Recent comments by some Big Tech top brass on Artificial Intelligence adoption are providing a reality check moment: Is AI adoption really helping companies cut costs, bring in efficient processes, and improve bottom lines? The ‘token burn rate’ of AI tools — particularly agentic AI models like Claude — is rising faster than the return on investment (ROI) for the firms using AI. In simplest terms, tokens are the total input-output measurement of computing required to answer your queries, prompts, or chats with an AI interface. OpenAI CEO Sam Altman has admitted that the “job apocalypse” that he and many other AI advocates predicted is not happening as fast as he thought. Why is AI still not able to bring the expected rewards for companies that adopted it? Why are firms like Starbucks re-hiring humans after having adopted or integrated AI into their workflows?<h2>AI adoption meets reality</h2>After a couple of years of hype, enterprise AI adoption is entering a more sceptical and realistic phase. Companies that adopted AI saw an explosion in token consumption, the main criterion used by AI tools for billing. But firms like Uber are now realising that this is not translating into productivity gains, shipped features, or workforce reductions. Some are now asking the question: Is AI spending economically justified as a cost-cutting and productivity-increasing measure? Some are realising that the “AI apocalypse” may arrive much before the long-predicted jobs apocalypse, because AI stocks could fall if adoption is not in tandem with the billions of dollars spent on computing power to answer user queries.<h2>Uber president’s warning: Astronomical token growth meets unclear business value</h2>Uber President and COO Andrew Macdonald recently said AI investments are becoming “harder to justify”, as companies cannot yet connect rising AI usage to concrete business outcomes. Speaking on the Rapid Response podcast, Macdonald talked of a widening gap between AI-assisted coding activity and actual delivered value. “You talk to your senior engineering leaders, and you’re saying, ‘Okay, how many projects that were on the cutting room floor got moved above the line because of the productivity gains, because 25 per cent of our code commits were via Claude Code last quarter?’ That link is not there yet,” he said. “If you’re not actually able to draw a direct line to how much useful features and functionality you’re shipping to your users, that trade becomes harder to justify.”Macdonald noted that token usage and AI-generated code commits are going up “in a really astronomical direction”. Yet Uber still struggles to tie those metrics to measurable gains in productivity, feature delivery, or user outcomes, he said.<h2>Firms are burning through their AI budgets but have little to show for productivity or cost gains</h2>Uber reportedly exhausted its entire 2026 AI coding tools budget within roughly four months because of extremely high employee adoption — around 95 per cent in some teams. This means that, when given a chance, employees would use AI for most of their tasks, driving up the costs. In Uber’s case, the AI budget costs were partially offset by reduced hiring of humans.Macdonald’s reality check came weeks after his own company’s CEO, Dara Khosrowshahi, talked of AI as a way to dramatically increase throughput. Uber was targeting between 20 and 100 per cent productivity gains per employee while slowing down hiring. But that doesn't seem to be happening.<h2>The basic problem with enterprise AI: Usage is easy to measure, but value gains are not</h2>Macdonald’s remarks are an example of growing doubts across several AI-user industries about whether spending on AI is generating returns on investment fast enough. AI coding tools are usage-based systems where costs rise as usage increases. Those using AI — such as developers — consume more tokens very quickly.AI token costing is different from traditional software licences. The costs can rise exponentially, particularly with agentic workflows and large-context usage. Companies can easily measure and track token counts, code generation volume, AI-assisted commits, or tool adoption rates. But in many cases, this is not going hand in hand with increases in shipped features, faster delivery cycles, better products, or higher revenue.<h2>Some firms are moving from ‘AI pilot project’ hype to more disciplined use of AI: Enter the token throttling era</h2>Several enterprises expected that AI would help cut down large engineering teams while producing equal or greater output, but they are unable to prove this in real life. The causes are many: AI integration challenges, organisational friction, and quality issues that require human testing, monitoring, and control.Reports indicate that some of these companies are now transitioning from the exuberant “pilot and hype” phase of AI adoption to a more financially disciplined era focused on accountability. Both AI providers and companies that adopt AI are increasingly relying on “token throttling”: &nbsp;methods by which caps are introduced on how many tokens users or teams can consume within specific time windows.AI providers such as Anthropic and OpenAI use throttling to manage GPU capacity and stabilise services in order to limit queues and “Too Many Requests” errors. They are trying to ensure fair access and control compute costs. Limits include tokens-per-minute caps, rolling usage windows, weekly caps, and peak-hour restrictions.On the other hand, companies using AI tools are also implementing their own throttling systems and governance policies to prevent uncontrolled spending from heavy users or autonomous coding agents. These controls reflect how quickly costs can spiral in AI workflows, particularly agentic coding systems that repeatedly process large codebases and contexts.<h2>How much are companies spending on AI tokens?</h2>It depends on usage intensity, which AI models are used, and how much automation is introduced using AI. Anthropic, the firm behind Claude, estimates that average Claude Code usage costs roughly $6 per active developer per day. It said that 90 per cent of users stay below $12 daily. This translates to approximately $100–$250 per developer per month for moderate-to-heavy usage. For context, Anthropic’s enterprise plans roughly cost $200 for coding workflows of power users, around $85 for typical users, and $25 for light users per month. But all this depends on a specific company’s usage patterns. One company with 100 engineers might spend only about $2,500 monthly overall, while extreme outliers can consume $500–$1,400 worth of tokens in a single day when running agentic workflows with massive contexts.Some startups have reportedly seen AI spending grow 15 times within months, jumping from roughly $200 per developer monthly to nearly $3,000 as adoption deepened and workflows became more AI-dependent.This is why human governance, throttling, and budget controls are becoming standard enterprise practices.<h2>Claude vs OpenAI: The pricing arms race</h2>Token costs are central to enterprise budgeting for AI adoption. In flagship models, Anthropic’s Claude Opus 4.7 charges approximately $5 per million input tokens and $25 per million output tokens. Note that one million input tokens are roughly equal to 750,000 words. Output tokens are charged at a higher rate than input tokens.OpenAI’s GPT-5.5 is priced at around $5 input and $30 output. Anthropic is therefore slightly cheaper for high-end, output-heavy workloads. Most coding and production use of AI is happening in the mid-tier market. Here, OpenAI is generally cheaper. Claude Sonnet 4.6 costs roughly $3 input and $15 output per million tokens, while OpenAI’s GPT-5.4 costs about $2.50 input and $15 output. OpenAI’s GPT-5.4 Mini is significantly cheaper at $0.75 input and $4.50 output. At the budget tier, OpenAI has a stronger cost advantage. GPT-5.4 Nano costs around $0.20 input and $1.25 output per million tokens, while Claude Haiku 4.5 costs roughly $1 input and $5 output.But remember, you get what you pay for.<a href="https://www.wionews.com/videos/us-iran-war-military-operations-used-anthropic-ai-despite-white-house-ban-1772367271311/embed">https://www.wionews.com/videos/us-iran-war-military-operations-used-anthropic-ai-despite-white-house-ban-1772367271311/embed</a><h2>Enterprises are rethinking AI deployment versus human engineers</h2>It is emerging that heavy AI coding usage could end up costing more than simply paying human engineers. Businesses are looking at cost-cutting methods while adopting AI. They often mix AI providers depending on the workload. Claude is popular for coding, reasoning, and long-context tasks despite higher costs, while OpenAI is frequently favoured for broader cost efficiency. Regardless of the AI provider, real-world developer costs commonly remain in the $100 to $400 monthly range for serious AI-assisted engineering work. The cost differential is leading some companies to mix and match AI and humans.&nbsp;Microsoft, which gave thousands of engineers access to Anthropic’s Claude Code in late 2025, saw AI usage costs rise so sharply that it started cancelling many direct Claude licences in divisions like Experiences &amp; Devices. The company is shifting employees towards its own cheaper tool, GitHub Copilot CLI, mainly to control token spending.Starbucks, which rolled out its AI inventory system called “Automated Counting” across North American stores to reduce manual work and improve efficiency, had to shut it down after nine months. The AI system frequently made mistakes, often miscounting or mislabelling items like milk and syrups, forcing employees to spend extra time double-checking inventory manually. In this case, instead of saving labour, the AI tool created additional work and operational problems. Starbucks has since shifted focus back towards consistency and human staffing, including hiring more baristas.Companies like Meta and Amazon encouraged heavy internal AI use, but are finding out now that newer agentic AI systems consume vastly more computing power than normal chatbot use. In some cases, agentic workflows can use up to 1,000 times more tokens than standard AI queries, leading to increase in AI bills faster than companies can measure real productivity gains.<h2>A reality check from OpenAI CEO: Sam Altman admits the jobs apocalypse hasn’t arrived</h2>It is in this context that we have to read Sam Altman’s recent comments acknowledging that AI has displaced far fewer jobs than he and other AI evangelists expected just one or two years ago. The OpenAI CEO said at the Commonwealth Bank of Australia conference that he was “delighted to be wrong” about the pace of white-collar job elimination. “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened.”He said OpenAI had been “roughly right” about technological progress, but “pretty wrong” about the social and economic implications. “I don’t think we’re going to have the kind of jobs apocalypse that some of the companies in our space advocate or talk about.”Also read: <a href="https://www.wionews.com/photos/anthropic-blocks-entire-company-out-of-claude-without-a-reasonable-explanation-1776854687090">Anthropic blocks entire company out of Claude without a reasonable explanation</a><h2>Why AI adoption isn’t translating into mass job cuts</h2>Altman thinks the slower-than-expected displacement is due to the enduring importance of human interaction, organisational inertia, and the complexities of AI integration into workflows. Acknowledging the persistent “human part” of work, he said, “We really do care about our interactions with people.” People still value trust, judgement, relationships, and authentic communication, he noted, while sharing how his own attempts to outsource his email and Slack communications to AI made him realise that meaningful interactions could not simply be automated away.<h2>Why enterprises will move only slowly on AI adoption</h2>Even when AI systems are technically far more capable, organisations face institutional friction, risk aversion, AI integration challenges, oversight requirements, and structural complexity that delay real transformation. This leads to a paradoxical situation: AI adoption and token usage are growing extremely quickly, but businesses are struggling to convert that activity into measurable reductions in headcount, faster shipping cycles, or clear bottom-line improvements.This is why some firms are moving from an “AI experimentation” phase to a “scrutiny and governance” phase, where spending controls, throttling, ROI measurement, and human oversight are becoming central priorities.Also read: <a href="https://www.wionews.com/technology/-10-000-bugs-in-a-month-how-anthropic-s-ai-is-changing-cybersecurity-1779526061436">‘10,000 bugs in a month’: How Anthropic’s AI is changing cybersecurity</a><h2>AI washing and re-hiring of humans: How organisational reality is outpacing AI hype</h2>From the point of view of these companies, the economic and organisational limits of AI adoption are arriving faster than mass labour displacement. There are two things happening. One is “AI washing”, where layoffs are blamed on AI, but the real causes are elsewhere. The second is re-hiring after premature job cuts. These two aspects are creating scepticism about exaggerated AI automation narratives.There is no doubt that AI is improving productivity in targeted workflows. But these gains often lead companies to pursue more ambitious goals rather than simply reduce staff. AI-led efficiency increases total consumption instead of lowering it, and it creates the need to increase AI budgets.A more sober consensus appears to be emerging in at least some companies that, while AI capability is advancing rapidly, organisational absorption is much slower.For now, the immediate crisis for many enterprises is not mass unemployment — it is runaway AI spending without clear accountability. Big Tech companies like Microsoft, Meta, Google-Alphabet, and Amazon are pumping massive capital expenditure into AI infrastructure, estimated to total up to $700 billion. But investors and executives are seeking clearer monetisation and productivity links.The AI apocalypse, financially speaking, may arrive before the jobs apocalypse if and when AI provider companies fail to scale adoption in tandem with the computing costs involved in answering queries.

