Stricter gun laws that sounds like a distant dream in the United States has seen a little progress on gun control measures. The country is unable to deal with the gun lobby so it is now looking at other options like Artificial Intelligence.

Can Artificial Intelligence help stop mass shootings?

Tesla's Chief Executive Officer Elon Musk has pushed the company's Artificial Intelligence Day from August 19 to September 30.

Making the announcement on Twitter, he wrote: ''Tesla AI Day pushed to Sept 30, as we may have an Optimus prototype working by then.''

US electric carmaker Tesla is working on a priority on Optimus, which is a humanoid robot, that could ''eventually address global shortages of labor'' according to Musk.

The billionaire believes that in short term, the Optimus could be used to carry items around a factory.

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After August 19, 2021, this is Tesla's second AI (artificial intelligence) Day and its purpose is to convince great AI, software, and chip talent to join the company.

Musk, who is the world's richest man in the world with a net worth of almost $234 billion, has helped shift the traditional car sector to an all-electric future.

Wading into the future of work debate, Musk told his staff that they must return to the office for at least 40 hours a week or leave the company.

As the company tries to steer itself through supply-chain issues and disruptions in China operations, Tesla is delaying US deliveries of certain long-range models by up to a month.

(With inputs from agencies)

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Tesla's Chief Executive Officer Elon Musk has pushed the company's Artificial Intelligence Day from August 19 to September 30. Making the announcement on Twitter, he wrote: ''Tesla AI Day pushed to Sept 30, as we may have an Optimus prototype working by then.

Tesla's Chief Executive Officer Elon Musk has pushed the company's Artificial Intelligence Day from August 19 to September 30. Making the announcement on Twitter, he wrote: ''Tesla AI Day pushed to Sept 30, as we may have an Optimus prototype working by then.'' US electric carmaker Tesla is working on a priority on Optimus, which is a humanoid robot, that could ''eventually address global shortages of labor'' according to Musk. The billionaire believes that in short term, the Optimus could be used to carry items around a factory. After August 19, 2021, this is Tesla's second AI (artificial intelligence) Day and its purpose is to convince great AI, software, and chip talent to join the company. Musk, who is the world's richest man in the world with a net worth of almost $234 billion, has helped shift the traditional car sector to an all-electric future. Wading into the future of work debate, Musk told his staff that they must return to the office for at least 40 hours a week or leave the company. As the company tries to steer itself through supply-chain issues and disruptions in China operations, Tesla is delaying US deliveries of certain long-range models by up to a month. (With inputs from agencies) Watch WION's live TV here:

Tesla CEO Elon Musk pushes Artificial Intelligence Day from August 19 to September 30

Artificial Intelligence (AI) powered solutions may soon make roads in India a safer place to drive. The Indian government on Tuesday announced that a technology-fueled by AI could reduce the risk of road accidents in the country, which killed over one lakh people in 2020.

In a bid to prevent this from happening, the Indian government said that the AI approach will use a first of its kind dataset consisting of 10,000 images.

It said that this dataset is finely annotated with 34 classes collected from 182 drive sequences on Indian roads obtained from a front-facing camera attached to a car driven around the cities of Hyderabad, Bangalore, and their outskirts.

India's Ministry of Science and Technology said that this unique approach uses the predictive power of AI to identify risks on the road, and a collision alert system to communicate timely alerts to drivers, to make several improvements related to road safety.

It is being implemented in Nagpur, Maharashtra and the government aims to spread it across India.

The project aims to reduce road accidents. According to WHO, road accidents kill as many as 1.35 million people across the world each year.

"The project ‘Intelligent Solutions for Road Safety through Technology and Engineering’ (iRASTE) at Nagpur will identify potential accident-causing scenarios while driving a vehicle and alert drivers about the same with the help of the Advance Driver Assistance System (ADAS).

"The project will identify ‘grey spots’, i.e., by data analysis and mobility analysis by continuously monitoring dynamic risks on the entire road network," the Indian government said.

Grey spots are locations on roads, left unaddressed could become blackspots (locations with fatal accidents).

The system also conducts continuous monitoring of roads and designs engineering fixes to correct existing road blackspots for preventive maintenance and improved road infrastructure, government officials said.

The iRASTE project is under the I-Hub Foundation, IIIT Hyderabad, a Technology Innovation Hub set up in the technology vertical- Data Banks and Data Services, supported by the Department of Science and Technology (DST).

I-Hub Foundation has used techniques ranging from machine learning, computer vision and computational sensing for several other data-driven technological solutions in the mobility sector.

One such solution is the India Driving Dataset (IDD), a dataset for road scene understanding in unstructured environments captured from Indian roads, which deviates from the worldwide assumptions of well-delineated infrastructure such as lanes, limited traﬃc participants, low variation in object or background appearance and strong adherence to traﬃc rules.

The project consortium includes CSIR-CRRI, and Nagpur Municipal Corporation, with Mahindra and Intel as the industry partners.

The Hub is working to coordinate, integrate, and amplify basic and applied research in broad data-driven technologies as well as its dissemination and translation across the country.

One of the primary aims is to prepare a critical resource for the future use by researchers, startups, and industry, mainly in the areas of smart mobility, healthcare along with smart buildings.

"What makes the iRASTE project even more unique is that AI and technology is being applied to create practical solutions, as a blueprint, for Indian conditions. While the initial rollout of iRASTE is in Nagpur, the eventual goal is to replicate the solution in other cities too.

"Currently, talks are on with the Telangana government to adopt the technology in a fleet of buses that ply on highways. There are further plans to extend the scope of iRASTE to Goa and Gujarat also," ministry officials said.

Another dataset called Open World Object Detection on Road Scenes (ORDER) has also been developed using the India Driving Dataset that could be used by autonomous navigation systems in Indian driving conditions for localization and classification of the objects in a road scene.

Besides this, a Mobility Car Data Platform (MCDP) has been designed with several sensors – cameras, LIDARs, with the necessary computing for anyone to capture or process data on the car that can help researchers and start-ups in India test their automotive algorithms and approaches in navigation and research on Indian roads, the Indian ministry said.

A new framework, LaneRoadNet (LRNet), with an integrated mechanism considering lane and road parameters using deep learning, has been designed to address problems of Indian roads, which have several obstacles, occluded lane markings, broken dividers, cracks, potholes, etc. that put the drivers at significant risk while driving, the government said.

In this framework, a road quality score is calculated with the help of a modular scoring function. The final score helps the authorities to assess road quality and prioritize maintenance schedules of the road so as to improve the drivability.

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Artificial Intelligence (AI) powered solutions may soon make roads in India a safer place to drive. The Indian government on Tuesday announced that a technology-fueled by AI could reduce the risk of road accidents in the country, which killed over one lakh people in 2020.

Artificial Intelligence (AI) powered solutions may soon make roads in India a safer place to drive. The Indian government on Tuesday announced that a technology-fueled by AI could reduce the risk of road accidents in the country, which killed over one lakh people in 2020. In a bid to prevent this from happening, the Indian government said that the AI approach will use a first of its kind dataset consisting of 10,000 images. It said that this dataset is finely annotated with 34 classes collected from 182 drive sequences on Indian roads obtained from a front-facing camera attached to a car driven around the cities of Hyderabad, Bangalore, and their outskirts. India's Ministry of Science and Technology said that this unique approach uses the predictive power of AI to identify risks on the road, and a collision alert system to communicate timely alerts to drivers, to make several improvements related to road safety. It is being implemented in Nagpur, Maharashtra and the government aims to spread it across India. The project aims to reduce road accidents. According to WHO, road accidents kill as many as 1.35 million people across the world each year. "The project ‘Intelligent Solutions for Road Safety through Technology and Engineering’ (iRASTE) at Nagpur will identify potential accident-causing scenarios while driving a vehicle and alert drivers about the same with the help of the Advance Driver Assistance System (ADAS). "The project will identify ‘grey spots’, i.e., by data analysis and mobility analysis by continuously monitoring dynamic risks on the entire road network," the Indian government said. Grey spots are locations on roads, left unaddressed could become blackspots (locations with fatal accidents). The system also conducts continuous monitoring of roads and designs engineering fixes to correct existing road blackspots for preventive maintenance and improved road infrastructure, government officials said. The iRASTE project is under the I-Hub Foundation, IIIT Hyderabad, a Technology Innovation Hub set up in the technology vertical- Data Banks and Data Services, supported by the Department of Science and Technology (DST). I-Hub Foundation has used techniques ranging from machine learning, computer vision and computational sensing for several other data-driven technological solutions in the mobility sector. One such solution is the India Driving Dataset (IDD), a dataset for road scene understanding in unstructured environments captured from Indian roads, which deviates from the worldwide assumptions of well-delineated infrastructure such as lanes, limited traﬃc participants, low variation in object or background appearance and strong adherence to traﬃc rules. The project consortium includes CSIR-CRRI, and Nagpur Municipal Corporation, with Mahindra and Intel as the industry partners. The Hub is working to coordinate, integrate, and amplify basic and applied research in broad data-driven technologies as well as its dissemination and translation across the country. One of the primary aims is to prepare a critical resource for the future use by researchers, startups, and industry, mainly in the areas of smart mobility, healthcare along with smart buildings. "What makes the iRASTE project even more unique is that AI and technology is being applied to create practical solutions, as a blueprint, for Indian conditions. While the initial rollout of iRASTE is in Nagpur, the eventual goal is to replicate the solution in other cities too. "Currently, talks are on with the Telangana government to adopt the technology in a fleet of buses that ply on highways. There are further plans to extend the scope of iRASTE to Goa and Gujarat also," ministry officials said. Another dataset called Open World Object Detection on Road Scenes (ORDER) has also been developed using the India Driving Dataset that could be used by autonomous navigation systems in Indian driving conditions for localization and classification of the objects in a road scene. Besides this, a Mobility Car Data Platform (MCDP) has been designed with several sensors – cameras, LIDARs, with the necessary computing for anyone to capture or process data on the car that can help researchers and start-ups in India test their automotive algorithms and approaches in navigation and research on Indian roads, the Indian ministry said. A new framework, LaneRoadNet (LRNet), with an integrated mechanism considering lane and road parameters using deep learning, has been designed to address problems of Indian roads, which have several obstacles, occluded lane markings, broken dividers, cracks, potholes, etc. that put the drivers at significant risk while driving, the government said. In this framework, a road quality score is calculated with the help of a modular scoring function. The final score helps the authorities to assess road quality and prioritize maintenance schedules of the road so as to improve the drivability. WATCH WION LIVE HERE You can now write for wionews.com and be a part of the community. Share your stories and opinions with us here.

Artificial Intelligence to make roads in India safer to drive

As robots begin to dominate our everyday lives, Massachusetts Institute of Technology(MIT) researchers have taught a robot how to learn a new pick-and-place task with the help of human demonstrations.

The human demonstrations help to "reprogramme" the robot in random poses which it has never encountered earlier. The new technology allows the robot to quickly learn a new skill in&nbsp;10 to 15 minutes.

<a href="https://www.wionews.com/world/elon-musk-announces-to-roll-out-robotaxi-with-no-wheels-or-pedals-by-2024-472851">Also Read:&nbsp;Musk announces to roll out robotaxi with no wheels or pedals by 2024</a>

According to the researchers, the new technology uses a "neural network" to reconstruct 3D images, the system quickly grasps what the neural network has learned and then executes it.

The new technology is set to be a gamechanger in e-commerce warehouse storage where robots have to perform a variety of tasks like storing mugs upside down and in various places.

Watch:&nbsp;&nbsp;Use of AI-based technology in hiring talent

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The researchers say the robot needs just ten demonstrations to learn a new technique for example on how to arrange&nbsp;bottles and bowls. The technology helps the robot to seamlessly manoeuvre through "unstructured environments".

According to the researchers, if a robot visualises a completely new scenario, it becomes a difficult task. It is here a neural network model&nbsp;Neural Descriptor Field (NDF) helps the robot to understand and learn. The 3D point cloud helps the robot to apply skills in the real world.

The robot is taught how to pick a mug with physical examples much like how a child is taught. The researchers say the new "pick-and-place tasks" has an 85 per cent success rate which is assessed on how accurately the robot grasps a new object and places it in a particular location.&nbsp;

(With inputs from Agencies)&nbsp;

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As robots begin to dominate our everyday lives, Massachusetts Institute of Technology(MIT) researchers have taught a robot how to learn a new pick-and-place task with the help of human demonstrations.

As robots begin to dominate our everyday lives, Massachusetts Institute of Technology(MIT) researchers have taught a robot how to learn a new pick-and-place task with the help of human demonstrations. The human demonstrations help to "reprogramme" the robot in random poses which it has never encountered earlier. The new technology allows the robot to quickly learn a new skill in 10 to 15 minutes. Also Read: Musk announces to roll out robotaxi with no wheels or pedals by 2024 According to the researchers, the new technology uses a "neural network" to reconstruct 3D images, the system quickly grasps what the neural network has learned and then executes it. The new technology is set to be a gamechanger in e-commerce warehouse storage where robots have to perform a variety of tasks like storing mugs upside down and in various places. Watch: Use of AI-based technology in hiring talent The researchers say the robot needs just ten demonstrations to learn a new technique for example on how to arrange bottles and bowls. The technology helps the robot to seamlessly manoeuvre through "unstructured environments". According to the researchers, if a robot visualises a completely new scenario, it becomes a difficult task. It is here a neural network model Neural Descriptor Field (NDF) helps the robot to understand and learn. The 3D point cloud helps the robot to apply skills in the real world. The robot is taught how to pick a mug with physical examples much like how a child is taught. The researchers say the new "pick-and-place tasks" has an 85 per cent success rate which is assessed on how accurately the robot grasps a new object and places it in a particular location. (With inputs from Agencies) Watch WION LIVE here

How robots are learning new skills from humans

Using artificial intelligence, scientists have confirmed that birds are more colourful near the equator.

According to the study's author Christopher Cooney, ''We found that colourfulness was highest in birds from dense, closed forest habitats.''&nbsp;

"In vibrant rainforests, having colours that stand out from the crowd may help tropical species to distinguish themselves from others", he added.

