Latest news with #1X
Time of India
30-05-2025
- Time of India
Police bust betting racket during women's cricket match in Indore
Indore: In a late-night operation on Wednesday, Rajendra Nagar police searched a cricket turf and busted a betting racket that was operating under the guise of a women's cricket match. Additional DCP Alok Sharma said that the match was being streamed live on YouTube under the name 'Female Indoor Cricket League', while bets were being placed through a mobile application called '1X' allegedly operated from Delhi. Sharma said that the authorities received intelligence about these activities for some time, particularly regarding matches held at a turf near Treasure Town Colony in Bijalpur, where female players participated in seemingly legitimate games that were used as a front for illegal online betting. Acting on this information, the police team reached the location and detained Anurag Dalal, who was living at a rented accommodation in Treasure Town and is originally from Delhi. During questioning, Anurag revealed that the entire operation was orchestrated by his friend Siddharth Rai, who resides in Delhi. According to Anurag, Siddharth handled the live broadcast of the matches on YouTube and facilitated the betting transactions using a specially developed application. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like 不加糖「愛文芒果乾」，每顆鮮果只取2片製作，品質高口感好，超85%用戶回購 Foodmall 立即選購 Undo Based on this revelation, Siddharth has also been named as an accused, and efforts are underway to track him down, along with other individuals involved in the network. Sharma said that a team will be sent to Delhi in search of the accused. At the time of the search, women were actively playing cricket on the turf while two cameras captured the live footage for the YouTube stream. "It is a matter of investigation if the women knew about the betting. Actions will be taken if necessary," he said. The police seized several electronic items from the site, including two mobile phones, a customised CPU, two monitors, two cameras, a UPS, a Cyber Power DVR and a router. In addition, a diary containing betting records and approximately Rs 35,000 in cash were also recovered. The police are now analysing technical evidence to expose the full extent of the betting syndicate.
The Star
05-05-2025
- Business
- The Star
Invasion of the home humanoid robots
REDWOOD CITY, California: On a recent morning, I knocked on the front door of a handsome two-story home in Redwood City, California. Within seconds, the door was opened by a faceless robot dressed in a beige bodysuit that clung tight to its trim waist and long legs. This svelte humanoid greeted me with what seemed to be a Scandinavian accent, and I offered to shake hands. As our palms met, it said: 'I have a firm grip.' When the home's owner, a Norwegian engineer named Bernt Børnich, asked for some bottled water, the robot turned, walked into the kitchen and opened the refrigerator with one hand. Artificial intelligence is already driving cars, writing essays and writing computer code. Now humanoids, machines built to look like humans and powered by AI, are poised to move into our homes so they can help with the daily chores. Børnich is CEO and founder of a startup called 1X. Before the end of the year, his company hopes to put his robot, Neo, into more than 100 homes in Silicon Valley and elsewhere. His startup is among the dozens of companies planning to sell humanoids for homes and businesses. Investors have poured US$7.2bil (RM31.49bil) into more than 50 startups since 2015, according to PitchBook, a research firm that tracks the tech industry. The humanoid frenzy reached a new peak last year, when investments topped US$1.6bil (RM7bil). That did not include the billions that Elon Musk and Tesla, his electric car company, are pumping into Optimus, a humanoid they began building in 2021. Entrepreneurs like Børnich and Musk believe that humanoids will one day do much of the physical work that is now handled by people, including household chores like wiping counters and emptying dishwashers, warehouse work like sorting packages, and factory labour like building cars on an assembly line. Simpler robots – small robotic arms and autonomous carts, for instance – have long shared the workload at warehouses and factories. Now companies are betting that machines can tackle a wider range of tasks by mimicking the ways that people walk, bend, twist, reach, grip and generally get things done. Because homes, offices and warehouses are already built for humans, these companies argue, humanoids are better equipped to navigate the world than any other robot. The push toward humanoid labour has been building for years, fueled by advances in both robotic hardware and AI technologies that allow robots to rapidly learn new skills. But these humanoids are still a bit of a mirage. Internet videos have circulated for years showing the remarkable dexterity of these machines, but they are often remotely guided by humans. And simple tasks like loading the dishwasher are anything but simple for them. 