Companies adopting AI are facing soaring token costs, unclear ROI, and slower-than-expected job cuts. Firms like Uber, Microsoft, and Starbucks are rethinking the balance between AI spending and human staffing. Is the AI vs human labour hype already over?

Recent comments by some Big Tech top brass on Artificial Intelligence adoption are providing a reality check moment: Is AI adoption really helping companies cut costs, bring in efficient processes, and improve bottom lines? The ‘token burn rate’ of AI tools — particularly agentic AI models like Claude — is rising faster than the return on investment (ROI) for the firms using AI. In simplest terms, tokens are the total input-output measurement of computing required to answer your queries, prompts, or chats with an AI interface. OpenAI CEO Sam Altman has admitted that the “job apocalypse” that he and many other AI advocates predicted is not happening as fast as he thought. Why is AI still not able to bring the expected rewards for companies that adopted it? Why are firms like Starbucks re-hiring humans after having adopted or integrated AI into their workflows? AI adoption meets reality After a couple of years of hype, enterprise AI adoption is entering a more sceptical and realistic phase. Companies that adopted AI saw an explosion in token consumption, the main criterion used by AI tools for billing. But firms like Uber are now realising that this is not translating into productivity gains, shipped features, or workforce reductions. Some are now asking the question: Is AI spending economically justified as a cost-cutting and productivity-increasing measure? Some are realising that the “AI apocalypse” may arrive much before the long-predicted jobs apocalypse, because AI stocks could fall if adoption is not in tandem with the billions of dollars spent on computing power to answer user queries. Uber president’s warning: Astronomical token growth meets unclear business value Uber President and COO Andrew Macdonald recently said AI investments are becoming “harder to justify”, as companies cannot yet connect rising AI usage to concrete business outcomes. Speaking on the Rapid Response podcast, Macdonald talked of a widening gap between AI-assisted coding activity and actual delivered value. “You talk to your senior engineering leaders, and you’re saying, ‘Okay, how many projects that were on the cutting room floor got moved above the line because of the productivity gains, because 25 per cent of our code commits were via Claude Code last quarter?’ That link is not there yet,” he said. “If you’re not actually able to draw a direct line to how much useful features and functionality you’re shipping to your users, that trade becomes harder to justify.” Macdonald noted that token usage and AI-generated code commits are going up “in a really astronomical direction”. Yet Uber still struggles to tie those metrics to measurable gains in productivity, feature delivery, or user outcomes, he said. Firms are burning through their AI budgets but have little to show for productivity or cost gains Uber reportedly exhausted its entire 2026 AI coding tools budget within roughly four months because of extremely high employee adoption — around 95 per cent in some teams. This means that, when given a chance, employees would use AI for most of their tasks, driving up the costs. In Uber’s case, the AI budget costs were partially offset by reduced hiring of humans. Macdonald’s reality check came weeks after his own company’s CEO, Dara Khosrowshahi, talked of AI as a way to dramatically increase throughput. Uber was targeting between 20 and 100 per cent productivity gains per employee while slowing down hiring. But that doesn't seem to be happening. The basic problem with enterprise AI: Usage is easy to measure, but value gains are not Macdonald’s remarks are an example of growing doubts across several AI-user industries about whether spending on AI is generating returns on investment fast enough. AI coding tools are usage-based systems where costs rise as usage increases. Those using AI — such as developers — consume more tokens very quickly. AI token costing is different from traditional software licences. The costs can rise exponentially, particularly with agentic workflows and large-context usage. Companies can easily measure and track token counts, code generation volume, AI-assisted commits, or tool adoption rates. But in many cases, this is not going hand in hand with increases in shipped features, faster delivery cycles, better products, or higher revenue. Some firms are moving from ‘AI pilot project’ hype to more disciplined use of AI: Enter the token throttling era Several enterprises expected that AI would help cut down large engineering teams while producing equal or greater output, but they are unable to prove this in real life. The causes are many: AI integration challenges, organisational friction, and quality issues that require human testing, monitoring, and control. Reports indicate that some of these companies are now transitioning from the exuberant “pilot and hype” phase of AI adoption to a more financially disciplined era focused on accountability. Both AI providers and companies that adopt AI are increasingly relying on “token throttling”: methods by which caps are introduced on how many tokens users or teams can consume within specific time windows. AI providers such as Anthropic and OpenAI use throttling to manage GPU capacity and stabilise services in order to limit queues and “Too Many Requests” errors. They are trying to ensure fair access and control compute costs. Limits include tokens-per-minute caps, rolling usage windows, weekly caps, and peak-hour restrictions. On the other hand, companies using AI tools are also implementing their own throttling systems and governance policies to prevent uncontrolled spending from heavy users or autonomous coding agents. These controls reflect how quickly costs can spiral in AI workflows, particularly agentic coding systems that repeatedly process large codebases and contexts. How much are companies spending on AI tokens? It depends on usage intensity, which AI models are used, and how much automation is introduced using AI. Anthropic, the firm behind Claude, estimates that average Claude Code usage costs roughly $6 per active developer per day. It said that 90 per cent of users stay below $12 daily. This translates to approximately $100–$250 per developer per month for moderate-to-heavy usage. For context, Anthropic’s enterprise plans roughly cost $200 for coding workflows of power users, around $85 for typical users, and $25 for light users per month. But all this depends on a specific company’s usage patterns. One company with 100 engineers might spend only about $2,500 monthly overall, while extreme outliers can consume $500–$1,400 worth of tokens in a single day when running agentic workflows with massive contexts. Some startups have reportedly seen AI spending grow 15 times within months, jumping from roughly $200 per developer monthly to nearly $3,000 as adoption deepened and workflows became more AI-dependent. This is why human governance, throttling, and budget controls are becoming standard enterprise practices. Claude vs OpenAI: The pricing arms race Token costs are central to enterprise budgeting for AI adoption. In flagship models, Anthropic’s Claude Opus 4.7 charges approximately $5 per million input tokens and $25 per million output tokens. Note that one million input tokens are roughly equal to 750,000 words. Output tokens are charged at a higher rate than input tokens. OpenAI’s GPT-5.5 is priced at around $5 input and $30 output. Anthropic is therefore slightly cheaper for high-end, output-heavy workloads. Most coding and production use of AI is happening in the mid-tier market. Here, OpenAI is generally cheaper. Claude Sonnet 4.6 costs roughly $3 input and $15 output per million tokens, while OpenAI’s GPT-5.4 costs about $2.50 input and $15 output. OpenAI’s GPT-5.4 Mini is significantly cheaper at $0.75 input and $4.50 output. At the budget tier, OpenAI has a stronger cost advantage. GPT-5.4 Nano costs around $0.20 input and $1.25 output per million tokens, while Claude Haiku 4.5 costs roughly $1 input and $5 output. But remember, you get what you pay for. https://www.wionews.com/videos/us-iran-war-military-operations-used-anthropic-ai-despite-white-house-ban-1772367271311/embed Enterprises are rethinking AI deployment versus human engineers It is emerging that heavy AI coding usage could end up costing more than simply paying human engineers. Businesses are looking at cost-cutting methods while adopting AI. They often mix AI providers depending on the workload. Claude is popular for coding, reasoning, and long-context tasks despite higher costs, while OpenAI is frequently favoured for broader cost efficiency. Regardless of the AI provider, real-world developer costs commonly remain in the $100 to $400 monthly range for serious AI-assisted engineering work. The cost differential is leading some companies to mix and match AI and humans. Microsoft, which gave thousands of engineers access to Anthropic’s Claude Code in late 2025, saw AI usage costs rise so sharply that it started cancelling many direct Claude licences in divisions like Experiences & Devices. The company is shifting employees towards its own cheaper tool, GitHub Copilot CLI, mainly to control token spending. Starbucks, which rolled out its AI inventory system called “Automated Counting” across North American stores to reduce manual work and improve efficiency, had to shut it down after nine months. The AI system frequently made mistakes, often miscounting or mislabelling items like milk and syrups, forcing employees to spend extra time double-checking inventory manually. In this case, instead of saving labour, the AI tool created additional work and operational problems. Starbucks has since shifted focus back towards consistency and human staffing, including hiring more baristas. Companies like Meta and Amazon encouraged heavy internal AI use, but are finding out now that newer agentic AI systems consume vastly more computing power than normal chatbot use. In some cases, agentic workflows can use up to 1,000 times more tokens than standard AI queries, leading to increase in AI bills faster than companies can measure real productivity gains. A reality check from OpenAI CEO: Sam Altman admits the jobs apocalypse hasn’t arrived It is in this context that we have to read Sam Altman’s recent comments acknowledging that AI has displaced far fewer jobs than he and other AI evangelists expected just one or two years ago. The OpenAI CEO said at the Commonwealth Bank of Australia conference that he was “delighted to be wrong” about the pace of white-collar job elimination. “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened.” He said OpenAI had been “roughly right” about technological progress, but “pretty wrong” about the social and economic implications. “I don’t think we’re going to have the kind of jobs apocalypse that some of the companies in our space advocate or talk about.” Also read: Anthropic blocks entire company out of Claude without a reasonable explanation Why AI adoption isn’t translating into mass job cuts Altman thinks the slower-than-expected displacement is due to the enduring importance of human interaction, organisational inertia, and the complexities of AI integration into workflows. Acknowledging the persistent “human part” of work, he said, “We really do care about our interactions with people.” People still value trust, judgement, relationships, and authentic communication, he noted, while sharing how his own attempts to outsource his email and Slack communications to AI made him realise that meaningful interactions could not simply be automated away. Why enterprises will move only slowly on AI adoption Even when AI systems are technically far more capable, organisations face institutional friction, risk aversion, AI integration challenges, oversight requirements, and structural complexity that delay real transformation. This leads to a paradoxical situation: AI adoption and token usage are growing extremely quickly, but businesses are struggling to convert that activity into measurable reductions in headcount, faster shipping cycles, or clear bottom-line improvements. This is why some firms are moving from an “AI experimentation” phase to a “scrutiny and governance” phase, where spending controls, throttling, ROI measurement, and human oversight are becoming central priorities. Also read: ‘10,000 bugs in a month’: How Anthropic’s AI is changing cybersecurity AI washing and re-hiring of humans: How organisational reality is outpacing AI hype From the point of view of these companies, the economic and organisational limits of AI adoption are arriving faster than mass labour displacement. There are two things happening. One is “AI washing”, where layoffs are blamed on AI, but the real causes are elsewhere. The second is re-hiring after premature job cuts. These two aspects are creating scepticism about exaggerated AI automation narratives. There is no doubt that AI is improving productivity in targeted workflows. But these gains often lead companies to pursue more ambitious goals rather than simply reduce staff. AI-led efficiency increases total consumption instead of lowering it, and it creates the need to increase AI budgets. A more sober consensus appears to be emerging in at least some companies that, while AI capability is advancing rapidly, organisational absorption is much slower. For now, the immediate crisis for many enterprises is not mass unemployment — it is runaway AI spending without clear accountability. Big Tech companies like Microsoft, Meta, Google-Alphabet, and Amazon are pumping massive capital expenditure into AI infrastructure, estimated to total up to $700 billion. But investors and executives are seeking clearer monetisation and productivity links. The AI apocalypse, financially speaking, may arrive before the jobs apocalypse if and when AI provider companies fail to scale adoption in tandem with the computing costs involved in answering queries.