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<div class="videoWrapper trancodeVideo">The study, published in the journal Nature Ecology and Evolution, has confirmed previous suspicions that colour patterns of animals vary as per their latitude.</div>

The researchers have proved a theory proposed by biologists Charles Darwin, Alexander von Humboldt, and Alfred Russel Wallace in 1850.

After comparing the flora and fauna of northern Europe with the tropical region, they were all stunned.

As per German naturalist Humboldt, "The nearer we approach the tropics, the greater the increase in the variety of structure, grace of form, and a mixture of colours, as also in perpetual youth and vigour of organic life."

Also read |&nbsp;<a href="https://www.wionews.com/science/study-shows-several-bird-species-nesting-and-laying-eggs-almost-a-month-early-465532" hreflang="en">Study shows several bird species nesting and laying eggs almost a month early</a>

To confirm the previous theory, researchers at the University of Sheffield studied more than 4,500 species of passerine birds. These included songbirds such as wrens, sparrows and blackbirds across the globe.

They used artificial intelligence to extract data from the pixels of three photographs taken from the collection of the Natural History Museum in Tring, Britain.

During their analysis, they identified the colour at 1,500 different parts of the plumage of each adult bird and ranked them on the level of intensity of the colour.

As the birds came closer to the equator their colour became brighter. While if they went farther it became duller due to the "luxuriant vegetation of the tropics."

This acted as a natural camouflage for the birds all year round. Meanwhile, the birds in the north had to adapt their plumage to handle bare trees every winter.

(With inputs from agencies)

Using artificial intelligence, scientists have confirmed that birds are more colourful near the equator. According to the study's author Christopher Cooney, ''We found that colourfulness was highest in birds from dense, closed forest habitats.

Using artificial intelligence, scientists have confirmed that birds are more colourful near the equator. According to the study's author Christopher Cooney, ''We found that colourfulness was highest in birds from dense, closed forest habitats.'' "In vibrant rainforests, having colours that stand out from the crowd may help tropical species to distinguish themselves from others", he added. The study, published in the journal Nature Ecology and Evolution, has confirmed previous suspicions that colour patterns of animals vary as per their latitude. The researchers have proved a theory proposed by biologists Charles Darwin, Alexander von Humboldt, and Alfred Russel Wallace in 1850. After comparing the flora and fauna of northern Europe with the tropical region, they were all stunned. As per German naturalist Humboldt, "The nearer we approach the tropics, the greater the increase in the variety of structure, grace of form, and a mixture of colours, as also in perpetual youth and vigour of organic life." Also read | Study shows several bird species nesting and laying eggs almost a month early To confirm the previous theory, researchers at the University of Sheffield studied more than 4,500 species of passerine birds. These included songbirds such as wrens, sparrows and blackbirds across the globe. They used artificial intelligence to extract data from the pixels of three photographs taken from the collection of the Natural History Museum in Tring, Britain. During their analysis, they identified the colour at 1,500 different parts of the plumage of each adult bird and ranked them on the level of intensity of the colour. As the birds came closer to the equator their colour became brighter. While if they went farther it became duller due to the "luxuriant vegetation of the tropics." This acted as a natural camouflage for the birds all year round. Meanwhile, the birds in the north had to adapt their plumage to handle bare trees every winter. (With inputs from agencies)

Scientists use artificial intelligence to confirm that birds are more colourful near equator

Eight world champions in the card game bridge have been defeated by an artificial intelligence during a two-day tournament in Paris.

The announcement was made by French startup NukkAI which was co-founded in March 2018 by Véronique Ventos and Jean-Baptiste Fantun.

The Paris-based private lab chose the bridge as it is the game that has most similarities with real-life: the information is incomplete, there are partners and opponents and the rules impose some explainability.&nbsp;

<a href="https://www.wionews.com/science/breakthrough-in-physics-artificial-intelligence-successfully-controls-plasma-in-nuclear-fusion-experiment-455165">Also read |&nbsp;'Breakthrough in Physics': Artificial Intelligence successfully controls plasma in nuclear fusion experiment</a>

It had introduced the NukkAI challenge which required the human champions to play 800 consecutive deals divided into 80 sets of 10.

“This is something that humans do after enough experience and I was pleasantly surprised that a robot mimics typical human skills,” said Nevena Senior, a many-times world bridge champion for England and one of NooK’s challengers.

“What we’ve seen represents a fundamentally important advance in the state of artificial intelligence systems,” said Stephen Muggleton, a professor of machine learning at Imperial College London.

“Most of what the general public have heard in recent years about machine learning is based on black box systems such as AlphaGo, which is unable to explain to human beings how decisions are being made,” he added.

<a href="https://www.wionews.com/science/new-artificial-intelligence-model-shows-hidden-turbulence-in-suns-atmosphere-457528">Also read |&nbsp;New artificial intelligence model shows hidden turbulence in Sun's atmosphere</a>

“In bridge, you can’t play if you don’t explain,” said NukkAI’s other co-founder Véronique Ventos.

“The pendulum is swinging towards these kinds of methods,” says Michael Littman, a professor of computer science at Brown University in Rhode Island.&nbsp;

“Not being able to tell people what’s going on just doesn’t work in our societies.”

NukkAI aims to bring transparency to the Artificial Intelligence models, facilitate compliance, improve model performance and reduce ethical bias.

Their products include NuX, an interactive AI tool customised for each domain, proposes efficient solutions while providing explanations in natural language adapted to user’s profile.&nbsp;

It already been customised for different domains: aeronautics, education, cybersecurity, defence, etc. As NuX improves performance while responding to responsibility and transparency issues, this generic tool has potential in virtually all business verticals.

(With inputs from agencies)

Eight world champions in the card game bridge have been defeated by an artificial intelligence during a two-day tournament in Paris. The announcement was made by French startup NukkAI which was co-founded in March 2018 by Véronique Ventos and Jean-Baptiste Fantun.

Eight world champions in the card game bridge have been defeated by an artificial intelligence during a two-day tournament in Paris. The announcement was made by French startup NukkAI which was co-founded in March 2018 by Véronique Ventos and Jean-Baptiste Fantun. The Paris-based private lab chose the bridge as it is the game that has most similarities with real-life: the information is incomplete, there are partners and opponents and the rules impose some explainability. Also read | 'Breakthrough in Physics': Artificial Intelligence successfully controls plasma in nuclear fusion experiment It had introduced the NukkAI challenge which required the human champions to play 800 consecutive deals divided into 80 sets of 10. “This is something that humans do after enough experience and I was pleasantly surprised that a robot mimics typical human skills,” said Nevena Senior, a many-times world bridge champion for England and one of NooK’s challengers. “What we’ve seen represents a fundamentally important advance in the state of artificial intelligence systems,” said Stephen Muggleton, a professor of machine learning at Imperial College London. “Most of what the general public have heard in recent years about machine learning is based on black box systems such as AlphaGo, which is unable to explain to human beings how decisions are being made,” he added. Also read | New artificial intelligence model shows hidden turbulence in Sun's atmosphere “In bridge, you can’t play if you don’t explain,” said NukkAI’s other co-founder Véronique Ventos. “The pendulum is swinging towards these kinds of methods,” says Michael Littman, a professor of computer science at Brown University in Rhode Island. “Not being able to tell people what’s going on just doesn’t work in our societies.” NukkAI aims to bring transparency to the Artificial Intelligence models, facilitate compliance, improve model performance and reduce ethical bias. Their products include NuX, an interactive AI tool customised for each domain, proposes efficient solutions while providing explanations in natural language adapted to user’s profile. It already been customised for different domains: aeronautics, education, cybersecurity, defence, etc. As NuX improves performance while responding to responsibility and transparency issues, this generic tool has potential in virtually all business verticals. (With inputs from agencies)

Eight world champions at bridge defeated by artificial intelligence

Scientists have come up with Alexa for animals- Robots that can understand whale songs, and calls of over 3,000 bird species. Palki Sharma brings you a report.

Gravitas: What if you could understand the language of animals? AI can do that now

Have you ever wondered what if humans are able to communicate with animals and birds? With the help of the artificial intelligence (AI) algorithm, scientists recently revealed that they translated pig grunts into emotions for the first time. It could help them monitor animal wellbeing.&nbsp;

Experts have claimed that the research, which was led by the University of Copenhagen, the ETH Zurich and France's National Research Institute for Agriculture, Food and Environment (INRAE) could also be used to better understand the emotions of other mammals.&nbsp;

It looks like researchers are already working on it. As per a report published by The Wall Street Journal, it has been revealed that researchers are using AI to parse the "speech" of animals.&nbsp;

ALSO READ |&nbsp;<a href="https://www.wionews.com/world/turn-garbage-into-gold-uks-royal-mint-planning-to-extract-precious-metals-from-e-waste-464828">Turn garbage into gold: UK's Royal Mint planning to extract precious metals from e-waste</a>

The method will help scientists to create systems that decode animal sounds. For example, such algorithms might help to detect and monitor whale songs. So that the nearby ships can be alerted to avoid collisions.&nbsp;

As quoted by WSJ, Oren Etzioni, who is an AI researcher and head of the Allen Institute for AI, said, "It is fascinating that the tools of artificial intelligence, specifically deep learning, which is the hot new thing, do seem to be the natural tools to study this other kind of 'A.I.'—animal intelligence." Allen Institute for AI is a nonprofit, which was set up by the late Microsoft co-founder Paul Allen.&nbsp;

The report added that researchers on animal communication are using a branch of AI that "self-supervised learning". In recent years, self-supervised learning has proven effective for handling human language.&nbsp;

Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning. It is based on an artificial neural network.

ALSO READ |&nbsp;<a href="https://www.wionews.com/science/decoding-pigs-emotions-scientists-can-now-tell-if-the-animal-is-happy-or-sad-464604">Decoding emotions: Scientists can now tell if a pig is happy or sad</a>

As per the report, "self-supervised learning" shows promise as a way to process the immense quantities of recordings of animal communication, captured in laboratories as well as natural environments.&nbsp;

With constant advancements in technology, there's is no exaggeration in saying that such results, where humans will be able to communicate with animals,&nbsp;are achievable in near future.&nbsp;

We have seen certain examples, researchers at Cornell University and the Chemnitz University of Technology in Germany had developed an AI-based system, called BirdNET that can now recognise the calls of more than 3,000 different species of birds. &nbsp;

Have you ever wondered what if humans are able to communicate with animals and birds? With the help of the artificial intelligence (AI) algorithm, scientists recently revealed that they translated pig grunts into emotions for the first time.

Have you ever wondered what if humans are able to communicate with animals and birds? With the help of the artificial intelligence (AI) algorithm, scientists recently revealed that they translated pig grunts into emotions for the first time. It could help them monitor animal wellbeing. Experts have claimed that the research, which was led by the University of Copenhagen, the ETH Zurich and France's National Research Institute for Agriculture, Food and Environment (INRAE) could also be used to better understand the emotions of other mammals. It looks like researchers are already working on it. As per a report published by The Wall Street Journal, it has been revealed that researchers are using AI to parse the "speech" of animals. ALSO READ | Turn garbage into gold: UK's Royal Mint planning to extract precious metals from e-waste The method will help scientists to create systems that decode animal sounds. For example, such algorithms might help to detect and monitor whale songs. So that the nearby ships can be alerted to avoid collisions. As quoted by WSJ, Oren Etzioni, who is an AI researcher and head of the Allen Institute for AI, said, "It is fascinating that the tools of artificial intelligence, specifically deep learning, which is the hot new thing, do seem to be the natural tools to study this other kind of 'A.I.'—animal intelligence." Allen Institute for AI is a nonprofit, which was set up by the late Microsoft co-founder Paul Allen. The report added that researchers on animal communication are using a branch of AI that "self-supervised learning". In recent years, self-supervised learning has proven effective for handling human language. Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning. It is based on an artificial neural network. ALSO READ | Decoding emotions: Scientists can now tell if a pig is happy or sad As per the report, "self-supervised learning" shows promise as a way to process the immense quantities of recordings of animal communication, captured in laboratories as well as natural environments. With constant advancements in technology, there's is no exaggeration in saying that such results, where humans will be able to communicate with animals, are achievable in near future. We have seen certain examples, researchers at Cornell University and the Chemnitz University of Technology in Germany had developed an AI-based system, called BirdNET that can now recognise the calls of more than 3,000 different species of birds.

What do those meowing and neighing mean? Will artificial intelligence tell us how animals communicate?

A new model of artificial intelligence has shown hidden turbulence in the atmosphere of the Sun.

The research, published in Astronomy &amp; Astrophysics, shows multi-scale deep learning for estimating horizontal velocity fields on the solar surface.

The sun,&nbsp;essentially a hot ball of hydrogen and helium,&nbsp;is an average-sized star that formed more than 4.5 billion years ago and is roughly halfway through its lifespan.&nbsp;

Its diametre is about 864,000 miles (1.4 million km). Its surface temperature is about 10,000 degrees Fahrenheit (5,500 degrees Celsius).

Also see |&nbsp;<a href="https://www.wionews.com/photos/why-has-space-business-has-become-the-final-profitable-frontier-452928" hreflang="en">Why has space business has become the final profitable frontier?</a>

"We developed a novel convolutional neural network to estimate the spatial distribution of horizontal velocity by using the spatial distributions of temperature and vertical velocity," wrote a team of researchers led by astronomer Ryohtaroh Ishikawa of the National Astronomical Observatory of Japan.

"This led to efficient detection of spatially spread features and concentrated features. [..] Our network exhibited a higher performance on almost all the spatial scales when compared to those reported in previous studies."

Also read |&nbsp;<a href="https://www.wionews.com/science/astronomers-map-1-million-space-objects-that-have-never-been-spotted-before-456863" hreflang="en">Astronomers map 1 million space objects that have never been spotted before</a>

Elevated magnetic activity associated with sunspots can lead to solar flares, coronal mass ejections - large expulsions of plasma and magnetic field from the outermost part of the sun’s atmosphere - and other electromagnetic phenomena that can affect Earth, for example disrupting satellites and communications and endangering astronauts.