'There are many videos out there that give a false impression of these robots,' said Ken Goldberg, a robotics professor at the University of California, Berkeley. 'Though they look like humans, they aren't always behaving like humans.' Neo said 'Hello' with a Scandinavian accent because it was operated by a Norwegian technician in the basement of Børnich's home. (Ultimately, the company wants to build call centers where perhaps dozens of technicians would support robots.) The robot walked through the dining room and kitchen on its own. But the technician spoke for Neo and remotely guided its hands via a virtual reality headset and two wireless joysticks. Robots are still learning to navigate the world on their own. And they need a lot of help doing it. At least for now. 'I saw a level of hardware that I did not think was possible.' I first visited 1X's offices in Silicon Valley nearly a year ago. When a robot named Eve entered the room, opening and closing the door, I could not shake the feeling that this wide-eyed robot was really a person in costume. Eve moved on wheels, not legs. Yet it still felt human. I thought of Sleeper , the 1973 Woody Allen sci-fi comedy filled with robotic butlers. The company's engineers had already built Neo, but it hadn't learned to walk. An early version hung on the wall of the company's lab. In 2022, Børnich logged on to a Zoom call with an AI researcher named Eric Jang. They had never met. Jang, now 30, worked in a robotics lab at Google's Silicon Valley headquarters, and Børnich, now 42, ran a startup in Norway called Halodi Robotics. A would-be investor had asked Jang to gather some information about Halodi to see if it was worth an investment. Børnich showed off Eve. It was something he had dreamed of building since he was a teenager, inspired – like many roboticists – by science fiction (his personal favorite: the 1982 movie Blade Runner ). Jang was entranced by the way that Eve moved. He compared the Zoom call to a scene in the sci-fi television drama Westworld in which a man attends a cocktail party and is shocked to learn that everyone in the room is a robot. 'I saw a level of hardware that I did not think was possible,' Jang said. The would-be investor did not invest in Halodi. But Jang soon convinced Børnich to join forces. Jang was part of a Google team teaching robots new skills using mathematical systems called neural networks, which allow robots to learn from data that depicts real-world tasks. After seeing Eve, Jang told Børnich that they should apply the same technique to humanoids. The result was a cross-Atlantic company they renamed 1X. The startup, which has grown to around 200 employees, is now backed by over US$125mil (RM546.75mil) in funding from investors that include Tiger Global and OpenAI. 'All of this is learned behaviour.' When I returned to the company's lab about six months after meeting Eve, I was greeted by a walking Neo. They had taught it to walk entirely in the digital world. By simulating the physics of the real world in a video-game-like environment, they could train a digital version of their robot to stand and balance and, eventually, take steps. After months spent training this digital robot, they transferred everything it had learned to a physical humanoid. If I stepped into Neo's path, it would stop and move around me. If I pushed its chest, it stayed on its feet. Sometimes, it stumbled or did not quite know what to do. But it could walk around a room much like people do. 'All of this is learned behaviour,' Jang said, as Neo clicked against the floor with each step. 