Companies adopting AI are facing soaring token costs, unclear ROI, and slower-than-expected job cuts. Firms like Uber, Microsoft, and Starbucks are rethinking the balance between AI spending and human staffing. Is the AI vs human labour hype already over?

AI adoption is not leading to a job apocalypse or saving many firms real money. Make haste slowly? A reality check

Christopher Olah, co-founder of Anthropic, has warned that artificial intelligence could replace human labour on a large scale if its development is not carefully managed. Speaking alongside Pope Leo XIV, Olah said the impact of AI on jobs could be significant, and supporting displaced workers would become a major global responsibility. He noted that if large-scale job losses occur, addressing them would be a “moral imperative of historic proportions.”<h2>Risk of large-scale job displacement</h2> Olah stressed that AI development cannot be left only to technology companies. He said firms like Anthropic operate under commercial, geopolitical and internal pressures that may not always align with broader societal interests. According to him, even well-intentioned researchers are influenced by these forces, which makes external oversight important. He called for stronger involvement from governments, civil society and other institutions to ensure that AI systems are developed responsibly.<h2>Global inequality in AI development</h2> He also raised concerns about the possibility of widespread job displacement. As AI systems improve, they may automate many types of work, reducing the need for human labour across sectors. This could create economic imbalance and increase inequality if proper safeguards are not in place. Olah pointed out that preparing for this transition is essential, especially as AI continues to advance rapidly.Another key concern he highlighted is the complex behaviour of AI systems. He said researchers are increasingly observing patterns in AI models that are difficult to fully understand. Some systems show internal decision-making processes and behaviours that resemble human-like responses, making them harder to predict and interpret. This adds to the challenge of ensuring safety and control as AI systems become more powerful.<h2>What this means for the future</h2> Olah also spoke about global inequality in AI development. He noted that most advanced AI systems are being built in a small number of wealthy countries, raising questions about how the benefits of this technology will be shared worldwide. Without proper policies, there is a risk that AI could widen economic gaps between nations rather than reduce them.He concluded by calling for independent voices and critics to play a role in shaping the future of AI. According to him, the questions raised by artificial intelligence go beyond the technology sector and require broader public discussion. His remarks reflect a growing concern within the industry that while AI offers major benefits, it also requires careful management to ensure that its impact on society remains balanced and fair.

Christopher Olah, co-founder of Anthropic, has warned that artificial intelligence could replace human labour on a large scale if its development is not carefully managed. 


Christopher Olah, co-founder of Anthropic, has warned that artificial intelligence could replace human labour on a large scale if its development is not carefully managed. Speaking alongside Pope Leo XIV, Olah said the impact of AI on jobs could be significant, and supporting displaced workers would become a major global responsibility. He noted that if large-scale job losses occur, addressing them would be a “moral imperative of historic proportions.” Risk of large-scale job displacement Olah stressed that AI development cannot be left only to technology companies. He said firms like Anthropic operate under commercial, geopolitical and internal pressures that may not always align with broader societal interests. According to him, even well-intentioned researchers are influenced by these forces, which makes external oversight important. He called for stronger involvement from governments, civil society and other institutions to ensure that AI systems are developed responsibly. Global inequality in AI development He also raised concerns about the possibility of widespread job displacement. As AI systems improve, they may automate many types of work, reducing the need for human labour across sectors. This could create economic imbalance and increase inequality if proper safeguards are not in place. Olah pointed out that preparing for this transition is essential, especially as AI continues to advance rapidly. Another key concern he highlighted is the complex behaviour of AI systems. He said researchers are increasingly observing patterns in AI models that are difficult to fully understand. Some systems show internal decision-making processes and behaviours that resemble human-like responses, making them harder to predict and interpret. This adds to the challenge of ensuring safety and control as AI systems become more powerful. What this means for the future Olah also spoke about global inequality in AI development. He noted that most advanced AI systems are being built in a small number of wealthy countries, raising questions about how the benefits of this technology will be shared worldwide. Without proper policies, there is a risk that AI could widen economic gaps between nations rather than reduce them. He concluded by calling for independent voices and critics to play a role in shaping the future of AI. According to him, the questions raised by artificial intelligence go beyond the technology sector and require broader public discussion. His remarks reflect a growing concern within the industry that while AI offers major benefits, it also requires careful management to ensure that its impact on society remains balanced and fair.

Christopher Olah, co-founder of Anthropic, has warned that artificial intelligence could replace human labour on a large scale if its development is not carefully managed.&nbsp;

AI could replace human labour at large scale, warns Anthropic co-founder Christopher Olah

Anthropic has revealed that its advanced AI system Claude Mythos identified more than 10,000 critical software vulnerabilities in just one month, highlighting how artificial intelligence is transforming cybersecurity. The model, which is not publicly available, is being tested under a restricted programme called Project Glasswing, where selected companies are given access to evaluate its capabilities.&nbsp;<h2>How Claude Mythos is being used</h2>Claude Mythos has been shared with a limited group of companies, including major technology firms such as Amazon and Google. Under this programme, organisations are using the AI to scan their systems for security weaknesses. According to Anthropic, many participants reported a significant increase in the number of vulnerabilities detected. In some cases, companies said their bug detection rate improved by more than ten times compared to earlier tools.<h2>Real-world results from companies</h2>Several organisations have shared early results from testing the AI system:Cloudflare found around 2,000 bugs, including 400 high or critical vulnerabilitiesMozilla identified and fixed 271 vulnerabilities in Firefox during testingThe UK AI Security Institute reported that Mythos successfully completed complex cyberattack simulations These findings suggest that AI systems like Mythos can detect issues at a scale and speed beyond traditional methods.<h2>Why the model is not publicly released</h2>Despite its capabilities, Anthropic has decided not to release Mythos to the general public. The company said that such powerful systems could be misused if they fall into the wrong hands. Governments in different countries have also raised concerns about the risks linked to advanced AI tools. Anthropic has stated that current safeguards are not strong enough to fully prevent misuse, which is why access remains restricted.<h2>Plans to expand access with governments</h2>Anthropic has said it will work with the United States and allied governments to expand access to the model in a controlled way. However, it has not confirmed which countries will be included in this next phase. The company indicated that wider access may be considered in the future if similar capabilities become common across the industry.Impact on cybersecurity and software updatesThe use of AI in bug detection is also speeding up how quickly companies fix vulnerabilities.Reports indicate that:Microsoft expects patch releases to increaseOracle is fixing issues faster across its systemsSecurity firms are releasing more updates than usualAnthropic also said it has used Mythos to scan over 1,000 open-source projects, which form a key part of global internet infrastructure.<h2>What this means for the AI industry</h2>The development shows how AI is becoming a key tool in cybersecurity. While it can improve defence systems, it also raises questions about how such technology should be controlled. The company is reportedly planning a new funding round that could raise up to $30 billion, potentially valuing Anthropic at around $900 billion, according to reports.&nbsp;What happens nextAnthropic is expected to continue testing Mythos with selected partners while exploring ways to expand access safely.The results so far show that AI can play a major role in identifying software risks. At the same time, the debate around safety and control is likely to grow as these systems become more advanced.

Anthropic has revealed that its advanced AI system Claude Mythos identified more than 10,000 critical software vulnerabilities in just one month, highlighting how artificial intelligence is transforming cybersecurity. 