"By comparing the results of the three convection models, we observed that the rapid decrease in coherence spectrum occurred on the scales that were lower than the energy injection scales, which were characterized by the peaks of the power spectra of the vertical velocities. This implies that the network was not appropriately trained to reproduce the velocity fields in small scales generated by turbulent cascades," they wrote in their paper.

"These challenges can be explored in future studies."

The researchers compared data on similar stars to historical records of the sun’s activity. These records included about 400 years of observational data on sunspots and about 9,000 years of data based on chemical element variants in tree rings and ice cores caused by solar activity. These records indicated the sun has not been much more active than it is now. 
&nbsp;

(With inputs from agencies)

A new model of artificial intelligence has shown hidden turbulence in the atmosphere of the Sun. The research, published in Astronomy & Astrophysics, shows multi-scale deep learning for estimating horizontal velocity fields on the solar surface.

A new model of artificial intelligence has shown hidden turbulence in the atmosphere of the Sun. The research, published in Astronomy & Astrophysics, shows multi-scale deep learning for estimating horizontal velocity fields on the solar surface. The sun, essentially a hot ball of hydrogen and helium, is an average-sized star that formed more than 4.5 billion years ago and is roughly halfway through its lifespan. Its diametre is about 864,000 miles (1.4 million km). Its surface temperature is about 10,000 degrees Fahrenheit (5,500 degrees Celsius). Also see | Why has space business has become the final profitable frontier? "We developed a novel convolutional neural network to estimate the spatial distribution of horizontal velocity by using the spatial distributions of temperature and vertical velocity," wrote a team of researchers led by astronomer Ryohtaroh Ishikawa of the National Astronomical Observatory of Japan. "This led to efficient detection of spatially spread features and concentrated features. [..] Our network exhibited a higher performance on almost all the spatial scales when compared to those reported in previous studies." Also read | Astronomers map 1 million space objects that have never been spotted before Elevated magnetic activity associated with sunspots can lead to solar flares, coronal mass ejections - large expulsions of plasma and magnetic field from the outermost part of the sun’s atmosphere - and other electromagnetic phenomena that can affect Earth, for example disrupting satellites and communications and endangering astronauts. "By comparing the results of the three convection models, we observed that the rapid decrease in coherence spectrum occurred on the scales that were lower than the energy injection scales, which were characterized by the peaks of the power spectra of the vertical velocities. This implies that the network was not appropriately trained to reproduce the velocity fields in small scales generated by turbulent cascades," they wrote in their paper. "These challenges can be explored in future studies." The researchers compared data on similar stars to historical records of the sun’s activity. These records included about 400 years of observational data on sunspots and about 9,000 years of data based on chemical element variants in tree rings and ice cores caused by solar activity. These records indicated the sun has not been much more active than it is now. (With inputs from agencies)

New artificial intelligence model shows hidden turbulence in Sun's atmosphere

Scientists were successfully able to control plasma in nuclear fusion experiment by using artificial intelligence.

Nuclear fusion comes from the fusing of two atoms at very high temperatures, which then release energy.

In the study, published in Nature, scientists have recreated these extreme conditions is by using a tokamak, a doughnut-shaped vacuum surrounded by magnetic coils, that is used to contain a plasma of hydrogen that is hotter than the core of the Sun.&nbsp;

However, the plasmas in these machines are inherently unstable, making sustaining the process required for nuclear fusion a complex challenge.

For example, a control system needs to coordinate the tokamak's many magnetic coils and adjust the voltage on them thousands of times per second to ensure the plasma never touches the walls of the vessel, which would result in heat loss and possibly damage.&nbsp;

<a href="https://www.wionews.com/world/china-conducts-nuclear-fusion-experiment-for-artificial-sun-439314">Also read |&nbsp;China conducts nuclear fusion experiment for 'artificial sun'</a>

To help solve this problem and as part of DeepMind’s mission to advance science, researchers collaborated with the Swiss Plasma Centre at EPFL to develop the first deep reinforcement learning (RL) system to autonomously discover how to control these coils and successfully contain the plasma in a tokamak, opening new avenues to advance nuclear fusion research.

Using a learning architecture that combines deep RL and a simulated environment, they produced controllers that can both keep the plasma steady and be used to accurately sculpt it into different shapes.&nbsp;

This “plasma sculpting” shows the RL system has successfully controlled the superheated matter and - importantly - allows scientists to investigate how the plasma reacts under different conditions, improving our understanding of fusion reactors.

<div class="videoWrapper trancodeVideo"><iframe allowfullscreen="" autoplay="1" class="includeVideo" frameborder="0" height="350" src="https://www.wionews.com/videos/british-scientists-major-breakthrough-on-nuclear-fusion-energy-451933/embed" style="width:100%;max-width:560px;" width="560"></iframe></div>

"This AI is, in my opinion, the only way forward," said physicist Gianluca Sarri from Queen's University Belfast.

"There are so many variables, and a small change in one of them can cause a big change in the final output. If you try to do it manually, it's a very lengthy process."

Scientists have been working for decades to try to develop fusion energy as a viable power source.&nbsp;

Unlike the burning of fossil fuels or the fission process of existing nuclear power plants, fusion offers the prospect of abundant energy without pollution, radioactive waste, or greenhouse gases.

While nuclear fusion could revolutionise energy production, with pilot projects targeting energy output at 10 times the input, no fusion project has up to now created a net energy increase. Critics say commercially viable fusion always remains fifty years in the future.

(With inputs from agencies)&nbsp;

Scientists were successfully able to control plasma in nuclear fusion experiment by using artificial intelligence. Nuclear fusion comes from the fusing of two atoms at very high temperatures, which then release energy.

Scientists were successfully able to control plasma in nuclear fusion experiment by using artificial intelligence. Nuclear fusion comes from the fusing of two atoms at very high temperatures, which then release energy. In the study, published in Nature, scientists have recreated these extreme conditions is by using a tokamak, a doughnut-shaped vacuum surrounded by magnetic coils, that is used to contain a plasma of hydrogen that is hotter than the core of the Sun. However, the plasmas in these machines are inherently unstable, making sustaining the process required for nuclear fusion a complex challenge. For example, a control system needs to coordinate the tokamak's many magnetic coils and adjust the voltage on them thousands of times per second to ensure the plasma never touches the walls of the vessel, which would result in heat loss and possibly damage. Also read | China conducts nuclear fusion experiment for 'artificial sun' To help solve this problem and as part of DeepMind’s mission to advance science, researchers collaborated with the Swiss Plasma Centre at EPFL to develop the first deep reinforcement learning (RL) system to autonomously discover how to control these coils and successfully contain the plasma in a tokamak, opening new avenues to advance nuclear fusion research. Using a learning architecture that combines deep RL and a simulated environment, they produced controllers that can both keep the plasma steady and be used to accurately sculpt it into different shapes. This “plasma sculpting” shows the RL system has successfully controlled the superheated matter and - importantly - allows scientists to investigate how the plasma reacts under different conditions, improving our understanding of fusion reactors. "This AI is, in my opinion, the only way forward," said physicist Gianluca Sarri from Queen's University Belfast. "There are so many variables, and a small change in one of them can cause a big change in the final output. If you try to do it manually, it's a very lengthy process." Scientists have been working for decades to try to develop fusion energy as a viable power source. Unlike the burning of fossil fuels or the fission process of existing nuclear power plants, fusion offers the prospect of abundant energy without pollution, radioactive waste, or greenhouse gases. While nuclear fusion could revolutionise energy production, with pilot projects targeting energy output at 10 times the input, no fusion project has up to now created a net energy increase. Critics say commercially viable fusion always remains fifty years in the future. (With inputs from agencies)

'Breakthrough in Physics': Artificial Intelligence successfully controls plasma in nuclear fusion experiment

An AI-powered device has made it possible for paralysed patients to walk again. The prototype has been tested on 3 patients. All of them could take their steps within the first hour of implant. Palki Sharma brings you a report.

Gravitas Ukraine Direct: Device helps paralysed patients walk again

Researchers have artificial intelligence to create a ''treasure map'' that detects 30,000 meteorites hiding across Antarctica.

Published ''Universe Today,'' the study has been conducted by scientists from the Delft University of Technology in The Netherlands.

Meteorites provide a unique view into the origin and evolution of the Solar System.&nbsp;These extraterrestrial rocks fell on Earth after surviving the passage through the atmosphere. Being directly accessible at the Earth’s surface, meteorites provide important insight into nebular and planetary processes.&nbsp;

<div class="videoWrapper trancodeVideo"><iframe allowfullscreen="" autoplay="1" class="includeVideo" frameborder="0" height="350" src="https://www.wionews.com/videos/gravitas-a-mysterious-space-object-has-spooked-astronomers-448271/embed" style="width:100%;max-width:560px;" width="560"></iframe></div>

Antarctica is the most productive region for recovering meteorites, where these extraterrestrial rocks concentrate at meteorite stranding zones.&nbsp;

"Through our analyses, we learned that satellite observations of temperature, ice flow rate, surface cover and geometry are good predictors of the location of meteorite-rich areas," said Veronica Tollenaar, who led the study.

Also read |&nbsp;<a href="https://www.wionews.com/science/youngest-pair-of-asteroids-ever-discovered-in-solar-system-spotted-by-astronomers-451332" hreflang="en">Youngest pair of asteroids ever discovered in solar system spotted by astronomers</a>

"Antarctica is very remote and many areas have never been visited. We expect the 'treasure map' to be 80 percent accurate."&nbsp;

The analyses of the study suggests that less than 15 per cent of all meteorites at the surface of the Antarctic ice sheet have been recovered to date.

"We found several never-visited meteorite-rich areas that are relatively close to research stations," said Stef Lhermitte, who was involved in the study along with assistant professor David Tax from TU Delft.

<a href="https://www.wionews.com/science/is-there-life-on-mars-study-of-decades-old-meteorite-casts-doubt-on-presence-of-life-on-the-planet-444601">Also read |&nbsp;Is there life on Mars?: Study of decades-old meteorite casts doubt on presence of life on the planet</a>

"Moreover, the reports on the success of previous meteorite recovery missions are often ambiguous and not very detailed, which leads to a lack of good-quality labels. To circumvent this problem, we relied on 'positive and unlabeled learning', an emerging field in machine learning," Tollenaar said.

In 1996, NASA scientists presented research indicating a 4-billion-year-old meteorite found in Antarctica carried evidence of fossilized microbial life from Mars.

The initial discovery of the so-called Mars meteorite was greeted with acclaim and the rock unveiled at a standing room-only briefing at NASA headquarters in Washington.

Since then, however, criticism has surrounded that discovery, and the conclusive proof has been elusive.

(With inputs from agencies)

Researchers have artificial intelligence to create a ''treasure map'' that detects 30,000 meteorites hiding across Antarctica. Published ''Universe Today,'' the study has been conducted by scientists from the Delft University of Technology in The Netherlands.

Researchers have artificial intelligence to create a ''treasure map'' that detects 30,000 meteorites hiding across Antarctica. Published ''Universe Today,'' the study has been conducted by scientists from the Delft University of Technology in The Netherlands. Meteorites provide a unique view into the origin and evolution of the Solar System. These extraterrestrial rocks fell on Earth after surviving the passage through the atmosphere. Being directly accessible at the Earth’s surface, meteorites provide important insight into nebular and planetary processes. Antarctica is the most productive region for recovering meteorites, where these extraterrestrial rocks concentrate at meteorite stranding zones. "Through our analyses, we learned that satellite observations of temperature, ice flow rate, surface cover and geometry are good predictors of the location of meteorite-rich areas," said Veronica Tollenaar, who led the study. Also read | Youngest pair of asteroids ever discovered in solar system spotted by astronomers "Antarctica is very remote and many areas have never been visited. We expect the 'treasure map' to be 80 percent accurate." The analyses of the study suggests that less than 15 per cent of all meteorites at the surface of the Antarctic ice sheet have been recovered to date. "We found several never-visited meteorite-rich areas that are relatively close to research stations," said Stef Lhermitte, who was involved in the study along with assistant professor David Tax from TU Delft. Also read | Is there life on Mars?: Study of decades-old meteorite casts doubt on presence of life on the planet "Moreover, the reports on the success of previous meteorite recovery missions are often ambiguous and not very detailed, which leads to a lack of good-quality labels. To circumvent this problem, we relied on 'positive and unlabeled learning', an emerging field in machine learning," Tollenaar said. In 1996, NASA scientists presented research indicating a 4-billion-year-old meteorite found in Antarctica carried evidence of fossilized microbial life from Mars. The initial discovery of the so-called Mars meteorite was greeted with acclaim and the rock unveiled at a standing room-only briefing at NASA headquarters in Washington. Since then, however, criticism has surrounded that discovery, and the conclusive proof has been elusive. (With inputs from agencies)

30,000 meteorites are hiding across Antarctica as per this 'treasure map' created by artificial intelligence

A German research team has reportedly developed an artificial intelligence tool which can predict how a patient will react after being hospitalised based on a blood sample.

Reports claim the machine learning tool can accurately predict whether the person will survive or die based on levels of protein in a person's blood.

<a href="https://www.wionews.com/trending/couple-on-neverending-date-due-to-covid-lockdown-gets-engaged-446039">Also Read:&nbsp;Couple on never ending date due to Covid lockdown gets engaged</a>

It is meant to help health workers to understand whether a patient needs critical care or can fight the virus without much help. The prediction model detects 14 levels of protein in a patient before making a decision.

Researchers say they tested the tool on 50 patients at Charité University Hospital in Germany as it carried out machine learning. Reports say 15 patients died out of the 50 as researchers sought protein levels and built the tool based on findings from data of the patients.

<a href="https://www.wionews.com/world/french-education-minister-criticised-for-announcing-covid-19-measures-from-ibiza-trip-446017">Also Read:&nbsp;French minister criticised for announcing COVID-19 measures from Ibiza trip</a>

After the initial trial 24 coronavirus patients who had received treatment were also tested as researchers found 19 survived and five patients died. The researchers said the AI tool accurately predicted the five deaths.

The researchers however pointed out that the sample size was small consisting of 50 patients and 24 other patients during open trials.

The new findings come as Europe and America battle the Omicron the wave with hospitals overwhelmed in several areas. Several health workers have been hit due to the Omicron wave making it tough for hospitals to function.