'If we put it into any environment, it should know how to do this.' Training a robot to do household chores, however, is an entirely different prospect. Because the physics of loading a dishwasher or folding laundry are exceedingly complex, 1X cannot teach these tasks in the virtual world. It has to gather data inside real homes. When I visited Børnich's home a month later, Neo started to struggle with the refrigerator's stainless-steel door. The robot's WiFi connection had dropped. But once the hidden technician rebooted the WiFi, he seamlessly guided the robot through its small task. Neo handed me a bottled water. I also watched Neo load a washing machine, squatting gingerly to lift clothes from a laundry basket. And as Børnich and I chatted outside the kitchen, the robot started wiping the counters. All of this was done via remote control. Even when controlled by humans, Neo might drop a cup or struggle to find the right angle as it tries to toss an empty bottle into a garbage can under a sink. Though humanoids have improved by leaps and bounds over the past decade, they are still not as nimble as humans. Neo, for instance, cannot raise its arms above its head. Neo can also feel a little creepy, like anything else that seems partly human and partly not. Talking to it is particularly strange, given that you are really talking to a remote technician. It's like talking to a ventriloquist's dummy. 'What we are selling is more of a journey than a destination.' By guiding Neo through households chores, Børnich and his team can gather data – using cameras and other sensors installed on the robot itself – that show how these tasks are done. Then 1X engineers can use this data to expand and improve Neo's skills. Just as ChatGPT can learn to write term papers by analysing text culled from the internet, a robot can learn to clean windows by pinpointing patterns in hours of digital video. Most humanoid efforts, including Musk's Optimus and similar projects like Apptronik and Figure AI, are designing humanoids for warehouses and factories, arguing that these tightly controlled environments will be easier for robots to navigate. But through selling humanoids into homes, 1X hopes to gather enormous amounts of data that can ultimately show these robots how to handle the chaos of daily life. First the company must find people who will welcome an early version of a strange new technology into their homes – and pay for it. 1X has not yet set a price for these machines, which it manufactures at its own factory in Norway. Building a humanoid like Neo costs about as much as building a small car – tens of thousands of dollars. To reach its potential, Neo must capture video of what happens inside homes. In some cases, technicians will see what happens in real time. Fundamentally, this is a robot that learns on the job. 'What we are selling is more of a journey than a destination,' Børnich said. 'It is going to be a really bumpy road, but Neo will do things that are truly useful.' 'We want you to give us your data on your terms.' When I asked Børnich how the company would handle privacy once the humanoids were inside customers' homes, he explained that technicians, working from remote call centers, would only take control of the robot if they received approval from the owner via a smartphone app. He also said data would not be used to train new systems until at least 24 hours after it was gathered. That would allow 1X to delete any videos that customers did not want the company to use. 'We want you to give us your data on your terms,' Børnich said. Using this data, Børnich hopes to produce a humanoid that can do almost any household chore. That means Neo could potentially replace workers who make their living cleaning homes. But that is still years away – at best. And because of growing shortage of workers who handle both house cleaning and care of elders and children, organizations that represent these workers welcome the rise of new technologies that do work in the home – provided that companies like 1X build robots that work well alongside human workers. 'These tools could make some of the more strenuous, taxing and dangerous work easier and allow workers to focus on things that only human workers can offer,' said Ai-jen Poo, president of the National Domestic Workers Alliance, which represents the country's house cleaners, home-care workers and nannies. Soon, Neo began cleaning the towering windows on the side of the house. Then as I turned back to Børnich, I heard a crash on the kitchen floor. After an electrical malfunction, Neo had fallen over backward – fainting dead away. Børnich picked the robot up as if it were a small teenager, carried it into the living room and laid it down on a chair. Even passed out, Neo looked human. Other humanoids I've met can be intimidating. Neo, under 5 1/2 feet tall and 66 pounds, is not. But I still wondered if it could injure a pet – or a child – with a fall like that. Will people let this machine into their homes? How quickly will its skills improve? Can it free people from their daily chores? These questions cannot yet be answered. But Børnich is pressing forward. 'There are a lot of people like me,' he said. 'They've dreamed of having something like this in their home since they were a kid.' – ©2025 The New York Times Company This article originally appeared in The New York Times.
