude Academy: Free AI courses teach users how to master Claude

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