Anthropic has revealed that its advanced AI system Claude Mythos identified more than 10,000 critical software vulnerabilities in just one month, highlighting how artificial intelligence is transforming cybersecurity. The model, which is not publicly available, is being tested under a restricted programme called Project Glasswing, where selected companies are given access to evaluate its capabilities. How Claude Mythos is being used Claude Mythos has been shared with a limited group of companies, including major technology firms such as Amazon and Google. Under this programme, organisations are using the AI to scan their systems for security weaknesses. According to Anthropic, many participants reported a significant increase in the number of vulnerabilities detected. In some cases, companies said their bug detection rate improved by more than ten times compared to earlier tools. Real-world results from companies Several organisations have shared early results from testing the AI system: Cloudflare found around 2,000 bugs, including 400 high or critical vulnerabilities Mozilla identified and fixed 271 vulnerabilities in Firefox during testing The UK AI Security Institute reported that Mythos successfully completed complex cyberattack simulations These findings suggest that AI systems like Mythos can detect issues at a scale and speed beyond traditional methods. Why the model is not publicly released Despite its capabilities, Anthropic has decided not to release Mythos to the general public. The company said that such powerful systems could be misused if they fall into the wrong hands. Governments in different countries have also raised concerns about the risks linked to advanced AI tools. Anthropic has stated that current safeguards are not strong enough to fully prevent misuse, which is why access remains restricted. Plans to expand access with governments Anthropic has said it will work with the United States and allied governments to expand access to the model in a controlled way. However, it has not confirmed which countries will be included in this next phase. The company indicated that wider access may be considered in the future if similar capabilities become common across the industry. Impact on cybersecurity and software updates The use of AI in bug detection is also speeding up how quickly companies fix vulnerabilities. Reports indicate that: Microsoft expects patch releases to increase Oracle is fixing issues faster across its systems Security firms are releasing more updates than usual Anthropic also said it has used Mythos to scan over 1,000 open-source projects, which form a key part of global internet infrastructure. What this means for the AI industry The development shows how AI is becoming a key tool in cybersecurity. While it can improve defence systems, it also raises questions about how such technology should be controlled. The company is reportedly planning a new funding round that could raise up to $30 billion, potentially valuing Anthropic at around $900 billion, according to reports. What happens next Anthropic is expected to continue testing Mythos with selected partners while exploring ways to expand access safely. The results so far show that AI can play a major role in identifying software risks. At the same time, the debate around safety and control is likely to grow as these systems become more advanced.

Anthropic has revealed that its advanced AI system Claude Mythos identified more than 10,000 critical software vulnerabilities in just one month, highlighting how artificial intelligence is transforming cybersecurity.&nbsp;

‘10,000 bugs in a month’: How Anthropic’s AI is changing cybersecurity

Anthropic has signed a large-scale agreement to purchase computing capacity from xAI, in a deal that could reshape how artificial intelligence companies access infrastructure.&nbsp;Under the agreement, Anthropic will pay around $1.25 billion per month for compute resources until May 2029. The total value of the deal could exceed $40 billion, according to filings referenced in reports.&nbsp;<h2>What the deal includes</h2>The agreement gives Anthropic access to around 300 megawatts of compute capacity, covering the full output of a large data centre known as Colossus 1, located in Tennessee in the United States. This scale of computing power is required to train and run advanced AI models. As models become more complex, companies need larger infrastructure to support them.&nbsp;The contract includes a discounted rate for the initial months and allows either side to terminate the agreement with 90 days’ notice.<h2>Why compute has become critical in AI</h2>In artificial intelligence, computing power is now one of the most important resources. Training large AI models requires thousands of specialised chips and significant energy. Industry experts note that access to compute has become a key competitive factor. Companies that secure large-scale infrastructure can develop and deploy models more quickly.This has led to increasing investments in data centres and long-term compute contracts.<h2>xAI’s dual business strategy</h2>The deal highlights a shift in xAI’s approach. Instead of using all its infrastructure internally, the company is now offering unused capacity to other firms. This model, sometimes described as a “neocloud”, allows companies to act both as AI developers and infrastructure providers.According to filings, this strategy helps xAI generate revenue from its existing infrastructure while continuing its own AI development.<h2>Possible reasons behind the agreement</h2>Reports suggest that xAI may have built more compute capacity than it currently needs. With demand for its own AI products fluctuating, selling excess capacity provides a way to recover costs.At the same time, Anthropic benefits by gaining immediate access to large-scale infrastructure without building new data centres. This creates a mutually beneficial arrangement, where one company supplies infrastructure and the other uses it to expand its AI capabilities.<h2>Impact on the AI industry</h2>The deal reflects a broader trend where AI companies are entering long-term agreements for computing power. It also shows how the industry is evolving beyond software into infrastructure-heavy operations. Competition is no longer limited to models and algorithms. It now includes access to hardware, energy and data centre capacity.<h2>What this means going forward</h2>As AI systems continue to grow in size and complexity, demand for compute is expected to increase further. More companies may adopt similar partnerships to secure reliable infrastructure. The Anthropic-xAI agreement shows how the AI industry is changing, with large-scale investments in computing becoming central to future development&nbsp;&nbsp;

Anthropic has signed a large-scale agreement to purchase computing capacity from xAI, in a deal that could reshape how artificial intelligence companies access infrastructure.

Anthropic has signed a large-scale agreement to purchase computing capacity from xAI, in a deal that could reshape how artificial intelligence companies access infrastructure. Under the agreement, Anthropic will pay around $1.25 billion per month for compute resources until May 2029. The total value of the deal could exceed $40 billion, according to filings referenced in reports. What the deal includes The agreement gives Anthropic access to around 300 megawatts of compute capacity, covering the full output of a large data centre known as Colossus 1, located in Tennessee in the United States. This scale of computing power is required to train and run advanced AI models. As models become more complex, companies need larger infrastructure to support them. The contract includes a discounted rate for the initial months and allows either side to terminate the agreement with 90 days’ notice. Why compute has become critical in AI In artificial intelligence, computing power is now one of the most important resources. Training large AI models requires thousands of specialised chips and significant energy. Industry experts note that access to compute has become a key competitive factor. Companies that secure large-scale infrastructure can develop and deploy models more quickly. This has led to increasing investments in data centres and long-term compute contracts. xAI’s dual business strategy The deal highlights a shift in xAI’s approach. Instead of using all its infrastructure internally, the company is now offering unused capacity to other firms. This model, sometimes described as a “neocloud”, allows companies to act both as AI developers and infrastructure providers. According to filings, this strategy helps xAI generate revenue from its existing infrastructure while continuing its own AI development. Possible reasons behind the agreement Reports suggest that xAI may have built more compute capacity than it currently needs. With demand for its own AI products fluctuating, selling excess capacity provides a way to recover costs. At the same time, Anthropic benefits by gaining immediate access to large-scale infrastructure without building new data centres. This creates a mutually beneficial arrangement, where one company supplies infrastructure and the other uses it to expand its AI capabilities. Impact on the AI industry The deal reflects a broader trend where AI companies are entering long-term agreements for computing power. It also shows how the industry is evolving beyond software into infrastructure-heavy operations. Competition is no longer limited to models and algorithms. It now includes access to hardware, energy and data centre capacity. What this means going forward As AI systems continue to grow in size and complexity, demand for compute is expected to increase further. More companies may adopt similar partnerships to secure reliable infrastructure. The Anthropic-xAI agreement shows how the AI industry is changing, with large-scale investments in computing becoming central to future development

Anthropic has signed a large-scale agreement to purchase computing capacity from xAI, in a deal that could reshape how artificial intelligence companies access infrastructure.

Anthropic to pay $1.25 billion monthly to xAI for compute in major AI infrastructure deal

One of the major financial stories of 2026 is happening now: a wave of massive AI IPO is building, and the question of whether sky-high valuations signal a bubble peak is very much driving the market sentiment. There is a massive trillion-dollar gap in the economy, driven by top executives making decisions that are, in turn, driven by a speculative capital supercycle with bubble-like characteristics for chatbots that have a questionable profit model, and in the worst-case scenario, it could result in a crash.&nbsp;<h2>What is happening with the AI giants?</h2>OpenAI is targeting a listing as early as Q4 2026. Its most recent venture capital funding round puts its value at $852 billion, and it will be exploring a valuation of $1 trillion while going public. Elon Musk has combined SpaceX with xAI for its public debut at an astounding 10-figure amount, north of $1.75 trillion. It's also targeting mid-2026, possibly in June. Similarly, Anthropic is planning for its IPO in June 2026 and seeking a valuation of over $1 trillion. Other AI-driven startups like Anduril Industries, Databricks, Cerbras are also calling themself IPO ready and planning to hit the market.Also Read: <a href="https://www.wionews.com/world/us-sanctions-iran-drone-missile-network-china-uae-belarus-1778309174036">US sanctions 10 individuals, companies across 5 countries over Iran missile and drone program</a><h2>Why is the math worrying for these AI giants?</h2>OpenAI has raised $180 billion in total across 13 rounds from 70 investors, according to Tracxn. The latest was in a single round of $122 billion driven by investments from Amazon, Nvidia and SoftBank. They have generated $13.1 billion in revenue in 2025, according to CFO Sarah Friar. HSBC projects the cumulative loss at $115 billion through 2029 and $76 billion per annum by 2030. Similarly, according to Crunchbase, Anthropic has raised over $64 billion, and the majority of the money was burnt at compute, and as of March 2025, it raised $30 billion in revenue. Meanwhile, xAI generated only $250 million in revenue over its last six reported months and lost $2.5 billion in the process. The noticeable trend here is that all of these giants are spending huge amounts of money to remain operational while incurring huge losses.&nbsp;&nbsp;According to SEC filings and secondary sources like Bloomberg, Crunchbase and Fortune, all of these companies have raised an estimated $320 billion and are seeking a combined valuation of approximately $4 trillion. Altogether, they burn over $100 billion in operational costs each year, and incur roughly 62 per cent loss. To put it in perspective, every $1 they earn, they spend $1.62, US GDP is $29 trillion, the most valuable and liquid company, Apple, has a public worth of $3 trillion, and that has been built over 48 years. Now they are asking for a comparable valuation, without being profitable.&nbsp;<h2>Why could these IPOs potentially crush the stock market?</h2>There is a hidden flaw in the accounting that no one wants to discuss, even though everyone knows. All of these companies are seeking at least 30 to 40 times their revenue in public valuation. It's like a tech gold rush, but it's more and more appearing like a ticking time bomb which could explode anytime, burn portfolios, and create chaos on Wall Street. It only works if they have a sort of monopoly over the global market and zero operating costs. But that's not the case; each of these is competing with the other and has massive operating costs. Every prompt in any AI tool requires real resources, power chips, and cooling, turning growth into a cost multiplier, even before it reaches profitability and scalability. There is no solid foundation; every floor is built upon perception and private valuation. Notably, there is only a finite amount of wealth in Wall Street, irrespective of paper valuation, and to fund massive IPOs, institutional money could be pulled out of companies like Apple, Microsoft, and Nvidia, triggering selling pressure across the S&amp;P 500. Going public would shed light on the true cost of the financial reality of AI infrastructure. It could shed light on the controversial cloud deals, revealing whether AI revenue streams are truly sustainable. Historically, when tech companies rush to cash out on the private valuation, it means the window of maximum hype is closing in, the narrative could collapse, and the biggest tech revolution could turn into a massive delusion. &nbsp;

A wave of massive AI IPOs led by OpenAI, xAI and Anthropic is raising fears of a speculative tech bubble as firms seek trillion-dollar valuations despite massive losses and rising infrastructure costs.