New York Times
04-04-2025
- Business
- New York Times
Invasion of the Home Humanoid Robots
On a recent morning, I knocked on the front door of a handsome two-story home in Redwood City, Calif. Within seconds, the door was opened by a faceless robot dressed in a beige bodysuit that clung tight to its trim waist and long legs. This svelte humanoid greeted me with what seemed to be a Scandinavian accent, and I offered to shake hands. As our palms met, it said: 'I have a firm grip.' When the home's owner, a Norwegian engineer named Bernt Børnich, asked for some bottled water, the robot turned, walked into the kitchen and opened the refrigerator with one hand. Artificial intelligence is already driving cars, writing essays and even writing computer code. Now, humanoids, machines built to look like humans and powered by A.I., are poised to move into our homes so they can help with the daily chores. Mr. Børnich is chief executive and founder of a start-up called 1X. Before the end of the year, his company hopes to put his robot, Neo, into more than 100 homes in Silicon Valley and elsewhere. His start-up is among the dozens of companies planning to sell humanoids and get them into both homes and businesses. Investors have poured $7.2 billion into more than 50 start-ups since 2015, according to PitchBook, a research firm that tracks the tech industry. The humanoid frenzy reached a new peak last year, when investments topped $1.6 billion. And that did not include the billions that Elon Musk and Tesla, his electric car company, are pumping into Optimus, a humanoid they began building in 2021. Entrepreneurs like Mr. Børnich and Mr. Musk believe humanoids will one day do much of the physical work that is now handled by people, including household chores like wiping counters and emptying dishwashers, warehouse jobs like sorting packages and factory labor like building cars on an assembly line. Simpler robots — small robotic arms and autonomous carts, for instance — have long shared the workload inside warehouses and factories. Now, companies are betting that machines can tackle a wider range of tasks by mimicking the ways that people walk, bend, twist, reach, grip and generally get things done. Because homes, offices and warehouses are already built for humans, these companies argue, humanoids are better equipped to navigate the world than any other robot. The push toward humanoid labor has been building for years, fueled by advances in both robotic hardware and A.I. technologies that allow robots to rapidly learn new skills. But these humanoids are still a bit of a mirage. Internet videos have circulated for years showing the remarkable dexterity of these machines, but very often, they are remotely guided by humans. And simple tasks like loading the dishwasher are anything but simple for them. 'There are many videos out there that give a false impression of these robots,' said Ken Goldberg, a robotics professor at the University of California, Berkeley. 'Though they look like humans, they aren't always behaving like humans.' Neo said 'Hello' with a Scandinavian accent because it was operated by a Norwegian technician in the basement of Mr. Børnich's home. (Ultimately, the company wants to build call centers where perhaps dozens of technicians would support robots.) The robot walked through the dining room and kitchen on its own. But the technician spoke for Neo and remotely guided its hands via a virtual reality headset and two wireless joysticks. Robots are still learning to navigate the world on their own. And they need a lot of help doing it. At least, for now. 'I saw a level of hardware that I did not think was possible.' I first visited 1X's offices in Silicon Valley nearly a year ago. When a robot named Eve entered the room, opening and closing the door, I could not shake the feeling that this wide-eyed robot was really a person in costume. Eve moved on wheels, not legs. And yet, it still felt human. I thought of 'Sleeper,' the 1973 Woody Allen sci-fi comedy filled with robotic butlers. The company's engineers had already built Neo, but it hadn't learned to walk. An early version hung on the wall of the company's lab. In 2022, Mr. Børnich logged onto a Zoom call with an A.I. researcher named Eric Jang. They had never met. Mr. Jang, now 30, worked in a robotics lab at Google's Silicon Valley headquarters, and Mr. Børnich, now 42, ran a start-up in Norway called Halodi Robotics. A would-be investor had asked Mr. Jang to gather some information on Halodi, to see if it was worth an investment. Mr. Børnich showed off the company's humanoid, Eve. It was something he had dreamed of building since he was a teenager, inspired — like many roboticists — by science fiction (his personal favorite: the 1982 movie 'Blade Runner'). Mr. Jang was entranced by the way that Eve moved. He compared the Zoom call to a scene in the sci-fi television drama 'Westworld' in which a man attends a cocktail party and is shocked to learn that everyone in the room is a robot. 'I saw a level of hardware that I did not think was possible,' Mr. Jang said. The would-be investor did not invest in Halodi. But Mr. Jang soon convinced Mr. Børnich to join forces. Mr. Jang was part of a Google team teaching robots new skills using mathematical systems called neural networks, which allow robots to learn from data that depicts real-world tasks. After seeing Eve, Mr. Jang told Mr. Børnich they should apply the same technique to humanoids. The result was a cross-Atlantic company they renamed 1X. The start-up, which has grown to around 200 employees, is now backed by over $125 million in funding from investors that include Tiger Global and the artificial intelligence start-up OpenAI. 