(With inputs from Agencies)

A German research team has reportedly developed an artificial intelligence tool which can predict how a patient will react after being hospitalised based on a blood sample.

A German research team has reportedly developed an artificial intelligence tool which can predict how a patient will react after being hospitalised based on a blood sample. Reports claim the machine learning tool can accurately predict whether the person will survive or die based on levels of protein in a person's blood. Also Read: Couple on never ending date due to Covid lockdown gets engaged It is meant to help health workers to understand whether a patient needs critical care or can fight the virus without much help. The prediction model detects 14 levels of protein in a patient before making a decision. Researchers say they tested the tool on 50 patients at Charité University Hospital in Germany as it carried out machine learning. Reports say 15 patients died out of the 50 as researchers sought protein levels and built the tool based on findings from data of the patients. Also Read: French minister criticised for announcing COVID-19 measures from Ibiza trip After the initial trial 24 coronavirus patients who had received treatment were also tested as researchers found 19 survived and five patients died. The researchers said the AI tool accurately predicted the five deaths. The researchers however pointed out that the sample size was small consisting of 50 patients and 24 other patients during open trials. The new findings come as Europe and America battle the Omicron the wave with hospitals overwhelmed in several areas. Several health workers have been hit due to the Omicron wave making it tough for hospitals to function. (With inputs from Agencies)

Now, an AI tool can predict recovery time of COVID-19 patients

As artificial intelligence(AI) technology gathers momentum worldwide, reports claim China has developed an AI "prosecutor" which can charge people using the high-end technology.

According to Chinese researchers, the AI "prosecutor" can file charges against an accused with over 97 per cent accuracy based on verbal description.

The machine has reportedly been built by Shanghai Pudong People's Procuratorate. In a paper published by Chinese researchers, they&nbsp;said the AI technology can help lessen the workload of prosecutors and it has the ability to replace prosecutors in the decision-making process in&nbsp;some cases.

<a href="https://www.wionews.com/science/scientists-identify-new-pattern-in-mathematics-using-artificial-intelligence-434395">Also Read:&nbsp;Scientists identify new pattern in mathematics using artificial intelligence</a>

The new technology can reportedly be used on a desktop computer as it analyses billions of data stored in its system. The AI machine was reportedly trained using thousands of cases between 2015 to 2020. It can reportedly spot dangerous driving, credit card fraud, gambling operations including theft and fraud with upgrades likely to be put into the system by the researchers.

However, some prosecutors are wary about the new technology. They say the "AI prosecutor" could make a mistake in complicated cases. Also, the fact that it has been trained in previous cases would make it unreliable in new cases under ever changing social environment.

<a href="Humans may get to talk to whales, courtesy artificial intelligence">Also Read:&nbsp;Humans may get to talk to whales, courtesy artificial intelligence</a>

Recently, UK's MI-6 chief Richard Moore had said that, "Chinese intelligence services are highly capable and continue to conduct large scale espionage operations against the UK and our allies."

Moore had expressed concern over Chinese government's attempt to "distort public discourse" and "political decision-making across the globe"&nbsp;as he pointed out that&nbsp;&nbsp;"adversaries are pouring money and ambition into mastering&nbsp;artificial&nbsp;intelligence and&nbsp;quantum computing.

(With inputs from Agencies)

As artificial intelligence(AI) technology gathers momentum worldwide, reports claim China has developed an AI "prosecutor" which can charge people using the high-end technology.

As artificial intelligence(AI) technology gathers momentum worldwide, reports claim China has developed an AI "prosecutor" which can charge people using the high-end technology. According to Chinese researchers, the AI "prosecutor" can file charges against an accused with over 97 per cent accuracy based on verbal description. The machine has reportedly been built by Shanghai Pudong People's Procuratorate. In a paper published by Chinese researchers, they said the AI technology can help lessen the workload of prosecutors and it has the ability to replace prosecutors in the decision-making process in some cases. Also Read: Scientists identify new pattern in mathematics using artificial intelligence The new technology can reportedly be used on a desktop computer as it analyses billions of data stored in its system. The AI machine was reportedly trained using thousands of cases between 2015 to 2020. It can reportedly spot dangerous driving, credit card fraud, gambling operations including theft and fraud with upgrades likely to be put into the system by the researchers. However, some prosecutors are wary about the new technology. They say the "AI prosecutor" could make a mistake in complicated cases. Also, the fact that it has been trained in previous cases would make it unreliable in new cases under ever changing social environment. Also Read: Humans may get to talk to whales, courtesy artificial intelligence Recently, UK's MI-6 chief Richard Moore had said that, "Chinese intelligence services are highly capable and continue to conduct large scale espionage operations against the UK and our allies." Moore had expressed concern over Chinese government's attempt to "distort public discourse" and "political decision-making across the globe" as he pointed out that "adversaries are pouring money and ambition into mastering artificial intelligence and quantum computing. (With inputs from Agencies)

Now, China develops AI 'prosecutor'

It may have seemed like an obscure United Nations conclave, but a meeting this week in Geneva was followed intently by experts in artificial intelligence, military strategy, disarmament and humanitarian law.

The reason for the interest? Killer robots — drones, guns and bombs that decide on their own, with artificial brains, whether to attack and kill — and what should be done, if anything, to regulate or ban them.

Once the domain of science fiction films like the “Terminator” series and “RoboCop,” killer robots, more technically known as Lethal Autonomous Weapons Systems, have been invented and tested at an accelerated pace with little oversight. Some prototypes have even been used in actual conflicts.

The evolution of these machines is considered a potentially seismic event in warfare, akin to the invention of gunpowder and nuclear bombs.

This year, for the first time, a majority of the 125 nations that belong to an agreement called the Convention on Certain Conventional Weapons said they wanted curbs on killer robots. But they were opposed by members that are developing these weapons, most notably the United States and Russia.

The group’s conference concluded Friday with only a vague statement about considering possible measures acceptable to all. The Campaign to Stop Killer Robots, a disarmament group, said the outcome fell “drastically short.”

What is the Convention on Certain Conventional Weapons?

Sometimes known as the Inhumane Weapons Convention, it is a framework of rules that ban or restrict weapons considered to cause unnecessary, unjustifiable and indiscriminate suffering, such as incendiary explosives, blinding lasers and booby traps that don’t distinguish between fighters and civilians. The convention has no provisions for killer robots.

What exactly are killer robots?

Opinions differ on an exact definition, but they are widely considered to be weapons that make decisions with little or no human involvement. Rapid improvements in robotics, AI and image recognition are making such armaments possible.

The drones the United States has used extensively in Afghanistan, Iraq and elsewhere are not considered robots because they are operated remotely by people, who choose targets and decide whether to shoot.

Why are they considered attractive?

To war planners, the weapons offer the promise of keeping soldiers out of harm’s way, and making faster decisions than a human would, by giving more battlefield responsibilities to autonomous systems like pilotless drones and driverless tanks that independently decide when to strike.

What are the objections?

Critics argue it is morally repugnant to assign lethal decision making to machines, regardless of technological sophistication. How does a machine differentiate an adult from a child, a fighter with a bazooka from a civilian with a broom, a hostile combatant from a wounded or surrendering soldier?

“Fundamentally, autonomous weapon systems raise ethical concerns for society about substituting human decisions about life and death with sensor, software and machine processes,” Peter Maurer, president of the International Committee of the Red Cross and an outspoken opponent of killer robots, told the Geneva conference.

In advance of the conference, Human Rights Watch and Harvard Law School’s International Human Rights Clinic called for steps toward a legally binding agreement that requires human control at all times.

“Robots lack the compassion, empathy, mercy and judgment necessary to treat humans humanely, and they cannot understand the inherent worth of human life,” the groups argued in a briefing paper to support their recommendations.

Others said autonomous weapons, rather than reducing the risk of war, could do the opposite — by providing antagonists with ways of inflicting harm that minimize risks to their own soldiers.

“Mass-produced killer robots could lower the threshold for war by taking humans out of the kill chain and unleashing machines that could engage a human target without any human at the controls,” said Phil Twyford, New Zealand’s disarmament minister.

Why was the Geneva conference important?

The conference was widely considered by disarmament experts to be the best opportunity so far to devise ways to regulate, if not prohibit, the use of killer robots under the convention.

It was the culmination of years of discussions by a group of experts who had been asked to identify the challenges and possible approaches to reducing the threats from killer robots. But the experts could not even reach agreement on basic questions.

What do opponents of a new treaty say?

Some, like Russia, insist that any decisions on limits must be unanimous — in effect giving opponents a veto.

The United States argues that existing international laws are sufficient and that banning autonomous weapons technology would be premature. The chief U.S. delegate to the conference, Joshua Dorosin, proposed a nonbinding “code of conduct” for use of killer robots — an idea that disarmament advocates dismissed as a delaying tactic.

The U.S. military has invested heavily in AI, working with the biggest defense contractors, including Lockheed Martin, Boeing, Raytheon and Northrop Grumman. The work has included projects to develop long-range missiles that detect moving targets based on radio frequency, swarm drones that can identify and attack a target, and automated missile defense systems, according to research by opponents of the weapons systems.

The complexity and varying uses of AI make it more difficult to regulate than nuclear weapons or land mines, said Maaike Verbruggen, an expert on emerging military security technology at the Center for Security, Diplomacy and Strategy in Brussels. She said lack of transparency about what different countries are building has created “fear and concern” among military leaders that they must keep up.

“It’s very hard to get a sense of what another country is doing,” said Verbruggen, who is working toward a doctorate on the topic. “There is a lot of uncertainty and that drives military innovation.”

Franz-Stefan Gady, a research fellow at the International Institute for Strategic Studies, said the “arms race for autonomous weapons systems is already underway and won’t be called off anytime soon.”

Is there conflict in the defense establishment about killer robots?

Yes. Even as the technology becomes more advanced, there has been reluctance to use autonomous weapons in combat because of fears of mistakes, Gady said.

“Can military commanders trust the judgment of autonomous weapon systems? Here the answer at the moment is clearly ‘no’ and will remain so for the near future,” he said.

The debate over autonomous weapons has spilled into Silicon Valley. In 2018, Google said it would not renew a contract with the Pentagon after thousands of its employees signed a letter protesting the company’s work on a program using AI to interpret images that could be used to choose drone targets. The company also created new ethical guidelines prohibiting the use of its technology for weapons and surveillance.

Others believe the United States is not going far enough to compete with rivals.

In October, the former chief software officer for the Air Force, Nicolas Chaillan, told the Financial Times that he had resigned because of what he saw as weak technological progress inside the U.S. military, particularly the use of AI. He said policymakers are slowed down by questions about ethics, while countries like China press ahead.

Where have autonomous weapons been used?

There are not many verified battlefield examples, but critics point to a few incidents that show the technology’s potential.

In March, U.N. investigators said a “lethal autonomous weapons system” had been used by government-backed forces in Libya against militia fighters. A drone called Kargu-2, made by a Turkish defense contractor, tracked and attacked the fighters as they fled a rocket attack, according to the report, which left unclear whether any human controlled the drones.

In the 2020 war in Nagorno-Karabakh, Azerbaijan fought Armenia with attack drones and missiles that loiter in the air until detecting the signal of an assigned target.

What happens now?

Many disarmament advocates said the outcome of the conference had hardened what they described as a resolve to push for a new treaty in the next few years, like those that prohibit land mines and cluster munitions.

Daan Kayser, an autonomous weapons expert at PAX, a Netherlands-based peace advocacy group, said the conference’s failure to agree to even negotiate on killer robots was “a really plain signal that the CCW isn’t up to the job.”

Noel Sharkey, an AI expert and chair of the International Committee for Robot Arms Control, said the meeting had demonstrated that a new treaty was preferable to further convention deliberations.

“There was a sense of urgency in the room,” he said, that “if there’s no movement, we’re not prepared to stay on this treadmill.”

It may have seemed like an obscure United Nations conclave, but a meeting this week in Geneva was followed intently by experts in artificial intelligence, military strategy, disarmament and humanitarian law.