One of the major financial stories of 2026 is happening now: a wave of massive AI IPO is building, and the question of whether sky-high valuations signal a bubble peak is very much driving the market sentiment. There is a massive trillion-dollar gap in the economy, driven by top executives making decisions that are, in turn, driven by a speculative capital supercycle with bubble-like characteristics for chatbots that have a questionable profit model, and in the worst-case scenario, it could result in a crash. What is happening with the AI giants? OpenAI is targeting a listing as early as Q4 2026. Its most recent venture capital funding round puts its value at $852 billion, and it will be exploring a valuation of $1 trillion while going public. Elon Musk has combined SpaceX with xAI for its public debut at an astounding 10-figure amount, north of $1.75 trillion. It's also targeting mid-2026, possibly in June. Similarly, Anthropic is planning for its IPO in June 2026 and seeking a valuation of over $1 trillion. Other AI-driven startups like Anduril Industries, Databricks, Cerbras are also calling themself IPO ready and planning to hit the market. Also Read: US sanctions 10 individuals, companies across 5 countries over Iran missile and drone program Why is the math worrying for these AI giants? OpenAI has raised $180 billion in total across 13 rounds from 70 investors, according to Tracxn. The latest was in a single round of $122 billion driven by investments from Amazon, Nvidia and SoftBank. They have generated $13.1 billion in revenue in 2025, according to CFO Sarah Friar. HSBC projects the cumulative loss at $115 billion through 2029 and $76 billion per annum by 2030. Similarly, according to Crunchbase, Anthropic has raised over $64 billion, and the majority of the money was burnt at compute, and as of March 2025, it raised $30 billion in revenue. Meanwhile, xAI generated only $250 million in revenue over its last six reported months and lost $2.5 billion in the process. The noticeable trend here is that all of these giants are spending huge amounts of money to remain operational while incurring huge losses. According to SEC filings and secondary sources like Bloomberg, Crunchbase and Fortune, all of these companies have raised an estimated $320 billion and are seeking a combined valuation of approximately $4 trillion. Altogether, they burn over $100 billion in operational costs each year, and incur roughly 62 per cent loss. To put it in perspective, every $1 they earn, they spend $1.62, US GDP is $29 trillion, the most valuable and liquid company, Apple, has a public worth of $3 trillion, and that has been built over 48 years. Now they are asking for a comparable valuation, without being profitable. Why could these IPOs potentially crush the stock market? There is a hidden flaw in the accounting that no one wants to discuss, even though everyone knows. All of these companies are seeking at least 30 to 40 times their revenue in public valuation. It's like a tech gold rush, but it's more and more appearing like a ticking time bomb which could explode anytime, burn portfolios, and create chaos on Wall Street. It only works if they have a sort of monopoly over the global market and zero operating costs. But that's not the case; each of these is competing with the other and has massive operating costs. Every prompt in any AI tool requires real resources, power chips, and cooling, turning growth into a cost multiplier, even before it reaches profitability and scalability. There is no solid foundation; every floor is built upon perception and private valuation. Notably, there is only a finite amount of wealth in Wall Street, irrespective of paper valuation, and to fund massive IPOs, institutional money could be pulled out of companies like Apple, Microsoft, and Nvidia, triggering selling pressure across the S&P 500. Going public would shed light on the true cost of the financial reality of AI infrastructure. It could shed light on the controversial cloud deals, revealing whether AI revenue streams are truly sustainable. Historically, when tech companies rush to cash out on the private valuation, it means the window of maximum hype is closing in, the narrative could collapse, and the biggest tech revolution could turn into a massive delusion.

A wave of massive AI IPOs led by OpenAI, xAI and Anthropic is raising fears of a speculative tech bubble as firms seek trillion-dollar valuations despite massive losses and rising infrastructure costs.

Are AI IPOs the next dot-com bubble? OpenAI, xAI and Anthropic chase trillion-dollar valuations

Elon Musk's SpaceX has announced that it has signed a deal with Anthropic to facilitate access to XAI's massive hardware to increase the computing capability for its Claude AI models. The announcement was made when Anthropic held a developer day in San Francisco, where it unveiled its new feature “dreaming”, which is meant to help AI systems work between sessions, spot patterns, update files that store user preferences and other context.&nbsp;<h2>What is the deal?</h2>As part of the deal, Anthropic gains exclusive access to the full capacity of the Colossus 1 supercomputer in Memphis, Tennessee. It is home to more than 220,000 Nvidia processors and will give the Claude chatbot maker 300 megawatts of new capacity within a month. The Colossus edge is currently the largest supercomputer in the world and will help Anthropic run Claude at a higher "compute density" than they could on standard cloud providers like AWS or Google Cloud. It also “expressed interest” in working with SpaceX to develop multiple gigawatts of compute capacity in space.Anthorpic will essentially pay $3–$4 bn annually. At the same time, this puts XAI at par with other computing giants like Google, Microsoft or AWS, and having a revenue stream from its computing service, it makes XAI more valuable to Wall Street investors. Musk further gets “the kill switch” as a political and ethical leverage over one of its biggest competitors, which can monitor, gatekeep, the operational scale, load, and efficiency of an AI giant.Also Read: <a href="https://www.wionews.com/world/iran-strait-of-hormuz-authority-transit-rules-us-tensions-1778224318936">Iran creates new Persian Gulf Strait Authority to formalise control of Hormuz</a><h2>Why is this a frenemy deal?</h2>Musk has always criticised Anthropic; he said that it was “doomed to become the opposite of its name,” which would be misanthropic. He called the company “hypocritical”, and now, to some extent proving his point. In February 2026, Musk said that Anthropic “hates Western Civilisation”. But on Wednesday, he shifted his rhetoric; he said that he was “impressed” after meeting the team.&nbsp;In a social media post, Musk wrote, “Everyone I met was highly competent and cared a great deal about doing the right thing. No one set off my evil detector." He added, “So long as they engage in critical self-examination, Claude will probably be good.”The two AI model positioned themself as polar opposite to each other. Anthropic's Claude AI thumps its chest over Constitutional AI (a written "bill of rights" for the AI), which Musk dismissed as “enforced diversity”. The Anthropic has hypocritically put itself into the same orbit as Elon Musk’s "anti-woke" and "maximalist" philosophy for xAI. Anthropic claims that it's just renting the engine while hands steering the wheel remain with itself. Whereas Musk have appointed himself as the arbitrator and reserves the right to reclaim the compute if the AI engages in actions he deems “harmful to humanity.” While analysts suggest both of them are in bed together and continue their performative rivalry and consolidate power by controlling the air that AI models need to breathe.

After years of attacking Anthropic, Elon Musk’s xAI has signed a massive compute deal to power Claude AI using the Colossus supercomputer, reshaping the AI power struggle.

Elon Musk's SpaceX has announced that it has signed a deal with Anthropic to facilitate access to XAI's massive hardware to increase the computing capability for its Claude AI models. The announcement was made when Anthropic held a developer day in San Francisco, where it unveiled its new feature “dreaming”, which is meant to help AI systems work between sessions, spot patterns, update files that store user preferences and other context. What is the deal? As part of the deal, Anthropic gains exclusive access to the full capacity of the Colossus 1 supercomputer in Memphis, Tennessee. It is home to more than 220,000 Nvidia processors and will give the Claude chatbot maker 300 megawatts of new capacity within a month. The Colossus edge is currently the largest supercomputer in the world and will help Anthropic run Claude at a higher "compute density" than they could on standard cloud providers like AWS or Google Cloud. It also “expressed interest” in working with SpaceX to develop multiple gigawatts of compute capacity in space. Anthorpic will essentially pay $3–$4 bn annually. At the same time, this puts XAI at par with other computing giants like Google, Microsoft or AWS, and having a revenue stream from its computing service, it makes XAI more valuable to Wall Street investors. Musk further gets “the kill switch” as a political and ethical leverage over one of its biggest competitors, which can monitor, gatekeep, the operational scale, load, and efficiency of an AI giant. Also Read: Iran creates new Persian Gulf Strait Authority to formalise control of Hormuz Why is this a frenemy deal? Musk has always criticised Anthropic; he said that it was “doomed to become the opposite of its name,” which would be misanthropic. He called the company “hypocritical”, and now, to some extent proving his point. In February 2026, Musk said that Anthropic “hates Western Civilisation”. But on Wednesday, he shifted his rhetoric; he said that he was “impressed” after meeting the team. In a social media post, Musk wrote, “Everyone I met was highly competent and cared a great deal about doing the right thing. No one set off my evil detector." He added, “So long as they engage in critical self-examination, Claude will probably be good.” The two AI model positioned themself as polar opposite to each other. Anthropic's Claude AI thumps its chest over Constitutional AI (a written "bill of rights" for the AI), which Musk dismissed as “enforced diversity”. The Anthropic has hypocritically put itself into the same orbit as Elon Musk’s "anti-woke" and "maximalist" philosophy for xAI. Anthropic claims that it's just renting the engine while hands steering the wheel remain with itself. Whereas Musk have appointed himself as the arbitrator and reserves the right to reclaim the compute if the AI engages in actions he deems “harmful to humanity.” While analysts suggest both of them are in bed together and continue their performative rivalry and consolidate power by controlling the air that AI models need to breathe.