'All of this is learned behavior.' When I returned to the company's lab about six months after meeting Eve, I was greeted by a walking Neo. They had taught it to walk entirely in the digital world. By simulating the physics of the real world in a video-game-like environment, they could train a digital version of their robot to stand and balance and, eventually, take steps. After months spent training this digital robot, they transferred everything it had learned to a physical humanoid. If I stepped into Neo's path, it would stop and move around me. If I pushed its chest, it stayed on its feet. Sometimes, it stumbled or did not quite know what to do. But it could walk around a room much like people do. 'All of this is learned behavior,' Mr. Jang said, as Neo clicked against the floor with each step. 'If we put it into any environment, it should know how to do this.' Training a robot to do household chores, however, is an entirely different prospect. Because the physics of loading a dishwasher or folding laundry are exceedingly complex, 1X cannot teach these tasks in the virtual world. They have to gather data inside real homes. When I visited Mr. Børnich's home a month later, Neo started to struggle with the refrigerator's stainless-steel door. The robot's Wi-Fi connection had dropped. But once the hidden technician rebooted the Wi-Fi, he seamlessly guided the robot through its small task. Neo handed me a bottled water. I also watched Neo load a washing machine, squatting gingerly to lift clothes from a laundry basket. And as Mr. Børnich and I chatted outside the kitchen, the robot started wiping the counters. All this was done via remote control. Even when controlled by humans, Neo might drop a cup or struggle to find the right angle as it tries to toss an empty bottle into a garbage can under a sink. Though humanoids have improved by leaps and bounds over the past decade, they are still not as nimble as humans. Neo, for instance, cannot raise its arms above its head. For the uninitiated, Neo can also feel a little creepy, like anything else that seems partly human and partly not. Talking to it is particularly strange, given that you are really talking to a remote technician. It's like talking to a ventriloquist's dummy. 'What we are selling is more of a journey than a destination.' By guiding Neo through households chores, Mr. Børnich and his team can gather data — using cameras and other sensors installed on the robot itself — that show how these tasks are done. Then 1X engineers can use this data to expand and improve Neo's skills. Just as ChatGPT can learn to write term papers by analyzing text culled from the internet, a robot can learn to clean windows by pinpointing patterns in hours of digital video. Most humanoid efforts, including Mr. Musk's Optimus and similar projects like Apptronik and Figure AI, are designing humanoids for warehouses and factories, arguing that these tightly controlled environments will be easier for robots to navigate. But through selling humanoids into homes, 1X hopes to gather enormous amounts of data that can ultimately show these robots how to handle the chaos of daily life. First, the company must find people who will welcome an early version of a strange new technology into their homes — and pay for it. 1X has not yet set a price for these machines, which it manufactures inside its own factory in Norway. Building a humanoid like Neo costs about as much as building a small car — tens of thousands of dollars. To reach its potential, Neo must capture video of what happens inside homes. In some cases, technicians will see what happens in real time. Fundamentally, this is a robot that learns on the job. 'What we are selling is more of a journey than a destination,' Mr. Børnich said. 'It is going to be a really bumpy road, but Neo will do things that are truly useful.' 'We want you to give us your data on your terms.' When I asked Mr. Børnich how the company would handle privacy once the humanoids were inside customers' homes, he explained that technicians, working from remote call centers, would only take control of the robot if they received approval from the owner via a smartphone app. He also said that data would not be used to train new systems until at least 24 hours after it was gathered. That would allow 1X to delete any videos that customers do not want the company to use. 'We want you to give us your data on your terms,' Mr. Børnich said. Using this data, Mr. Børnich hopes to produce a humanoid that can do almost any household chore. That means Neo could potentially replace workers who make their living cleaning homes. But that is still years away — at best. And because of growing shortage of workers who handle both house cleaning and care of elders and children, organizations that represent these workers welcome the rise of new technologies that do work in the home — provided that companies like 1X build robots that work well alongside human workers. 'These tools could make some of the more strenuous, taxing and dangerous work easier — and allow workers to focus on things that only human workers can offer,' said Ai-jen Poo, president of the National Domestic Workers Alliance, which represents the country's house cleaners, home-care workers and nannies. Soon, Neo began cleaning the towering windows on the side of the house. Then, as I turned back to Mr. Børnich, I heard a crash on the kitchen floor. After an electrical malfunction, Neo had fallen over backward — fainting dead away. Mr. Børnich picked the robot up, like it was small teenager, carried it into the living room and laid it down on a chair. Even when Neo passed out, it looked human. Other humanoids I've met can be intimidating. Neo, less than five and half feet tall and a 66 pounds, is not. But I still wondered if it could injure a pet — or a child — with a fall like that. Will people let this machine into their homes? How quickly will its skills improve? Can it free people from their daily chores? These questions cannot yet be answered. But Mr. Børnich is pressing forward. 'There are a lot of people like me," he said. 'They've dreamed of having something like this in their home since they were a kid.'