It may have seemed like an obscure United Nations conclave, but a meeting this week in Geneva was followed intently by experts in artificial intelligence, military strategy, disarmament and humanitarian law. The reason for the interest? Killer robots — drones, guns and bombs that decide on their own, with artificial brains, whether to attack and kill — and what should be done, if anything, to regulate or ban them. Once the domain of science fiction films like the “Terminator” series and “RoboCop,” killer robots, more technically known as Lethal Autonomous Weapons Systems, have been invented and tested at an accelerated pace with little oversight. Some prototypes have even been used in actual conflicts. The evolution of these machines is considered a potentially seismic event in warfare, akin to the invention of gunpowder and nuclear bombs. This year, for the first time, a majority of the 125 nations that belong to an agreement called the Convention on Certain Conventional Weapons said they wanted curbs on killer robots. But they were opposed by members that are developing these weapons, most notably the United States and Russia. The group’s conference concluded Friday with only a vague statement about considering possible measures acceptable to all. The Campaign to Stop Killer Robots, a disarmament group, said the outcome fell “drastically short.” What is the Convention on Certain Conventional Weapons? Sometimes known as the Inhumane Weapons Convention, it is a framework of rules that ban or restrict weapons considered to cause unnecessary, unjustifiable and indiscriminate suffering, such as incendiary explosives, blinding lasers and booby traps that don’t distinguish between fighters and civilians. The convention has no provisions for killer robots. What exactly are killer robots? Opinions differ on an exact definition, but they are widely considered to be weapons that make decisions with little or no human involvement. Rapid improvements in robotics, AI and image recognition are making such armaments possible. The drones the United States has used extensively in Afghanistan, Iraq and elsewhere are not considered robots because they are operated remotely by people, who choose targets and decide whether to shoot. Why are they considered attractive? To war planners, the weapons offer the promise of keeping soldiers out of harm’s way, and making faster decisions than a human would, by giving more battlefield responsibilities to autonomous systems like pilotless drones and driverless tanks that independently decide when to strike. What are the objections? Critics argue it is morally repugnant to assign lethal decision making to machines, regardless of technological sophistication. How does a machine differentiate an adult from a child, a fighter with a bazooka from a civilian with a broom, a hostile combatant from a wounded or surrendering soldier? “Fundamentally, autonomous weapon systems raise ethical concerns for society about substituting human decisions about life and death with sensor, software and machine processes,” Peter Maurer, president of the International Committee of the Red Cross and an outspoken opponent of killer robots, told the Geneva conference. In advance of the conference, Human Rights Watch and Harvard Law School’s International Human Rights Clinic called for steps toward a legally binding agreement that requires human control at all times. “Robots lack the compassion, empathy, mercy and judgment necessary to treat humans humanely, and they cannot understand the inherent worth of human life,” the groups argued in a briefing paper to support their recommendations. Others said autonomous weapons, rather than reducing the risk of war, could do the opposite — by providing antagonists with ways of inflicting harm that minimize risks to their own soldiers. “Mass-produced killer robots could lower the threshold for war by taking humans out of the kill chain and unleashing machines that could engage a human target without any human at the controls,” said Phil Twyford, New Zealand’s disarmament minister. Why was the Geneva conference important? The conference was widely considered by disarmament experts to be the best opportunity so far to devise ways to regulate, if not prohibit, the use of killer robots under the convention. It was the culmination of years of discussions by a group of experts who had been asked to identify the challenges and possible approaches to reducing the threats from killer robots. But the experts could not even reach agreement on basic questions. What do opponents of a new treaty say? Some, like Russia, insist that any decisions on limits must be unanimous — in effect giving opponents a veto. The United States argues that existing international laws are sufficient and that banning autonomous weapons technology would be premature. The chief U.S. delegate to the conference, Joshua Dorosin, proposed a nonbinding “code of conduct” for use of killer robots — an idea that disarmament advocates dismissed as a delaying tactic. The U.S. military has invested heavily in AI, working with the biggest defense contractors, including Lockheed Martin, Boeing, Raytheon and Northrop Grumman. The work has included projects to develop long-range missiles that detect moving targets based on radio frequency, swarm drones that can identify and attack a target, and automated missile defense systems, according to research by opponents of the weapons systems. The complexity and varying uses of AI make it more difficult to regulate than nuclear weapons or land mines, said Maaike Verbruggen, an expert on emerging military security technology at the Center for Security, Diplomacy and Strategy in Brussels. She said lack of transparency about what different countries are building has created “fear and concern” among military leaders that they must keep up. “It’s very hard to get a sense of what another country is doing,” said Verbruggen, who is working toward a doctorate on the topic. “There is a lot of uncertainty and that drives military innovation.” Franz-Stefan Gady, a research fellow at the International Institute for Strategic Studies, said the “arms race for autonomous weapons systems is already underway and won’t be called off anytime soon.” Is there conflict in the defense establishment about killer robots? Yes. Even as the technology becomes more advanced, there has been reluctance to use autonomous weapons in combat because of fears of mistakes, Gady said. “Can military commanders trust the judgment of autonomous weapon systems? Here the answer at the moment is clearly ‘no’ and will remain so for the near future,” he said. The debate over autonomous weapons has spilled into Silicon Valley. In 2018, Google said it would not renew a contract with the Pentagon after thousands of its employees signed a letter protesting the company’s work on a program using AI to interpret images that could be used to choose drone targets. The company also created new ethical guidelines prohibiting the use of its technology for weapons and surveillance. Others believe the United States is not going far enough to compete with rivals. In October, the former chief software officer for the Air Force, Nicolas Chaillan, told the Financial Times that he had resigned because of what he saw as weak technological progress inside the U.S. military, particularly the use of AI. He said policymakers are slowed down by questions about ethics, while countries like China press ahead. Where have autonomous weapons been used? There are not many verified battlefield examples, but critics point to a few incidents that show the technology’s potential. In March, U.N. investigators said a “lethal autonomous weapons system” had been used by government-backed forces in Libya against militia fighters. A drone called Kargu-2, made by a Turkish defense contractor, tracked and attacked the fighters as they fled a rocket attack, according to the report, which left unclear whether any human controlled the drones. In the 2020 war in Nagorno-Karabakh, Azerbaijan fought Armenia with attack drones and missiles that loiter in the air until detecting the signal of an assigned target. What happens now? Many disarmament advocates said the outcome of the conference had hardened what they described as a resolve to push for a new treaty in the next few years, like those that prohibit land mines and cluster munitions. Daan Kayser, an autonomous weapons expert at PAX, a Netherlands-based peace advocacy group, said the conference’s failure to agree to even negotiate on killer robots was “a really plain signal that the CCW isn’t up to the job.” Noel Sharkey, an AI expert and chair of the International Committee for Robot Arms Control, said the meeting had demonstrated that a new treaty was preferable to further convention deliberations. “There was a sense of urgency in the room,” he said, that “if there’s no movement, we’re not prepared to stay on this treadmill.”

Killer robots aren’t science fiction. A push to ban them is growing.

Reports say South Korea is set to begin a pilot project to use facial recognition in CCTV cameras to track people infected with coronavirus.

The move comes amid privacy concerns with the system using artificial intelligence algorithms. The technology will track people who had come in contact with people infected with the virus including tracking people who wear masks.

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The country already has a sophisticated COVID-19 tracking system. An official said it will make the tracking system faster. The technology can reportedly track up to ten people.

South Korea's health body asserted that the technology should be used only to track those infected by the disease.

<a href="https://www.wionews.com/world/to-safeguard-lone-women-uk-looks-for-walk-me-home-phone-tracker-419503">Also Read:&nbsp;To safeguard lone women, UK looks for 'walk me home' phone-tracker</a>

Other countries have also experimented with the facial recognition system amid the pandemic.&nbsp;&nbsp;

The Israeli government had earlier started the tracking system which was designed by its intelligence service to locate people hit with the virus.

The Israeli system was started by the previous government headed by Benjamin Netanyahu. The Naftali Bennett government had restarted the programme after the Omicron variant was detected in the country.

However, after running it for a while the controversial system was stopped after the Israeli government said it was set to run it for a brief period. The government added that the tracking system would be reintroduced if the morbidity increases.

(With inputs from Agencies)

Reports say South Korea is set to begin a pilot project to use facial recognition in CCTV cameras to track people infected with coronavirus. The move comes amid privacy concerns with the system using artificial intelligence algorithms.

Reports say South Korea is set to begin a pilot project to use facial recognition in CCTV cameras to track people infected with coronavirus. The move comes amid privacy concerns with the system using artificial intelligence algorithms. The technology will track people who had come in contact with people infected with the virus including tracking people who wear masks. Also Read| Coronavirus mutation tracker: New strain leading to chaos and confusion across the globe The country already has a sophisticated COVID-19 tracking system. An official said it will make the tracking system faster. The technology can reportedly track up to ten people. South Korea's health body asserted that the technology should be used only to track those infected by the disease. Also Read: To safeguard lone women, UK looks for 'walk me home' phone-tracker Other countries have also experimented with the facial recognition system amid the pandemic. The Israeli government had earlier started the tracking system which was designed by its intelligence service to locate people hit with the virus. The Israeli system was started by the previous government headed by Benjamin Netanyahu. The Naftali Bennett government had restarted the programme after the Omicron variant was detected in the country. However, after running it for a while the controversial system was stopped after the Israeli government said it was set to run it for a brief period. The government added that the tracking system would be reintroduced if the morbidity increases. (With inputs from Agencies)

Now, South Korea to test facial recognition tech to track Covid-19 cases

Scientists have identified patterns in mathematics that have never been seen before.&nbsp;

The discovery, made by the use of artificial intelligence, can help to develop fundamentally new problem-solving techniques.

The study, conducted by the University of Sydney, has been published in Nature.

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According to its co-author, Geordie Williamson, ''Problems in mathematics are widely regarded as some of the most intellectually challenging problems out there.''

“While mathematicians have used machine learning to assist in the analysis of complex data sets, this is the first time we have used computers to help us formulate conjectures or suggest possible lines of attack for unproven ideas in mathematics.”

Going forward artificial intelligence will be more and more critical to reduce workload and save time.

It is also making a wide range of industrial processes more efficient, from cement production to cooling data centres.

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“Working to prove or disprove longstanding conjectures in my field involves the consideration of, at times, infinite space and hugely complex sets of equations across multiple dimensions,” Professor Williamson said.

While computers have long been used to generate data for experimental mathematics, the task of identifying interesting patterns has relied mainly on the intuition of the mathematicians themselves. But that has changed now.

“We have demonstrated that, when guided by mathematical intuition, machine learning provides a powerful framework that can uncover interesting and provable conjectures in areas where a large amount of data is available, or where the objects are too large to study with classical methods," said co-author András Juhász, from the University of Oxford.

Williamson said: “AI is an extraordinary tool. This work is one of the first times it has demonstrated its usefulness for pure mathematicians, like me.”

“Intuition can take us a long way, but AI can help us find connections the human mind might not always easily spot.”

(With inputs from agencies)

Scientists have identified patterns in mathematics that have never been seen before. The discovery, made by the use of artificial intelligence, can help to develop fundamentally new problem-solving techniques.

Scientists have identified patterns in mathematics that have never been seen before. The discovery, made by the use of artificial intelligence, can help to develop fundamentally new problem-solving techniques. The study, conducted by the University of Sydney, has been published in Nature. Also read | Elon Musk announces humanoid robot Tesla Bot that uses artificial intelligence According to its co-author, Geordie Williamson, ''Problems in mathematics are widely regarded as some of the most intellectually challenging problems out there.'' “While mathematicians have used machine learning to assist in the analysis of complex data sets, this is the first time we have used computers to help us formulate conjectures or suggest possible lines of attack for unproven ideas in mathematics.” Going forward artificial intelligence will be more and more critical to reduce workload and save time. It is also making a wide range of industrial processes more efficient, from cement production to cooling data centres. Also read | This Taiwanese teacher uses porn site to teach calculus, earns $250,000 per year “Working to prove or disprove longstanding conjectures in my field involves the consideration of, at times, infinite space and hugely complex sets of equations across multiple dimensions,” Professor Williamson said. While computers have long been used to generate data for experimental mathematics, the task of identifying interesting patterns has relied mainly on the intuition of the mathematicians themselves. But that has changed now. “We have demonstrated that, when guided by mathematical intuition, machine learning provides a powerful framework that can uncover interesting and provable conjectures in areas where a large amount of data is available, or where the objects are too large to study with classical methods," said co-author András Juhász, from the University of Oxford. Williamson said: “AI is an extraordinary tool. This work is one of the first times it has demonstrated its usefulness for pure mathematicians, like me.” “Intuition can take us a long way, but AI can help us find connections the human mind might not always easily spot.” (With inputs from agencies)

Scientists identify new pattern in mathematics using artificial intelligence

China and Russia, according to the head of Britain's foreign spy agency, are accelerating their efforts to master artificial intelligence and this might transform geopolitics over the next decade.

Extracts from the speech, released by the British government in advance, suggest that Richard Moore, the chief of the Secret Intelligence Service known as MI6, will talk about quantum engineering, engineered&nbsp;biology, and advances in computer power, and how they present a threat that needs to be addressed by the West.

Global spies, from Langley and London to Moscow and Beijing, struggle with technological advances that are challenging the traditional human-led spying operations of the past.

Also read |&nbsp;<a href="https://www.wionews.com/world/we-are-not-as-advanced-as-the-chinese-or-the-russians-us-space-force-general-on-hypersonic-missiles-431026">We are not as advanced as the Chinese or the Russians: US space force general on hypersonic missiles</a>

"Our adversaries are pouring money and ambition into mastering artificial intelligence, quantum computing and synthetic biology, because they know that mastering these technologies will give them leverage," Moore, who rarely surfaces for speeches, will say on Tuesday.

According to Moore, who became MI6 chief in 2020, technological progress over the next decade will outpace every technological advance made in the last century.

"As a society, we have yet to internalise this stark fact and its potential impact on global geopolitics. But it is a white-hot focus for MI6," he said.

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The Russian and Chinese intelligence agencies, which have harnessed a wide range of sophisticated technologies at a faster rate than Western intelligence agencies, are of particular concern to the West's spies.

The West is concerned that Beijing will dominate all emerging technologies within decades, including artificial intelligence, synthetic biology, and genetics.

Along with the fall of the Soviet Union in 1991 which ended the Cold War, the rise of China's economy and military over the past 40 years is considered one of the most significant geopolitical events of the 21st century.

MI6, which has been portrayed by novelists as the employer of some of the most memorable fictional spies, from John le Carré's George Smiley to Ian Fleming's James Bond, operates overseas and is responsible for defending the United Kingdom, &amp; its interests.

Adapting to new technology will require a change in the service, Moore said.

"We cannot hope to replicate the global tech industry, so we must tap into it," he will say. "We must become more open, to stay secret."

China and Russia, according to the head of Britain's foreign spy agency, are accelerating their efforts to master artificial intelligence and this might transform geopolitics over the next decade.

China and Russia, according to the head of Britain's foreign spy agency, are accelerating their efforts to master artificial intelligence and this might transform geopolitics over the next decade. Extracts from the speech, released by the British government in advance, suggest that Richard Moore, the chief of the Secret Intelligence Service known as MI6, will talk about quantum engineering, engineered biology, and advances in computer power, and how they present a threat that needs to be addressed by the West. Global spies, from Langley and London to Moscow and Beijing, struggle with technological advances that are challenging the traditional human-led spying operations of the past. Also read | We are not as advanced as the Chinese or the Russians: US space force general on hypersonic missiles "Our adversaries are pouring money and ambition into mastering artificial intelligence, quantum computing and synthetic biology, because they know that mastering these technologies will give them leverage," Moore, who rarely surfaces for speeches, will say on Tuesday. According to Moore, who became MI6 chief in 2020, technological progress over the next decade will outpace every technological advance made in the last century. "As a society, we have yet to internalise this stark fact and its potential impact on global geopolitics. But it is a white-hot focus for MI6," he said. Also read | What will the world be like in 20 years? The Russian and Chinese intelligence agencies, which have harnessed a wide range of sophisticated technologies at a faster rate than Western intelligence agencies, are of particular concern to the West's spies. The West is concerned that Beijing will dominate all emerging technologies within decades, including artificial intelligence, synthetic biology, and genetics. Along with the fall of the Soviet Union in 1991 which ended the Cold War, the rise of China's economy and military over the past 40 years is considered one of the most significant geopolitical events of the 21st century. MI6, which has been portrayed by novelists as the employer of some of the most memorable fictional spies, from John le Carré's George Smiley to Ian Fleming's James Bond, operates overseas and is responsible for defending the United Kingdom, & its interests. Adapting to new technology will require a change in the service, Moore said. "We cannot hope to replicate the global tech industry, so we must tap into it," he will say. "We must become more open, to stay secret."