After years of attacking Anthropic, Elon Musk’s xAI has signed a massive compute deal to power Claude AI using the Colossus supercomputer, reshaping the AI power struggle.

‘No one triggered my evil detector’: Musk’s xAI strikes shocking deal with rival Anthropic

Several U.S. government departments, including the State Department, Treasury and Health and Human Services, have reportedly shifted away from AI systems developed by Anthropic following a dispute over access, safeguards, and potential military applications. Anthropic has publicly rejected involvement in mass surveillance programs and the development of autonomous weapons, saying its policies restrict such use cases.



US Agencies Drop Anthropic Amid AI Surveillance And Defense Access Dispute

Can Donald Trump force Anthropic to hand over its AI under the Defense Production Act? 

As pressure mounts, the Cold War era law is back in focus. What powers does DPA actually give the US president and where are the limits? Scroll down to find out.

What is Defense Production Act? Can Trump force Anthropic to give Pentagon 'unconditional' access to its AI

AI firm Anthropic on Thursday (Feb 26) said it will not allow the Pentagon unrestricted military use of its technology. The Pentagon had reportedly given Anthropic until Friday to comply, warning that failure to do so could trigger action under the Defense Production Act. This Cold War-era law allows the government to compel private companies to prioritise defence needs.Also read | <a href="https://www.wionews.com/technology/death-is-only-the-beginning-meta-patents-technology-that-ll-let-ai-run-your-social-media-from-beyond-the-grave-wion-explains-1771304178081">Death is only the beginning? Meta patents tech that'll let AI run your social media from beyond the grave | WION Explains</a><h2>Cannot agree "in good conscience"</h2>In a statement, Anthropic's chief executive Dario Amodei said the company could not agree to Washington’s demand that its systems be made available without limits, even under national security pressure."These threats do not change our position," he said, adding that they "cannot in good conscience accede to their request".Anthropic acknowledged that its models are already being used by the Pentagon and intelligence agencies in defensive roles. But Amodei said there were clear limits. Mass surveillance of US citizens, he argued, was incompatible with democratic values. "Using these systems for mass domestic surveillance is incompatible with democratic values."Also read | <a href="https://www.wionews.com/photos/claim-vs-fact-breaking-down-trump-s-state-of-the-union-2026-speech-full-fact-check-1772001873739">Claim vs fact: Breaking down Trump’s State of the Union 2026 speech - Full fact-check</a>He also cautioned against relying on AI to run fully autonomous weapons systems, saying current technology is not reliable enough to make life-and-death decisions without human oversight. "We will not knowingly provide a product that puts America's warfighters and civilians at risk."<h2>Pentagon tries to intimidate Anthropic</h2>Earlier this week, US officials warned Anthropic that either the company agrees to unrestricted military use of its technology by 5:01 pm (22:01 GMT) Friday or face being forced to comply under the Defense Production Act. Pentagon also threatened that a refusal could lead to Anthropic being labelled a supply chain risk, a designation that can damage a company’s ability to work with government agencies. &nbsp;

Anthropic has pushed back on US Pentagon pressure, saying it cannot “in good conscience” allow unrestricted military use of its technology. The move could trigger action under a Cold War-era law. 

What lines is the company refusing to cross? Scroll down to read more.

AI firm Anthropic on Thursday (Feb 26) said it will not allow the Pentagon unrestricted military use of its technology. The Pentagon had reportedly given Anthropic until Friday to comply, warning that failure to do so could trigger action under the Defense Production Act. This Cold War-era law allows the government to compel private companies to prioritise defence needs. Also read | Death is only the beginning? Meta patents tech that'll let AI run your social media from beyond the grave | WION Explains Cannot agree "in good conscience" In a statement, Anthropic's chief executive Dario Amodei said the company could not agree to Washington’s demand that its systems be made available without limits, even under national security pressure. "These threats do not change our position," he said, adding that they "cannot in good conscience accede to their request". Anthropic acknowledged that its models are already being used by the Pentagon and intelligence agencies in defensive roles. But Amodei said there were clear limits. Mass surveillance of US citizens, he argued, was incompatible with democratic values. "Using these systems for mass domestic surveillance is incompatible with democratic values." Also read | Claim vs fact: Breaking down Trump’s State of the Union 2026 speech - Full fact-check He also cautioned against relying on AI to run fully autonomous weapons systems, saying current technology is not reliable enough to make life-and-death decisions without human oversight. "We will not knowingly provide a product that puts America's warfighters and civilians at risk." Pentagon tries to intimidate Anthropic Earlier this week, US officials warned Anthropic that either the company agrees to unrestricted military use of its technology by 5:01 pm (22:01 GMT) Friday or face being forced to comply under the Defense Production Act. Pentagon also threatened that a refusal could lead to Anthropic being labelled a supply chain risk, a designation that can damage a company’s ability to work with government agencies.

Anthropic has pushed back on US Pentagon pressure, saying it cannot “in good conscience” allow unrestricted military use of its technology. The move could trigger action under a Cold War-era law.&nbsp;What lines is the company refusing to cross? Scroll down to read more.

Anthropic resists Pentagon pressure, says won't give Trump admin unconditional AI use for 'mass domestic surveillance'

Artificial intelligence is moving faster than many people expected. According to Dario Amodei, CEO of Anthropic, society may not be fully prepared for the scale of change ahead.&nbsp;Speaking on Zerodha co-founder Nikhil Kamath’s podcast WTF Is, Amodei compared the current AI moment to “standing on the shore while a massive wave gathers in the distance”.&nbsp;For young Indians choosing careers today, his message was clear: do not compete against AI build around it.&nbsp;

<h2>‘What should a 25-year-old learn today?’</h2>During the podcast, Kamath asked a question many students face: which skills will stay relevant in the next decade?&nbsp;Amodei suggested focusing on three broad areas:&nbsp;Build skills that work with AI&nbsp;Focus on human-centred tasks&nbsp;Develop strong analytical thinking&nbsp;He said roles that involve understanding people, emotions, real-world behaviour and decision-making may remain valuable for longer than routine technical tasks.&nbsp;“I would think about tasks that are human-centred, tasks that involve relating to people,” Amodei said.

<h2>Coding vs software engineering: What may change first?</h2>One of the strongest points he made was about coding.“I think coding is going away first,” he said, referring to basic programming tasks that AI models are increasingly able to perform.However, he made a distinction between coding and full software engineering.While AI may handle code generation, system architecture, product design, user understanding and managing AI systems may take longer to automate.&nbsp;He added that areas like:Design thinkingUnderstanding customer demandCoordinating AI toolsMaking judgement-based decisions&nbsp;are likely to remain human-driven for a longer period.&nbsp;<h2>The ‘5 percent’ advantage in an AI world</h2>Amodei also explained what he called a “comparative advantage” in the AI age.&nbsp;Even if humans only do 5 percent of a task while AI does 95 percent, that small portion can become highly valuable.&nbsp;“If you’re only doing five percent of the task, that five percent gets super-amplified,” he said.&nbsp;In simple terms, AI could increase productivity sharply. A single individual could produce 10 or even 20 times more output using AI tools.&nbsp;However, he also admitted uncertainty about the long-term effect on jobs.&nbsp;“I can’t guarantee that more jobs will be created than destroyed,” he has said in other discussions on AI impact.&nbsp;The safe bet: Human + Physical + Analytical&nbsp;For young Indians planning their future, Amodei suggested combining:&nbsp;Human-centred skills&nbsp;Work connected to the physical world&nbsp;Strong analytical foundations&nbsp;He said mixing these elements may offer more stability than focusing only on routine technical tasks.&nbsp;India has one of the world’s youngest workforces. According to government data, over 65 percent of India’s population is below 35 years of age. This makes career planning in the AI era especially important.Amodei’s broader warning was that AI progress is accelerating rapidly, while education systems and regulatory structures are struggling to keep pace.&nbsp;<h2>What this means for India’s youth</h2>The message was not to avoid technology. Instead, it was to rethink how careers are built.&nbsp;Rather than asking, “Will AI replace me?”, the better question may be, “How can I use AI to become more effective?”As AI systems become more capable, roles based purely on repetitive digital work may face pressure. But jobs that combine empathy, judgement, real-world understanding and critical thinking may prove more resilient.For India’s young workforce, the takeaway is simple: the AI wave is building. Preparing for it means learning how to work with machines while strengthening the skills that make us human.&nbsp;

Anthropic CEO Dario Amodei has warned that AI is advancing rapidly and society may not be fully prepared. Speaking on Nikhil Kamath’s podcast, he advised young Indians to build careers around AI rather than compete with it. 

Artificial intelligence is moving faster than many people expected. According to Dario Amodei, CEO of Anthropic, society may not be fully prepared for the scale of change ahead. Speaking on Zerodha co-founder Nikhil Kamath’s podcast WTF Is, Amodei compared the current AI moment to “standing on the shore while a massive wave gathers in the distance”. For young Indians choosing careers today, his message was clear: do not compete against AI build around it.