Fox News
19-03-2025
- Business
- Fox News
Fox News AI Newsletter: 'America's great industrial comeback'
IN TODAY'S NEWSLETTER: -- Vance knocks globalization's 'cheap labor' and lauds 'America's great industrial comeback' at AI summit-- Home robot automates household chores like Rosie from 'The Jetsons'-- AI dashcams enhance trucker safety while raising privacy concerns-- Getting divorced? Artificial intelligence deepfakes could cost you in court 'INDUSTRIAL COMEBACK': Vice President JD Vance knocked recent globalization efforts that use "cheap labor as a crutch" while simultaneously hampering innovation on the global scale during a Tuesday tech and artificial intelligence speech. NO MORE CHORES: Developed by the artificial intelligence company 1X, NEO Gamma isn't your clunky, metallic automaton. It is designed to be a helpful, almost human-like assistant. AI DASHCAM DILEMMA: The trucking industry is in the midst of a technological revolution, thanks to the arrival of artificial intelligence-powered dashcams. These innovative devices promise to make roads safer and operations more efficient, but they also raise some important questions about privacy. REAL 'THREAT': Americans looking to settle a divorce and obtain custody of their children could rack up unforeseen court costs by trying to disprove artificial intelligence (AI)-generated deepfake videos, photographs and documents, according to a leading family law attorney. FOLLOW FOX NEWS ON SOCIAL MEDIA FacebookInstagramYouTubeTwitterLinkedIn SIGN UP FOR OUR OTHER NEWSLETTERS Fox News FirstFox News OpinionFox News LifestyleFox News Health DOWNLOAD OUR APPS Fox NewsFox BusinessFox WeatherFox SportsTubi WATCH FOX NEWS ONLINE STREAM FOX NATION Stay up to date on the latest AI technology advancements and learn about the challenges and opportunities AI presents now and for the future with Fox News here.
Yahoo
18-03-2025
- Business
- Yahoo
NVIDIA Announces Major Release of Cosmos World Foundation Models and Physical AI Data Tools
NVIDIA Cosmos New Models Enable Prediction, Controllable World Generation and Reasoning for Physical AI Two New Blueprints Deliver Massive Physical AI Synthetic Data Generation for Robot and Autonomous Vehicle Post-Training 1X, Agility Robotics, Figure AI, Skild AI Among Early Adopters SAN JOSE, Calif., March 18, 2025 (GLOBE NEWSWIRE) -- GTC—NVIDIA today announced a major release of new NVIDIA Cosmos™ world foundation models (WFMs), introducing an open and fully customizable reasoning model for physical AI development and giving developers unprecedented control over world generation. NVIDIA is also launching two new blueprints — powered by the NVIDIA Omniverse™ and Cosmos platforms — that provide developers with massive, controllable synthetic data generation engines for post-training robots and autonomous vehicles. Industry leaders including 1X, Agility Robotics, Figure AI, Foretellix, Skild AI and Uber are among the first to adopt Cosmos to generate richer training data for physical AI faster and at scale. 'Just as large language models revolutionized generative and agentic AI, Cosmos world foundation models are a breakthrough for physical AI,' said Jensen Huang, founder and CEO of NVIDIA. 'Cosmos introduces an open and fully customizable reasoning model for physical AI and unlocks opportunities for step-function advances in robotics and the physical industries.' Cosmos Transfer for Synthetic Data GenerationCosmos Transfer WFMs ingest structured video inputs such as segmentation maps, depth maps, lidar scans, pose estimation maps and trajectory maps to generate controllable photoreal video outputs. Cosmos Transfer streamlines perception AI training, transforming 3D simulations or ground truth created in Omniverse into photorealistic videos for large-scale, controllable synthetic data generation. Agility Robotics will be an early adopter of Cosmos Transfer and Omniverse for large-scale synthetic data generation to train its robot models. 'Cosmos offers us an opportunity to scale our photorealistic training data beyond what we can feasibly collect in the real world,' said Pras Velagapudi, chief technology officer of Agility Robotics. 