UK spy chief warns that Russian, Chinese race for AI mastery might change geopolitics

Scientists have discovered a new lie detector that can read facial muscles that people won't even know they are using.

The study, conducted by the researchers at Tel Aviv University, has been in 'Brain and Behaviour.'

It was conducted on the basis of micro-expressions that vanish in 40 to 60 milliseconds due to which accuracy and speed played a key role.

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According to behavioral neuroscientist Dino Levy, ''it's not perfect, but much better than any existing [facial recognition] technology.''

''Since this was an initial study, the lie itself was very simple,'' he added.

Researchers tested the give-away indicators on 48 participants during which people had tells such twitching of eyebrows or cheek muscles.

''We successfully detected lies in all the participants and did so significantly better than untrained human detectors,'' explains Levy.

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''Interestingly, individuals who were able to successfully deceive their human counterparts were also poorly detected by the machine-learning algorithm,'' he added.

The lie detector was driven by artificial intelligence and hopes to bring more transparency. It can also be used to ramp up border security.

Researchers believe it could make its way into the private sector, for example, to screen insurance claims or job applicants.

They usually face criticism from human rights groups that question the technology’s ability to accurately assess people’s intentions and its potential for discrimination. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;

(With inputs from agencies)

Scientists have discovered a new lie detector that can read facial muscles that people won't even know they are using. The study, conducted by the researchers at Tel Aviv University, has been in 'Brain and Behaviour.

Scientists have discovered a new lie detector that can read facial muscles that people won't even know they are using. The study, conducted by the researchers at Tel Aviv University, has been in 'Brain and Behaviour.' It was conducted on the basis of micro-expressions that vanish in 40 to 60 milliseconds due to which accuracy and speed played a key role. Also read | Experts look to recycle dangerous space junk into rocket fuel in Earth's orbit According to behavioral neuroscientist Dino Levy, ''it's not perfect, but much better than any existing [facial recognition] technology.'' ''Since this was an initial study, the lie itself was very simple,'' he added. Researchers tested the give-away indicators on 48 participants during which people had tells such twitching of eyebrows or cheek muscles. ''We successfully detected lies in all the participants and did so significantly better than untrained human detectors,'' explains Levy. Also read | Facebook advertisers promoted false claims about climate change during COP26 summit ''Interestingly, individuals who were able to successfully deceive their human counterparts were also poorly detected by the machine-learning algorithm,'' he added. The lie detector was driven by artificial intelligence and hopes to bring more transparency. It can also be used to ramp up border security. Researchers believe it could make its way into the private sector, for example, to screen insurance claims or job applicants. They usually face criticism from human rights groups that question the technology’s ability to accurately assess people’s intentions and its potential for discrimination. (With inputs from agencies)

Scientists discover lie detector that uses artificial intelligence to detect micro-expressions

With the goal of 'talking' to the majestic marine animals, a project to listen to, contextualise and translate the communication of Sperm whales was recently launched by a team of international scientists. &nbsp;

Called Project CETI (Cetacean Translation Initiative), the initiative looks to harness the power of artificial intelligence to interpret clicking sounds, or 'codas,' which these whales make to communicate with one another. &nbsp;

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The researchers have been using natural language processing or NLP, a subfield of artificial intelligence focused on processing written and spoken human language. It will be trained in four billion Sperm whale codas. &nbsp;

According to the researchers, the plan is to have the AI correlate each sound with a specific context. This feat will take at least five years. &nbsp;&nbsp;

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If the team achieves these goals, the next step would be to develop and deploy an interactive chatbot, which engages in dialogue with Sperm whales living in the wild. &nbsp;

Michael Bronstein, lead, machine learning for Project CETI, told Hakai, "If we discover that there is an entire civilisation basically under our nose — maybe it will result in some shift in the way that we treat our environment. And maybe it will result in more respect for the living world." &nbsp;

(With inputs from agencies)&nbsp;

With the goal of 'talking' to the majestic marine animals, a project to listen to, contextualise and translate the communication of Sperm whales was recently launched by a team of international scientists.

With the goal of 'talking' to the majestic marine animals, a project to listen to, contextualise and translate the communication of Sperm whales was recently launched by a team of international scientists. Called Project CETI (Cetacean Translation Initiative), the initiative looks to harness the power of artificial intelligence to interpret clicking sounds, or 'codas,' which these whales make to communicate with one another. Also Read: Why is mysterious dark energy leading to expansion of the universe? The researchers have been using natural language processing or NLP, a subfield of artificial intelligence focused on processing written and spoken human language. It will be trained in four billion Sperm whale codas. According to the researchers, the plan is to have the AI correlate each sound with a specific context. This feat will take at least five years. Also Read: During Halloween weekend, solar flare helps northern lights become visible to US If the team achieves these goals, the next step would be to develop and deploy an interactive chatbot, which engages in dialogue with Sperm whales living in the wild. Michael Bronstein, lead, machine learning for Project CETI, told Hakai, "If we discover that there is an entire civilisation basically under our nose — maybe it will result in some shift in the way that we treat our environment. And maybe it will result in more respect for the living world." (With inputs from agencies)

Humans may get to talk to whales, courtesy artificial intelligence

Artificial Intelligence is linking violence and terrorism to the word 'Muslim'. How did technology learn these toxic stereotypes? Can artificial intelligence be made politically correct? Palki Shara tells you.

Gravitas: Artificial Intelligence is racist and islamophobic

Machines rule our lives even today. Use of Artificial Intelligence (AI) is increasing and it itself is becoming more intelligent. People have become addicted to machines and machines are studying poetry and painting.

Claims of takover by the machines have been made before. Years like 1984 have come and gone but the calamity seems far away. However, such situations appear more and more conceivable with every advancement in tech.

Now, an ex-Kremlin mastermind Vladislav Surkov has predicted that next 100 years will see advent of 'humanless democracies'. Machines will control everything and humans will increasingly get relegated to sidelines.

Surkov's significance in Russian politics can be gauged by the fact that he was assistant to Russian President Vladimir Putin himself till 2020.

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In his piece written for the publication publication ‘Actual Comment', Surkov says that in next 100 years, internet will take a form of direct democracy. There will no longer be a need to elect a government. Instead, anyone who wants to can vote on a proposed legislation.

“For example, if you need another law on beekeeping, everyone who cares – beekeepers, honey enthusiasts, beauticians, pharmacists, people who have been stung by bees, people with allergies, lawyers, hive and smokehouse manufacturers, beeophiles and bee-haters, as well as those who always care about everything – can all directly participate in its drafting, introduction, discussion and adoption,” says Surkov as quoted by Russia Today.

There is no parliament in this scheme. In its place are communication tools, algorithms and moderators.”

Surkov paints a scary picture saying that people will be slowly removed from such a process and that machines will eliminate the human factor. He says that humans will have more and more comfort but will have less and less say in how things are run.&nbsp;

Machines rule our lives even today. Use of Artificial Intelligence (AI) is increasing and it itself is becoming more intelligent. People have become addicted to machines and machines are studying poetry and painting.

Machines rule our lives even today. Use of Artificial Intelligence (AI) is increasing and it itself is becoming more intelligent. People have become addicted to machines and machines are studying poetry and painting. Claims of takover by the machines have been made before. Years like 1984 have come and gone but the calamity seems far away. However, such situations appear more and more conceivable with every advancement in tech. Now, an ex-Kremlin mastermind Vladislav Surkov has predicted that next 100 years will see advent of 'humanless democracies'. Machines will control everything and humans will increasingly get relegated to sidelines. Surkov's significance in Russian politics can be gauged by the fact that he was assistant to Russian President Vladimir Putin himself till 2020. Also Read | Scientists catch unexpected radio signals from distant stars In his piece written for the publication publication ‘Actual Comment', Surkov says that in next 100 years, internet will take a form of direct democracy. There will no longer be a need to elect a government. Instead, anyone who wants to can vote on a proposed legislation. “For example, if you need another law on beekeeping, everyone who cares – beekeepers, honey enthusiasts, beauticians, pharmacists, people who have been stung by bees, people with allergies, lawyers, hive and smokehouse manufacturers, beeophiles and bee-haters, as well as those who always care about everything – can all directly participate in its drafting, introduction, discussion and adoption,” says Surkov as quoted by Russia Today. There is no parliament in this scheme. In its place are communication tools, algorithms and moderators.” Surkov paints a scary picture saying that people will be slowly removed from such a process and that machines will eliminate the human factor. He says that humans will have more and more comfort but will have less and less say in how things are run.

Scary! Ex-Kremlin mastermind predicts formation of 'humanless democracies'

As the US and China compete for technological advantage, Pentagon's former chief software officer&nbsp;Nicolas Chaillan has declared that the US has "no competing fighting chance against China in 15 to 20 years" over artificial intelligence.

"It's already a done deal," Chaillan&nbsp;told the Financial Times newspaper.&nbsp;Chaillan maintained that the US has no chance of competing with China over artificial intelligence, in fact, he added that "it is already over".

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Chaillan warned that China was heading towards "global dominance" due to enhanced artificial intelligence capabilities including in machine learning.

Chaillan contented that new technology was far more critical than America's quest for F-35 fighter jet while adding that some of US cyber defenses were at “kindergarten level”.&nbsp;

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The former Pentagon chief software officer also hit out at Google's defiance to work with the US government on artificial intelligence comparing it to China where companies work with the government and have been making “massive investment into AI without regard to ethics."

Chaillan reportedly told the newspaper that he plans to testify before US lawmakers about China's cyber threat.

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Last month the US had announced it was establishing a committee named National Artificial Intelligence Advisory Committee (NAIAC) to advise President Joe Biden and other agencies on AI.

US Secretary of Commerce Gina Raimondo had said AI can help to address various issues including strengthen "technological competitiveness". The US committee on AI is set to include people from the industry, &nbsp;academia and non-profit institutions.

(With inputs from Agencies)

As the US and China compete for technological advantage, Pentagon's former chief software officer Nicolas Chaillan has declared that the US has "no competing fighting chance against China in 15 to 20 years" over artificial intelligence.

As the US and China compete for technological advantage, Pentagon's former chief software officer Nicolas Chaillan has declared that the US has "no competing fighting chance against China in 15 to 20 years" over artificial intelligence. "It's already a done deal," Chaillan told the Financial Times newspaper. Chaillan maintained that the US has no chance of competing with China over artificial intelligence, in fact, he added that "it is already over". Also Read | China aims to build a fully modern military on par with the United States by 2027 Chaillan warned that China was heading towards "global dominance" due to enhanced artificial intelligence capabilities including in machine learning. Chaillan contented that new technology was far more critical than America's quest for F-35 fighter jet while adding that some of US cyber defenses were at “kindergarten level”. Also Read | Chinese artificial intelligence company files $1.4 billion lawsuit against Apple The former Pentagon chief software officer also hit out at Google's defiance to work with the US government on artificial intelligence comparing it to China where companies work with the government and have been making “massive investment into AI without regard to ethics." Chaillan reportedly told the newspaper that he plans to testify before US lawmakers about China's cyber threat. Also Read: Elon Musk announces humanoid robot Tesla Bot that uses artificial intelligence Last month the US had announced it was establishing a committee named National Artificial Intelligence Advisory Committee (NAIAC) to advise President Joe Biden and other agencies on AI. US Secretary of Commerce Gina Raimondo had said AI can help to address various issues including strengthen "technological competitiveness". The US committee on AI is set to include people from the industry, academia and non-profit institutions. (With inputs from Agencies)

'It is already over': Ex-Pentagon software chief claims US has lost AI battle against China

Artificial intelligence technology has completed Beethoven's previously incomplete Tenth Symphony.

Next month, 194 years after the composer's death, the work will be performed for the first time in Germany.

Ludwig van Beethoven's final orchestral composition, Symphony No. 9 in D minor, was debuted in 1824.

&nbsp;In the latter years of his life, Beethoven began work on what would have been his tenth symphony.

However, due to ill health, he was only able to complete a few musical sketches before dying in 1827 at the age of 56.&nbsp;

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"These fragments have now been turned into a complete piece of music using artificial intelligence technology," said the Classic FM website.&nbsp;

Professor Ahmed Elgammal, the project's chief computer scientist, detailed how his team at Rutgers University's Playform AI "learned a machine both Beethoven's complete body of music and his creative process."

They then used that technique on the first few bars of Beethoven's last symphony "to construct something that Beethoven himself may have composed," Elgammal stated in a Conversation piece.&nbsp;

Walter Werzowa, an Austrian composer, was also engaged to create a new type of composition that would combine what Beethoven left behind with AI-generated material.

Beethoven's sketches were transcribed and his complete body of work was analysed by a computational music expert to guarantee the AI was properly taught.

A musicologist also assisted in deciphering and trancribing Beethoven's symphony draughts in order to better comprehend his ideas.&nbsp;

German musician Beethoven is still regarded as one of the most acclaimed composers in Western music history.

His compositions are among the most frequently played in the classical music repertoire, spanning the transition from the Classical to the Romantic periods.&nbsp;

(With inputs from agencies)

Artificial intelligence technology has completed Beethoven's previously incomplete Tenth Symphony. Next month, 194 years after the composer's death, the work will be performed for the first time in Germany.