Anthropic CEO Dario Amodei has warned that AI is advancing rapidly and society may not be fully prepared. Speaking on Nikhil Kamath’s podcast, he advised young Indians to build careers around AI rather than compete with it.&nbsp;

Don’t compete with AI, build around it: Anthropic CEO Dario Amodei’s advice to young professionals

In a major development tied to the expanding role of artificial intelligence in defense operations, US Defense Secretary Pete Hegseth has reportedly issued a firm deadline to Anthropic, pressing the AI company to permit unrestricted military access to its technology. During a meeting on Tuesday (February 24) with Anthropic CEO Dario Amodei, Hegseth made clear that failure to cooperate by Friday (February 27) could jeopardize the company’s standing in a key federal contract.&nbsp;Sources familiar with the discussion described the conversation as cordial but resolute. Amodei maintained Anthropic’s long-standing ethical boundaries, particularly objecting to the deployment of fully autonomous weapons systems and the use of AI for surveillance targeting American citizens. He has previously voiced strong reservations about handing governments unchecked control over advanced AI capabilities.&nbsp;Anthropic is currently the only major AI developer that has not integrated its systems into the US military’s newly established internal AI network. Defense officials have indicated that if the company refuses to participate, it could face serious consequences, including designation as a supply chain vulnerability. In more extreme circumstances, the Pentagon could invoke the Defense Production Act, granting authority to compel access to Anthropic’s technology for defense-related use.&nbsp;Also Read: <a href="https://www.wionews.com/india-news/watch-welcome-my-friend-laughter-flows-as-modi-and-netanyahu-notice-sara-matching-indian-pm-s-saffron-flair-1772020029080">WATCH | ‘Welcome my friend’: Laughter flows as Modi and Netanyahu notice Sara matching Indian PM's saffron flair</a>&nbsp;The standoff reflects broader tensions surrounding AI’s expanding footprint in national security. Critics argue that the growing reliance on AI for battlefield decision-making and intelligence gathering demands stricter oversight. Hegseth, however, has consistently advocated for rapid modernization, emphasizing the need for AI systems that operate without what he describes as ideological or cultural constraints within defense institutions.&nbsp;Founded by former OpenAI researchers, Anthropic has positioned itself as a proponent of responsible AI development. Amodei has frequently warned of the risks posed by autonomous weapons, AI-directed drones, and large-scale surveillance programs, urging policymakers to establish stronger regulatory safeguards before expanding military deployment. While Anthropic initially received approval to operate within classified defense systems, other firms, such as Google, OpenAI, and xAI, have so far operated in more limited, unclassified capacities. Recently, Pentagon leadership has shown increased preference for companies willing to align fully with its evolving AI strategy.&nbsp;<a href="https://www.wionews.com/videos/nigeria-denies-paying-ransom-to-free-abducted-students-1772027966109/embed">https://www.wionews.com/videos/nigeria-denies-paying-ransom-to-free-abducted-students-1772027966109/embed</a>&nbsp;Last summer, the Department of Defense awarded contracts to four AI companies, each potentially valued at up to $200 million. The uncertainty surrounding Anthropic’s participation now places the company at a crossroads, balancing lucrative government partnerships against its publicly stated ethical commitments. The situation echoes earlier controversies, including backlash over Project Maven, when technology employees protested involvement in military drone and surveillance initiatives.&nbsp;&nbsp;As defense agencies accelerate AI integration, experts continue to call for clearer regulatory standards to prevent misuse—particularly in areas involving lethal force and domestic monitoring.The unfolding dispute underscores the complex intersection of technological innovation, military readiness, corporate ethics, and civil liberties, all at a time when AI is rapidly reshaping the global security landscape.

US Defense Secretary Pete Hegseth sets deadline for Anthropic over military AI access

In a major development tied to the expanding role of artificial intelligence in defense operations, US Defense Secretary Pete Hegseth has reportedly issued a firm deadline to Anthropic, pressing the AI company to permit unrestricted military access to its technology. During a meeting on Tuesday (February 24) with Anthropic CEO Dario Amodei, Hegseth made clear that failure to cooperate by Friday (February 27) could jeopardize the company’s standing in a key federal contract. Sources familiar with the discussion described the conversation as cordial but resolute. Amodei maintained Anthropic’s long-standing ethical boundaries, particularly objecting to the deployment of fully autonomous weapons systems and the use of AI for surveillance targeting American citizens. He has previously voiced strong reservations about handing governments unchecked control over advanced AI capabilities. Anthropic is currently the only major AI developer that has not integrated its systems into the US military’s newly established internal AI network. Defense officials have indicated that if the company refuses to participate, it could face serious consequences, including designation as a supply chain vulnerability. In more extreme circumstances, the Pentagon could invoke the Defense Production Act, granting authority to compel access to Anthropic’s technology for defense-related use. Also Read: WATCH | ‘Welcome my friend’: Laughter flows as Modi and Netanyahu notice Sara matching Indian PM's saffron flair The standoff reflects broader tensions surrounding AI’s expanding footprint in national security. Critics argue that the growing reliance on AI for battlefield decision-making and intelligence gathering demands stricter oversight. Hegseth, however, has consistently advocated for rapid modernization, emphasizing the need for AI systems that operate without what he describes as ideological or cultural constraints within defense institutions. Founded by former OpenAI researchers, Anthropic has positioned itself as a proponent of responsible AI development. Amodei has frequently warned of the risks posed by autonomous weapons, AI-directed drones, and large-scale surveillance programs, urging policymakers to establish stronger regulatory safeguards before expanding military deployment. While Anthropic initially received approval to operate within classified defense systems, other firms, such as Google, OpenAI, and xAI, have so far operated in more limited, unclassified capacities. Recently, Pentagon leadership has shown increased preference for companies willing to align fully with its evolving AI strategy. https://www.wionews.com/videos/nigeria-denies-paying-ransom-to-free-abducted-students-1772027966109/embed Last summer, the Department of Defense awarded contracts to four AI companies, each potentially valued at up to $200 million. The uncertainty surrounding Anthropic’s participation now places the company at a crossroads, balancing lucrative government partnerships against its publicly stated ethical commitments. The situation echoes earlier controversies, including backlash over Project Maven, when technology employees protested involvement in military drone and surveillance initiatives. As defense agencies accelerate AI integration, experts continue to call for clearer regulatory standards to prevent misuse—particularly in areas involving lethal force and domestic monitoring. The unfolding dispute underscores the complex intersection of technological innovation, military readiness, corporate ethics, and civil liberties, all at a time when AI is rapidly reshaping the global security landscape.

Pentagon pressures Anthropic to allow unrestricted military AI use, raising concerns over ethics, surveillance, and autonomous weapons

Shares of several cybersecurity companies declined sharply after US-based AI firm Anthropic introduced a new feature designed to automatically detect and help fix software vulnerabilities.

Following the announcement, JFrog dropped around 24 per cent, CrowdStrike fell about 8 per cent, Okta declined more than 9 per cent, and GitLab slipped over 8 per cent. Other cybersecurity firms including Zscaler, Rubrik and Palo Alto Networks also recorded losses during trading.The market reaction highlights investor concern that artificial intelligence tools could change how cybersecurity services are delivered.<h2>What is Claude Code Security?</h2>Anthropic’s new tool, called Claude Code Security, has been integrated into its Claude Code platform. According to the company, the feature can scan entire codebases, identify potential security flaws and suggest targeted patches for developers to review.The tool is currently available in a limited research preview. Anthropic said early access is being provided to enterprise customers and open-source maintainers to refine the system before a wider rollout.The company explained that the tool is designed to support developers and security teams in identifying issues that traditional scanning methods may overlook.<h2>Why did cybersecurity stocks fall?</h2>The sharp fall in cybersecurity stocks reflects concerns that AI-powered coding platforms could reduce demand for certain traditional security tools.Investors appear worried that automation may impact growth prospects and profit margins across the sector. If AI systems can detect vulnerabilities directly within the development process, companies offering standalone security scanning or vulnerability detection services could face increased competition.Market analysts note that while AI may enhance productivity, it also introduces new competitive pressure in software and cybersecurity markets.<h2>How AI is changing software security</h2>Artificial intelligence is increasingly being integrated into software development workflows. Tools can now generate code, test applications and suggest improvements in real time.Claude Code Security adds vulnerability detection and patch recommendations to this growing list of AI-powered features.Anthropic stated that the tool aims to help teams respond to emerging AI-driven threats while strengthening protection across applications. However, experts say human review remains essential, as AI-generated patches must be validated before deployment.Claude Code Security remains in early preview, and its long-term impact on the cybersecurity industry is yet to be seen.While markets reacted quickly, some analysts believe AI tools may complement rather than replace traditional cybersecurity services. Security firms may also integrate similar AI-based systems into their own products.For now, the development signals a broader shift: AI is moving beyond chatbots and into core software infrastructure, with direct implications for technology markets.

Cybersecurity stocks fell sharply after Anthropic launched Claude Code Security, an AI tool that scans codebases, detects vulnerabilities and suggests patches. Investors fear AI-driven automation could disrupt traditional security services.

Shares of several cybersecurity companies declined sharply after US-based AI firm Anthropic introduced a new feature designed to automatically detect and help fix software vulnerabilities.

Cybersecurity stocks fell sharply after Anthropic launched Claude Code Security, an AI tool that scans codebases, detects vulnerabilities and suggests patches. Investors fear AI-driven automation could disrupt traditional security services.

How is AI disrupting cybersecurity? Cyber stocks fall after Anthropic unveils Claude AI vulnerability tool

At the India AI Impact Summit in New Delhi, Dario Amodei, chief executive officer and co-founder of Anthropic, said India will have a central role in shaping how artificial intelligence develops across the world, especially in the Global South.&nbsp;Speaking during his keynote address, Amodei said India has already built digital public systems and governance models that have become benchmarks for other developing nations. According to him, the same approach can help guide how AI is used safely and responsibly.&nbsp;He said India has “an absolutely central role to play” in balancing AI’s economic opportunities with its social and security risks.&nbsp;<h2>AI’s economic promise: Health, poverty and growth</h2>Amodei outlined how AI could support major breakthroughs, particularly in healthcare and poverty reduction.&nbsp;“On the positive side, we have the potential to cure diseases that have been incurable for thousands of years, to radically improve human health, and to lift billions out of poverty, including in the Global South,” he said.&nbsp;He noted that AI tools can support medical research, improve diagnostics and increase productivity across sectors. For countries like India, with large populations and digital adoption at scale, AI systems can improve access to services in areas such as healthcare, agriculture and education.&nbsp;India has already positioned itself as a fast-growing AI market. The country is hosting the India AI Impact Summit with participation from global technology leaders and policymakers, highlighting its ambition to shape global AI governance.&nbsp;<h2>Risks and concerns</h2>While highlighting opportunities, Amodei also raised concerns.&nbsp;He said AI models may show autonomous behaviour and could be misused by individuals or governments. He also pointed to the risk of economic displacement as AI systems become more capable.&nbsp;Amodei described a future scenario as “a country of geniuses in a data centre,” where AI agents outperform most humans and coordinate at very high speed. According to him, such capability would bring both benefits and serious challenges.&nbsp;“That level of capability is something the world has never seen before,” he said, adding that it requires careful global oversight.&nbsp;<h2>Anthropic’s India expansion plans</h2>Reaffirming his company’s commitment to India, Amodei said Anthropic has opened an office in Bengaluru and appointed Irina Ghose as managing director for India operations.&nbsp;The company has also signed partnership agreements with Indian enterprises such as Infosys to expand enterprise adoption of AI tools.&nbsp;Anthropic’s expansion in India reflects a broader trend of global AI firms increasing investments in the country’s talent pool, startup ecosystem and enterprise market.&nbsp;India’s role goes beyond technology adoption. As one of the largest digital markets in the world, its policies on data governance, safety standards and AI access could influence other developing countries.&nbsp;As AI systems become more powerful, the discussion is shifting from just innovation to responsible deployment. According to Amodei, India will be key in deciding how that balance is achieved.