'We're excited to see what new performance we can unlock with the platform, while making the most use of the physics-based simulation data we already have.' The NVIDIA Omniverse Blueprint for autonomous vehicle simulation uses Cosmos Transfer to amplify variations of physically based sensor data. With the blueprint, Foretellix can enhance behavioral scenarios by varying conditions like weather and lighting for diverse driving datasets. Parallel Domain is also using the blueprint to apply similar variation to its sensor simulation. The NVIDIA GR00T Blueprint for synthetic manipulation motion generation combines Omniverse and Cosmos Transfer to generate diverse datasets at scale, benefiting from OpenUSD-powered simulations and reducing data collection and augmentation time from days to hours. Cosmos Predict for Intelligent World GenerationAnnounced at the CES trade show in January, Cosmos Predict WFMs generate virtual world states from multimodal inputs like text, images and video. New Cosmos Predict models will enable multi-frame generation, predicting intermediate actions or motion trajectories when given start and end input images. Purpose-built for post-training, these models can be customized using NVIDIA's openly available physical AI dataset. With the inference compute power of NVIDIA Grace Blackwell NVL72 systems and their large NVIDIA NVLink™ domain, developers can achieve real-time world generation. 1X is using Cosmos Predict and Cosmos Transfer to train its new humanoid robot NEO Gamma. Robot brain developer Skild AI is tapping into Cosmos Transfer to augment synthetic datasets for its robots. Plus, Nexar and Oxa are using Cosmos Predict to advance their autonomous driving systems. Multimodal Reasoning for Physical AI Cosmos Reason is an open, fully customizable WFM with spatiotemporal awareness that uses chain-of-thought reasoning to understand video data and predict the outcomes of interactions — such as a person stepping into a crosswalk or a box falling from a shelf — in natural language. Developers can use Cosmos Reason to improve physical AI data annotation and curation, enhance existing world foundation models or create new vision language action models. They can also post-train it to build high-level planners to tell the physical AI what it needs to do to complete a task. Accelerating Data Curation and Post-Training for Physical AIBased on their downstream task, developers can post-train Cosmos WFMs using native PyTorch scripts or the NVIDIA NeMo™ framework on NVIDIA DGX™ Cloud. Cosmos developers can also use NVIDIA NeMo Curator on DGX Cloud for accelerated data processing and curation. Linker Vision and Milestone Systems are using it for curating large amounts of video data to train large vision language models for visual agents built on the NVIDIA AI Blueprint for video search and summarization. Virtual Incision is exploring it to be deployed in future surgical robots, while Uber and Waabi are advancing autonomous vehicles development. Driving Responsible AI and Content TransparencyIn line with NVIDIA's trustworthy AI principles, NVIDIA enforces open guardrails across all Cosmos WFMs. In addition, NVIDIA is collaborating with Google DeepMind to integrate SynthID to watermark and help identify AI-generated outputs from the Cosmos WFM NVIDIA NIM™ microservice featured on AvailabilityCosmos WFMs are available for preview in the NVIDIA API catalog and now listed in the Vertex AI Model Garden on Google Cloud. Cosmos Predict and Cosmos Transfer are openly available on Hugging Face and GitHub. Cosmos Reason is available in early access. Learn more by watching the NVIDIA GTC keynote and by registering for Cosmos sessions and training from NVIDIA and industry leaders at the show, including 'An Introduction to Cosmos World Foundation Models' with Ming-Yu Liu, vice president of generative AI research at NVIDIA. About NVIDIANVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. For further information, contact:Paris Fox Corporate CommunicationsNVIDIA Corporation+1-408-242-0035pfox@ Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, availability, and performance of NVIDIA's products, services, and technologies; third parties adopting NVIDIA's products and technologies and the benefits and impact thereof; and Cosmos opening opportunities for step-function advances in robotics and the physical industries are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. © 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, NVIDIA Cosmos, NVIDIA DGX, NVIDIA NeMo, NVIDIA NIM, NVIDIA Omniverse and NVLink are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice. A photo accompanying this announcement is available at