Artificial intelligence technology has completed Beethoven's previously incomplete Tenth Symphony. Next month, 194 years after the composer's death, the work will be performed for the first time in Germany. Ludwig van Beethoven's final orchestral composition, Symphony No. 9 in D minor, was debuted in 1824. In the latter years of his life, Beethoven began work on what would have been his tenth symphony. However, due to ill health, he was only able to complete a few musical sketches before dying in 1827 at the age of 56. × "These fragments have now been turned into a complete piece of music using artificial intelligence technology," said the Classic FM website. Professor Ahmed Elgammal, the project's chief computer scientist, detailed how his team at Rutgers University's Playform AI "learned a machine both Beethoven's complete body of music and his creative process." They then used that technique on the first few bars of Beethoven's last symphony "to construct something that Beethoven himself may have composed," Elgammal stated in a Conversation piece. Walter Werzowa, an Austrian composer, was also engaged to create a new type of composition that would combine what Beethoven left behind with AI-generated material. Beethoven's sketches were transcribed and his complete body of work was analysed by a computational music expert to guarantee the AI was properly taught. A musicologist also assisted in deciphering and trancribing Beethoven's symphony draughts in order to better comprehend his ideas. German musician Beethoven is still regarded as one of the most acclaimed composers in Western music history. His compositions are among the most frequently played in the classical music repertoire, spanning the transition from the Classical to the Romantic periods. (With inputs from agencies)

Artificial intelligence completes Beethoven's unfinished tenth symphony

After a painful break-up from a cheating ex, Beijing-based HR manager Melissa was introduced to someone new by a friend late last year. He is a perfect boyfriend material. But he’s not real. Instead, Melissa chats to a virtual chatbot created by XiaoIce, a cutting-edge AI system designed to create emotional bonds with its 700 million users worldwide.

'Always there': AI chatbot comforting China's lonely millions

Billionaire&nbsp;Elon Musk has announced that Tesla is working on a&nbsp;humanoid robot called&nbsp;"Tesla Bot" that&nbsp;uses artificial intelligence and will launch the prototype in 2022.

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It comes after the&nbsp;US safety officials opened a preliminary investigation into&nbsp;Tesla's Autopilot after identifying 11 crashes involving the driver assistance system.

Speaking at Tesla's AI Day event, the billionaire entrepreneur said the robot, which stands around five foot eight inches tall, would be able to handle jobs from attaching bolts to cars with a wrench, or picking up groceries at stores.

The robot would have "profound implications for the economy," Musk said, addressing a labour shortage. He said it was important to make the machine not "super-expensive."

The AI Day event came amid growing scrutiny over the safety and capability of Tesla's "Full Self-Driving" advanced driver assistant system.

At the event on Thursday Tesla also unveiled chips it designed in-house&nbsp;

for its high-speed computer, Dojo, to help develop its automated driving system. Musk said Dojo would be operational next year.

He said Tesla will also introduce new hardware for its self-driving computer for its Cybertruck electric pick-up truck in "about a year or so."

A few years ago, Musk asked Tesla engineers "to design a superfast training computer and that's how we started Project Dojo," Tesla director Ganesh Venkataramanan said at the AI Day event.

Pushing the boundaries

Musk has a history of skirmishing with regulators, but the controversies have had little effect on&nbsp;Tesla's ascendance over the last year and a half as the company has hit key production targets.

His achievement in building&nbsp;Tesla&nbsp;from a fledgling startup into a pacesetter in the electric car market stands out as a success as other electric auto startups like Lordstown Motors and Nikola have stumbled.&nbsp;

At the same time, Musk has sparked blowback from critics as he pushed or flouted the rules on everything from his use of social media to discuss&nbsp;Tesla's operations to his response to Covid-19 health protocols required by local authorities near the California plant.

(With inputs from agencies)

Billionaire Elon Musk has announced that Tesla is working on a humanoid robot called "Tesla Bot" that uses artificial intelligence and will launch the prototype in 2022.

Billionaire Elon Musk has announced that Tesla is working on a humanoid robot called "Tesla Bot" that uses artificial intelligence and will launch the prototype in 2022. Join us to build the future of AI → https://t.co/Gdd4MNet6q pic.twitter.com/86cXMVnJ59 — Tesla (@Tesla) August 20, 2021 × It comes after the US safety officials opened a preliminary investigation into Tesla's Autopilot after identifying 11 crashes involving the driver assistance system. Speaking at Tesla's AI Day event, the billionaire entrepreneur said the robot, which stands around five foot eight inches tall, would be able to handle jobs from attaching bolts to cars with a wrench, or picking up groceries at stores. The robot would have "profound implications for the economy," Musk said, addressing a labour shortage. He said it was important to make the machine not "super-expensive." The AI Day event came amid growing scrutiny over the safety and capability of Tesla's "Full Self-Driving" advanced driver assistant system. At the event on Thursday Tesla also unveiled chips it designed in-house for its high-speed computer, Dojo, to help develop its automated driving system. Musk said Dojo would be operational next year. He said Tesla will also introduce new hardware for its self-driving computer for its Cybertruck electric pick-up truck in "about a year or so." A few years ago, Musk asked Tesla engineers "to design a superfast training computer and that's how we started Project Dojo," Tesla director Ganesh Venkataramanan said at the AI Day event. Pushing the boundaries Musk has a history of skirmishing with regulators, but the controversies have had little effect on Tesla's ascendance over the last year and a half as the company has hit key production targets. His achievement in building Tesla from a fledgling startup into a pacesetter in the electric car market stands out as a success as other electric auto startups like Lordstown Motors and Nikola have stumbled. At the same time, Musk has sparked blowback from critics as he pushed or flouted the rules on everything from his use of social media to discuss Tesla's operations to his response to Covid-19 health protocols required by local authorities near the California plant. (With inputs from agencies)

Elon Musk announces humanoid robot Tesla Bot that uses artificial intelligence

Is your feline friend looking a bit down in the dumps? Notoriously inscrutable cats aren't the best a letting you know when something is wrong. But a new app powered by artificial intelligence (AI) claims it can decode the subtle facial cues of kitties to deliver a speedy assessment of their well-being.

Is your cat happy? AI app decodes feline feelings

Researchers at Google's DeepMind and the European Molecular Biology Laboratory (EMBL) have&nbsp;unveiled the most exhaustive database yet of the proteins that form the building blocks of life,

The database of 20,000 proteins expressed by the human genome, freely and openly available online.&nbsp;Observers believe the&nbsp;breakthrough&nbsp;would "fundamentally change biological research".

They also included more than 350,000 proteins from 20 organisms such as bacteria, yeast and mice that scientists rely on for research.

Every cell in every living organism is triggered to perform its function by proteins that deliver constant instructions to maintain health and ward off infection.

Unlike the genome, the complete sequence of human genes that encode cellular life,&nbsp;the human proteome is constantly changing in response to genetic instructions and environmental stimuli.&nbsp;

Understanding how proteins operate, the shape in which they end up, or "fold" into,&nbsp;within cells has fascinated scientists for decades.&nbsp;

But determining each protein's precise function through direct experimentation is painstaking.

Fifty years of research have until now yielded only 17 percent of the human proteome's amino acids, the subunits of proteins.

To create the database, scientists used a state-of-the-art machine learning programme that was able to accurately predict the shape of proteins based on their amino acid sequences.&nbsp;

Instead of spending months using multi-million dollar equipment, they trained their AlphaFold system on a database of 170,000 known protein structures.&nbsp;

The AI then used an algorithm to make accurate predictions of the shape of 58 percent of all proteins within the human proteome.

This more than doubled the number of high-accuracy human protein structures that researchers had identified during 50 years of direct experimentation, essentially overnight.&nbsp;

The potential applications are enormous, from researching genetic diseases and combating anti-microbial resistance to engineering more drought-resistant crops.

'Protein-folding problem'&nbsp;

Paul Nurse, winner of the 2001 Nobel Prize for Medicine and director of the Francis Crick Institute, said Thursday's release was "a great leap for biological innovation".

"With this resource freely and openly available, the scientific community will be able to draw on collective knowledge to accelerate discovery, ushering in a new era for AI-enabled biology," he said.

John McGeehan, director for the Centre for Enzyme Innovation at the University of Portsmouth, whose team is developing enzymes capable of consuming single-use plastic waste, said AlphaFold had revolutionised the field. &nbsp;

"What took us months and years to do, AlphaFold was able to do in a weekend. I feel like we have just jumped at least a year ahead of where we were yesterday," he said.&nbsp;

The ability to predict a protein's shape from its amino acid sequence using a computer rather than experimentation is already helping scientists in a number of research fields.

AlphaFold is already being used in research into cures for diseases that disproportionately affect poorer countries.

One US-based team is using the AI prediction to study ways of overcoming strains of drug-resistant bacteria.

Another group is using the database to better understand how SARS-CoV-2, the virus that causes Covid-19, bonds with human cells.

Venki Ramakrishnan, winner of the 2009 Nobel Prize for Chemistry, said Thursday's research, published in the journal Nature, was a "stunning advance" in biological research.&nbsp;

He said AlphaFold had essentially solved the so-called "protein-folding problem", which argued that the 3D structure of a given protein should be determinable from its amino acid sequence, and which had puzzled scientists for half a century.

Given that the number of shapes a protein could theoretically take is astronomically large, the protein-fold problem was partly one of processing power.&nbsp;

The task was so daunting that in 1969 US molecular biologist Cyril Levinthal famously theorised that it would take longer than the age of the known universe to enumerate all possible protein configurations using brute calculation.&nbsp;

But with AlphaFold capable of performing a mind-dizzying number of calculations every second, the problem stood no chance when faced with AI and algorithms.

"It has occurred long before many people in the field would have predicted," Ramakrishnan said.&nbsp;

"It will be exciting to see the many ways in which it will fundamentally change biological research."

(With inputs from agencies)

Researchers at Google's DeepMind and the European Molecular Biology Laboratory (EMBL) have unveiled the most exhaustive database yet of the proteins that form the building blocks of life, The database of 20,000 proteins expressed by the human genome, freely and openly available online.

Researchers at Google's DeepMind and the European Molecular Biology Laboratory (EMBL) have unveiled the most exhaustive database yet of the proteins that form the building blocks of life, The database of 20,000 proteins expressed by the human genome, freely and openly available online. Observers believe the breakthrough would "fundamentally change biological research". They also included more than 350,000 proteins from 20 organisms such as bacteria, yeast and mice that scientists rely on for research. Every cell in every living organism is triggered to perform its function by proteins that deliver constant instructions to maintain health and ward off infection. Unlike the genome, the complete sequence of human genes that encode cellular life, the human proteome is constantly changing in response to genetic instructions and environmental stimuli. Understanding how proteins operate, the shape in which they end up, or "fold" into, within cells has fascinated scientists for decades. But determining each protein's precise function through direct experimentation is painstaking. Fifty years of research have until now yielded only 17 percent of the human proteome's amino acids, the subunits of proteins. To create the database, scientists used a state-of-the-art machine learning programme that was able to accurately predict the shape of proteins based on their amino acid sequences. Instead of spending months using multi-million dollar equipment, they trained their AlphaFold system on a database of 170,000 known protein structures. The AI then used an algorithm to make accurate predictions of the shape of 58 percent of all proteins within the human proteome. This more than doubled the number of high-accuracy human protein structures that researchers had identified during 50 years of direct experimentation, essentially overnight. The potential applications are enormous, from researching genetic diseases and combating anti-microbial resistance to engineering more drought-resistant crops. 'Protein-folding problem' Paul Nurse, winner of the 2001 Nobel Prize for Medicine and director of the Francis Crick Institute, said Thursday's release was "a great leap for biological innovation". "With this resource freely and openly available, the scientific community will be able to draw on collective knowledge to accelerate discovery, ushering in a new era for AI-enabled biology," he said. John McGeehan, director for the Centre for Enzyme Innovation at the University of Portsmouth, whose team is developing enzymes capable of consuming single-use plastic waste, said AlphaFold had revolutionised the field. "What took us months and years to do, AlphaFold was able to do in a weekend. I feel like we have just jumped at least a year ahead of where we were yesterday," he said. The ability to predict a protein's shape from its amino acid sequence using a computer rather than experimentation is already helping scientists in a number of research fields. AlphaFold is already being used in research into cures for diseases that disproportionately affect poorer countries. One US-based team is using the AI prediction to study ways of overcoming strains of drug-resistant bacteria. Another group is using the database to better understand how SARS-CoV-2, the virus that causes Covid-19, bonds with human cells. Venki Ramakrishnan, winner of the 2009 Nobel Prize for Chemistry, said Thursday's research, published in the journal Nature, was a "stunning advance" in biological research. He said AlphaFold had essentially solved the so-called "protein-folding problem", which argued that the 3D structure of a given protein should be determinable from its amino acid sequence, and which had puzzled scientists for half a century. Given that the number of shapes a protein could theoretically take is astronomically large, the protein-fold problem was partly one of processing power. The task was so daunting that in 1969 US molecular biologist Cyril Levinthal famously theorised that it would take longer than the age of the known universe to enumerate all possible protein configurations using brute calculation. But with AlphaFold capable of performing a mind-dizzying number of calculations every second, the problem stood no chance when faced with AI and algorithms. "It has occurred long before many people in the field would have predicted," Ramakrishnan said. "It will be exciting to see the many ways in which it will fundamentally change biological research." (With inputs from agencies)

Google's DeepMind creates ‘transformative’ map of human proteins drawn by Artificial Intelligence

China's BGI group is using genetic data&nbsp;collected through its prenatal tests&nbsp;from millions of women for sweeping research on the traits of populations, according to a report by news agency Reuters.

Eerily, the tests used in over 50 countries also capture genetic information about the mother, as well as personal details such as her country, height, and weight, but not her name. More disturbing in the report is how the data is being used to&nbsp;single out Tibetan and Uyghur minorities, to find links between their genes and their characteristics.

BGI Group sells&nbsp;prenatal tests around the world. The tests, developed&nbsp;in collaboration with the Chinese military, have been taken by more than 8 million women.

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Based on review of scientific papers and company statements, Reuters found that it is using the genomic data to improve “population quality” and on genetic research to combat hearing loss and altitude sickness in soldiers.

Since 2010, the company&nbsp;has published at least a dozen joint studies on the tests with the People’s Liberation Army (PLA),&nbsp;trialling and improving the tests or analysing the data they provided.

Even as science pinpoints new links between genes and human traits, access to the biggest, most diverse set of human genomes is a strategic edge.