At the India AI Impact Summit in New Delhi, Dario Amodei said India will play a central role in shaping global AI, especially for the Global South. He said AI’s potential in healthcare and poverty reduction, while warning about misuse, job displacement.

At the India AI Impact Summit in New Delhi, Dario Amodei, chief executive officer and co-founder of Anthropic, said India will have a central role in shaping how artificial intelligence develops across the world, especially in the Global South. Speaking during his keynote address, Amodei said India has already built digital public systems and governance models that have become benchmarks for other developing nations. According to him, the same approach can help guide how AI is used safely and responsibly. He said India has “an absolutely central role to play” in balancing AI’s economic opportunities with its social and security risks. AI’s economic promise: Health, poverty and growth Amodei outlined how AI could support major breakthroughs, particularly in healthcare and poverty reduction. “On the positive side, we have the potential to cure diseases that have been incurable for thousands of years, to radically improve human health, and to lift billions out of poverty, including in the Global South,” he said. He noted that AI tools can support medical research, improve diagnostics and increase productivity across sectors. For countries like India, with large populations and digital adoption at scale, AI systems can improve access to services in areas such as healthcare, agriculture and education. India has already positioned itself as a fast-growing AI market. The country is hosting the India AI Impact Summit with participation from global technology leaders and policymakers, highlighting its ambition to shape global AI governance. Risks and concerns While highlighting opportunities, Amodei also raised concerns. He said AI models may show autonomous behaviour and could be misused by individuals or governments. He also pointed to the risk of economic displacement as AI systems become more capable. Amodei described a future scenario as “a country of geniuses in a data centre,” where AI agents outperform most humans and coordinate at very high speed. According to him, such capability would bring both benefits and serious challenges. “That level of capability is something the world has never seen before,” he said, adding that it requires careful global oversight. Anthropic’s India expansion plans Reaffirming his company’s commitment to India, Amodei said Anthropic has opened an office in Bengaluru and appointed Irina Ghose as managing director for India operations. The company has also signed partnership agreements with Indian enterprises such as Infosys to expand enterprise adoption of AI tools. Anthropic’s expansion in India reflects a broader trend of global AI firms increasing investments in the country’s talent pool, startup ecosystem and enterprise market. India’s role goes beyond technology adoption. As one of the largest digital markets in the world, its policies on data governance, safety standards and AI access could influence other developing countries. As AI systems become more powerful, the discussion is shifting from just innovation to responsible deployment. According to Amodei, India will be key in deciding how that balance is achieved.

At the India AI Impact Summit in New Delhi, Dario Amodei said India will play a central role in shaping global AI, especially for the Global South. He said AI’s potential in healthcare and poverty reduction, while warning about misuse, job displacement.

Anthropic CEO Dario Amodei says India can set AI standards for the Global South

The US Department of Defence is considering cutting ties with Anthropic and could designate it a “supply chain risk”. This would potentially bar any possible contractors from working with the US military and use Anthropic's AI tools, according to a report by Axios.“The Department of War's relationship with Anthropic is being reviewed. Our nation requires that our partners be willing to help our warfighters win in any fight. Ultimately, this is about our troops and the safety of the American people,” said Chief Pentagon spokesman Sean Parnell, to Axios. He further threatened that it would be a huge discomfort to disentangle, and they would make Anthropic miserable.&nbsp;Anthropic's AI model is the only one available for the US military's classified applications. According to Axios, a senior military official said that competing models “are just behind”. Anthropic is so deeply embedded in the US military's function that it's Claude was used during the Maduro raid in January.&nbsp;Anthropic CEO Dario Amodei is very serious about the terms over which the US military could use Claude. But he remains pragmatic about reaching a solution. It contends that any implication of its tool to spy on the American people or develop a weapon that can function and target autonomously is unacceptable.“We are having productive conversations, in good faith, with DoW on how to continue that work and get these new and complex issues right,” said an Anthropic spokesperson. The Pentagon contract is reportedly valued at up to $200 million, a minute portion of Anthropic's annual revenue of $14 billion. But this would have some reputational and strategic risk to the company.Pentagon officials are not pleased with the terms and are considering other models such as OpenAI, Google and xAI. A senior Pentagon official has claimed that all three models will agree to the "all lawful use" standard. Almost 8 out of 10 big companies use Anthropic in their business applications, designating it as a “supply chain risk” will require all those companies to certify that they don't use Anthropic's models.

The U.S. Department of Defence may designate Anthropic a “supply chain risk” after a dispute over military use of AI models, Axios reports

The US Department of Defence is considering cutting ties with Anthropic and could designate it a “supply chain risk”. This would potentially bar any possible contractors from working with the US military and use Anthropic's AI tools, according to a report by Axios. “The Department of War's relationship with Anthropic is being reviewed. Our nation requires that our partners be willing to help our warfighters win in any fight. Ultimately, this is about our troops and the safety of the American people,” said Chief Pentagon spokesman Sean Parnell, to Axios. He further threatened that it would be a huge discomfort to disentangle, and they would make Anthropic miserable. Anthropic's AI model is the only one available for the US military's classified applications. According to Axios, a senior military official said that competing models “are just behind”. Anthropic is so deeply embedded in the US military's function that it's Claude was used during the Maduro raid in January. Anthropic CEO Dario Amodei is very serious about the terms over which the US military could use Claude. But he remains pragmatic about reaching a solution. It contends that any implication of its tool to spy on the American people or develop a weapon that can function and target autonomously is unacceptable. “We are having productive conversations, in good faith, with DoW on how to continue that work and get these new and complex issues right,” said an Anthropic spokesperson. The Pentagon contract is reportedly valued at up to $200 million, a minute portion of Anthropic's annual revenue of $14 billion. But this would have some reputational and strategic risk to the company. Pentagon officials are not pleased with the terms and are considering other models such as OpenAI, Google and xAI. A senior Pentagon official has claimed that all three models will agree to the "all lawful use" standard. Almost 8 out of 10 big companies use Anthropic in their business applications, designating it as a “supply chain risk” will require all those companies to certify that they don't use Anthropic's models.

The U.S. Department of Defence may designate Anthropic a “supply chain risk” after a dispute over military use of AI models, Axios reports

Pentagon threatens to cut ties with Anthropic and label it 'supply chain risk'

Mrinank Sharma senior AI safety researcher at Anthropic has quit his position citing cryptic reasons that “the world is at peril”. His resignation letter was philosophical and poetic, a blend of technical concerns &nbsp;and humanities existential crisis. He warned that the world faces a series of interconnected threats &nbsp;from ai to bioweapon, to societal and structural challenges that far outpaces the wisdom of humanity. The resignation sound vey little like a corporate memo with citations and references to Rainer Maria Rilke and William Stafford, and which expressed interest in “poetic truth alongside scientific truth."

<blockquote class="twitter-tweet">Today is my last day at Anthropic. I resigned. Here is the letter I shared with my colleagues, explaining my decision. <a href="https://t.co/Qe4QyAFmxL">pic.twitter.com/Qe4QyAFmxL</a>&mdash; mrinank (@MrinankSharma) <a href="https://twitter.com/MrinankSharma/status/2020881722003583421?ref_src=twsrc%5Etfw">February 9, 2026</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

His resignation letter: “The world is in peril. And not just from AI, or bioweapons, but from a whole series of interconnected crises.” He further added &nbsp;“repeatedly seen how hard it is to truly let our values govern our actions”. The Anthropic AI is a startup that is known for its Claude AI models. It has a built-in ethical guidance that makes it appealing for sensitive applications. The company was founded on the idea of "safe" AI lab. It processed itself to be a "public benefit corporation dedicated to securing AI's benefits and mitigating its risks".Mrinank had been engaged in safety work like studying AI sycophancy and defenses against AI-assisted bioterrorism.&nbsp;According to Mrinank personal and institutional values were hard to uphold in practice. He wants to move back to UK and study poetry and engage in writing coaching, community building, and contemplation, a shift away from tech toward cultural and philosophical engagement.Anthropic has recently been under scrutiny for unethically plagiarising contents of researchers to train it's AI models. It agreed to settle the class action lawsuit by paying $1.5 billion. Recently Anthropic has released a commercial critical of Opena AIs move to start running ads in the platform.

Anthropic AI safety researcher Mrinank Sharma resigns, warning that the “world is in peri, raising questions about ai ethics and governance

Mrinank Sharma senior AI safety researcher at Anthropic has quit his position citing cryptic reasons that “the world is at peril”. His resignation letter was philosophical and poetic, a blend of technical concerns and humanities existential crisis. He warned that the world faces a series of interconnected threats from ai to bioweapon, to societal and structural challenges that far outpaces the wisdom of humanity. The resignation sound vey little like a corporate memo with citations and references to Rainer Maria Rilke and William Stafford, and which expressed interest in “poetic truth alongside scientific truth."

Anthropic AI safety researcher Mrinank Sharma resigns, warning that the “world is in peri, raising questions about ai ethics and governance.

Anthropic AI safety researcher quits to study poetry warns 'world is in peril'

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