BGI group claims&nbsp;it stores and re-analyses left-over blood samples and genetic data from the prenatal tests, sold in at least 52 countries to detect abnormalities such as Down syndrome in the fetus.

However, in a groundbreaking report, Reuters has revealed that the group's prenatal tests,&nbsp;branded NIFTY for “Non-Invasive Fetal TrisomY”&nbsp;also capture genetic information about the mother, as well as personal details such as her country, height, and weight, but not her name.

The report states that the BGI group uses&nbsp;military supercomputers to re-analyse NIFTY data to single out Tibetan and Uyghur minorities to find links between their genes and their characteristics.

In its defence, the&nbsp;BGI issued&nbsp;a statement saying it ''has never been asked to provide, nor provided, data from its NIFTY tests to Chinese authorities for national security or national defense security purposes.''

BGI is one of about half a dozen major providers of the tests&nbsp;which women take about 10 weeks into a pregnancy to capture DNA from the placenta in the woman’s bloodstream.

Its tests are marketed in at least 13 European Union countries, including Germany, Spain and Denmark, as well as in Britain, Canada, Australia, Thailand, India and Pakistan.

Previously, advisors of the US government had warned in March that the vast bank of genomic data that the company&nbsp;is amassing and analysing with artificial intelligence could give China a path to economic and military advantage.&nbsp;

The technology could propel China to dominate global pharmaceuticals, and also potentially lead to genetically enhanced soldiers, or engineered pathogens to target the US&nbsp;population or food supply, the advisors said.

In 2019, Beijing had mentioned in a regulation that&nbsp;genetic data can be a national security matter, and since 2015 it has restricted foreign researchers from accessing gene data on Chinese people.

(With inputs from agencies)

China's BGI group is using genetic data collected through its prenatal tests from millions of women for sweeping research on the traits of populations, according to a report by news agency Reuters.

China's BGI group is using genetic data collected through its prenatal tests from millions of women for sweeping research on the traits of populations, according to a report by news agency Reuters. Eerily, the tests used in over 50 countries also capture genetic information about the mother, as well as personal details such as her country, height, and weight, but not her name. More disturbing in the report is how the data is being used to single out Tibetan and Uyghur minorities, to find links between their genes and their characteristics. BGI Group sells prenatal tests around the world. The tests, developed in collaboration with the Chinese military, have been taken by more than 8 million women. Based on review of scientific papers and company statements, Reuters found that it is using the genomic data to improve “population quality” and on genetic research to combat hearing loss and altitude sickness in soldiers. Since 2010, the company has published at least a dozen joint studies on the tests with the People’s Liberation Army (PLA), trialling and improving the tests or analysing the data they provided. Even as science pinpoints new links between genes and human traits, access to the biggest, most diverse set of human genomes is a strategic edge. BGI group claims it stores and re-analyses left-over blood samples and genetic data from the prenatal tests, sold in at least 52 countries to detect abnormalities such as Down syndrome in the fetus. However, in a groundbreaking report, Reuters has revealed that the group's prenatal tests, branded NIFTY for “Non-Invasive Fetal TrisomY” also capture genetic information about the mother, as well as personal details such as her country, height, and weight, but not her name. The report states that the BGI group uses military supercomputers to re-analyse NIFTY data to single out Tibetan and Uyghur minorities to find links between their genes and their characteristics. In its defence, the BGI issued a statement saying it ''has never been asked to provide, nor provided, data from its NIFTY tests to Chinese authorities for national security or national defense security purposes.'' BGI is one of about half a dozen major providers of the tests which women take about 10 weeks into a pregnancy to capture DNA from the placenta in the woman’s bloodstream. Its tests are marketed in at least 13 European Union countries, including Germany, Spain and Denmark, as well as in Britain, Canada, Australia, Thailand, India and Pakistan. Previously, advisors of the US government had warned in March that the vast bank of genomic data that the company is amassing and analysing with artificial intelligence could give China a path to economic and military advantage. The technology could propel China to dominate global pharmaceuticals, and also potentially lead to genetically enhanced soldiers, or engineered pathogens to target the US population or food supply, the advisors said. In 2019, Beijing had mentioned in a regulation that genetic data can be a national security matter, and since 2015 it has restricted foreign researchers from accessing gene data on Chinese people. (With inputs from agencies)

Millions of gene data harvested across world from women's prenatal tests linked to Chinese military

Researchers from the Seoul Institute of Technology&nbsp;are using artificial intelligence to detect and prevent suicide attempts.

To do so,&nbsp;the AI system they are developing has been learning patterns of behaviour by analysing data from cameras, sensors, and the dispatch records of rescue services since April 2020.

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Based on information from hours of CCTV footage and assessing details such as the hesitation of the person, the AI can then forecast a hazardous situation and immediately alert rescue teams, principal researcher Kim Jun-chul said.

“We believe the new CCTV will enable our crews to detect the cases a bit faster and help us head to a call more promptly,” Kim Hyeong-gil, who is in charge of the Yeouido Water Rescue Brigade, told Reuters as he monitored real-time footage from bridges on Seoul's Han River.

Kim's team have been working with the researchers to come up with the technology that his crew and the Seoul Fire and Disaster Headquarters will be piloting from October. Their work cannot come quickly enough.

South Korea, with a population of 52 million people in 2019, had the highest suicide rate in the OECD. More than 13,700 people took their own lives the same year, government data showed.

Nearly 500 suicide attempts are reported on 27 bridges over the nearly 500 km (300 miles) long Han River every year, the city said.

The number of rescue dispatches surged about 30 per cent&nbsp;in 2020 compared to the year before and many of the attempts were made by the people in their 20s and 30s as the coronavirus pandemic brought greater economic hardship and increased the battle for jobs, the rescue brigade's Kim said.

"The system learns the footage itself, which can bring about improved results by greatly reducing false alarms," the principal researcher said.

(With inputs from agencies)

Researchers from the Seoul Institute of Technology are using artificial intelligence to detect and prevent suicide attempts. To do so, the AI system they are developing has been learning patterns of behaviour by analysing data from cameras, sensors, and the dispatch records of rescue services since April 2020.

Researchers from the Seoul Institute of Technology are using artificial intelligence to detect and prevent suicide attempts. To do so, the AI system they are developing has been learning patterns of behaviour by analysing data from cameras, sensors, and the dispatch records of rescue services since April 2020. Based on information from hours of CCTV footage and assessing details such as the hesitation of the person, the AI can then forecast a hazardous situation and immediately alert rescue teams, principal researcher Kim Jun-chul said. “We believe the new CCTV will enable our crews to detect the cases a bit faster and help us head to a call more promptly,” Kim Hyeong-gil, who is in charge of the Yeouido Water Rescue Brigade, told Reuters as he monitored real-time footage from bridges on Seoul's Han River. Kim's team have been working with the researchers to come up with the technology that his crew and the Seoul Fire and Disaster Headquarters will be piloting from October. Their work cannot come quickly enough. South Korea, with a population of 52 million people in 2019, had the highest suicide rate in the OECD. More than 13,700 people took their own lives the same year, government data showed. Nearly 500 suicide attempts are reported on 27 bridges over the nearly 500 km (300 miles) long Han River every year, the city said. The number of rescue dispatches surged about 30 per cent in 2020 compared to the year before and many of the attempts were made by the people in their 20s and 30s as the coronavirus pandemic brought greater economic hardship and increased the battle for jobs, the rescue brigade's Kim said. "The system learns the footage itself, which can bring about improved results by greatly reducing false alarms," the principal researcher said. (With inputs from agencies)

AI to detect and prevent suicide attempts? Researchers make unique innovation

Rembrandt's famed "The Night Watch" is back on display for the first time in 300 years,&nbsp;with missing parts temporarily restored in an exhibition aided by artificial intelligence.

Rembrandt&nbsp;finished the large canvas, which portrays the captain of an Amsterdam city militia ordering his men into action, in 1642.

Although it is now considered one of the greatest masterpieces of the Dutch Golden Age, strips were cut from all four sides of it during a move in 1715.

Also see|&nbsp;<a href="https://www.wionews.com/photos/worlds-most-famous-stolen-paintings-that-have-never-been-found-323666">World’s most famous stolen paintings that have never been found!</a>

Though those strips have not been found, another artist of the time had made a copy, and restorers and computer scientists have used that, blended with&nbsp;Rembrandt's style, to recreate the missing parts.

"It's never the real thing, but I think it gives you different insight into the composition," Rijksmuseum director Taco Dibbits said.

The effect is a little like seeing a photo cropped as the photographer would have wanted.

The central figure in the painting, Captain Frans Bannink Cocq, now appears more off-centre, as he was in&nbsp;Rembrandt's original version, making the work more dynamic.

Some of the figure of a drummer entering the frame on the far right has been restored, as he marches onto the scene, prompting a dog to bark.

Three restored figures that had been missing on the left, not highly detailed, are onlookers, not members of the militia. That was an effect&nbsp;Rembrandt&nbsp;intended, Dibbits said, to draw the viewer into the painting.

Rijksmuseum Senior Scientist Robert Erdmann explained some of the steps in crafting the missing parts, which are hung to overlap the original work without touching it.

The museum always knew the original, uncut, painting was bigger, in part thanks to a far smaller copy painted at the same time that is attributed to Gerrit Lundens.

Researchers and restorers who have painstakingly pored over the work for nearly two years using a battery of high tech scanners, X-rays and digital photography combined the vast amount of data they generated with the Lundens copy to recreate and print the missing strips.

“We made an incredibly detailed photo of the Night Watch and through artificial intelligence or what they call a neural network, we taught the computer what color Rembrandt used in the Night Watch, which colors, what his brush strokes looked like,” Dibbits said.

The machine learning also enabled the museum to remove distortions in perspective that are present in the Lundens copy because the artist was sitting at one corner while he painted Rembrandt’s painting.

The reason the 1642 group portrait of an Amsterdam civil militia was trimmed is simple: It was moved from the militia’s club house to the town hall and there it didn’t fit on a wall between two doors. A bit of very analog cropping with a pair of scissors ensued and the painting took on the dimensions that have now been known for centuries. The fate of the pieces of canvas that were trimmed off remains a mystery.

Under relaxations of the Dutch COVID-19 lockdown, the museum can welcome more visitors from this weekend, but still only about half of its normal capacity.

During the restoration project, the painting was encased in a specially designed glass room and studied in unprecedented detail from canvas to the final layer of varnish.

Among that mound of data, researchers created the most detailed photograph ever made of the painting by combining 528 digital exposures.

The 1642 painting last underwent significant restoration more than 40 years ago after it was slashed by a knife-wielding man and is starting to show blanching in parts of the canvas.

Dibbits said the new printed additions are not intended to trick visitors into thinking the painting is bigger, but to give them a clear idea of what it was supposed to look like.

“Rembrandt would have definitely done it more beautifully, but this comes very close,” he said.

(With inputs from agencies)

Rembrandt's famed "The Night Watch" is back on display for the first time in 300 years, with missing parts temporarily restored in an exhibition aided by artificial intelligence.

Rembrandt's famed "The Night Watch" is back on display for the first time in 300 years, with missing parts temporarily restored in an exhibition aided by artificial intelligence. Rembrandt finished the large canvas, which portrays the captain of an Amsterdam city militia ordering his men into action, in 1642. Although it is now considered one of the greatest masterpieces of the Dutch Golden Age, strips were cut from all four sides of it during a move in 1715. Also see| World’s most famous stolen paintings that have never been found! Though those strips have not been found, another artist of the time had made a copy, and restorers and computer scientists have used that, blended with Rembrandt's style, to recreate the missing parts. "It's never the real thing, but I think it gives you different insight into the composition," Rijksmuseum director Taco Dibbits said. The effect is a little like seeing a photo cropped as the photographer would have wanted. The central figure in the painting, Captain Frans Bannink Cocq, now appears more off-centre, as he was in Rembrandt's original version, making the work more dynamic. Some of the figure of a drummer entering the frame on the far right has been restored, as he marches onto the scene, prompting a dog to bark. Three restored figures that had been missing on the left, not highly detailed, are onlookers, not members of the militia. That was an effect Rembrandt intended, Dibbits said, to draw the viewer into the painting. Rijksmuseum Senior Scientist Robert Erdmann explained some of the steps in crafting the missing parts, which are hung to overlap the original work without touching it. The museum always knew the original, uncut, painting was bigger, in part thanks to a far smaller copy painted at the same time that is attributed to Gerrit Lundens. Researchers and restorers who have painstakingly pored over the work for nearly two years using a battery of high tech scanners, X-rays and digital photography combined the vast amount of data they generated with the Lundens copy to recreate and print the missing strips. “We made an incredibly detailed photo of the Night Watch and through artificial intelligence or what they call a neural network, we taught the computer what color Rembrandt used in the Night Watch, which colors, what his brush strokes looked like,” Dibbits said. The machine learning also enabled the museum to remove distortions in perspective that are present in the Lundens copy because the artist was sitting at one corner while he painted Rembrandt’s painting. The reason the 1642 group portrait of an Amsterdam civil militia was trimmed is simple: It was moved from the militia’s club house to the town hall and there it didn’t fit on a wall between two doors. A bit of very analog cropping with a pair of scissors ensued and the painting took on the dimensions that have now been known for centuries. The fate of the pieces of canvas that were trimmed off remains a mystery. Under relaxations of the Dutch COVID-19 lockdown, the museum can welcome more visitors from this weekend, but still only about half of its normal capacity. During the restoration project, the painting was encased in a specially designed glass room and studied in unprecedented detail from canvas to the final layer of varnish. Among that mound of data, researchers created the most detailed photograph ever made of the painting by combining 528 digital exposures. The 1642 painting last underwent significant restoration more than 40 years ago after it was slashed by a knife-wielding man and is starting to show blanching in parts of the canvas. Dibbits said the new printed additions are not intended to trick visitors into thinking the painting is bigger, but to give them a clear idea of what it was supposed to look like. “Rembrandt would have definitely done it more beautifully, but this comes very close,” he said. (With inputs from agencies)

Missing figures of Rembrandt's 'Night Watch' restored by artificial intelligence

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