Articles tagged with "NVIDIA"
Does Tesla Need Another Year of Self-Driving Training? New Elon Musk Prediction After HUGE Prediction Miss - CleanTechnica
The article discusses Elon Musk's recent and somewhat puzzling statement regarding the timeline for achieving fully autonomous self-driving capabilities, particularly in relation to Tesla's progress and NVIDIA’s ambitions in the autonomous driving space. Musk emphasized that roughly 10 billion miles of training data are needed to achieve safe unsupervised self-driving, highlighting the complexity of real-world driving scenarios. Tesla has logged nearly 7.3 billion Full Self-Driving (FSD) miles as of late 2025, and based on recent data accumulation rates, reaching 10 billion miles could take another 6 to 12 months. However, Musk’s past predictions, such as the claim that Tesla’s Robotaxi network would cover half the U.S. population by the end of 2025, have not materialized, underscoring the need for caution when interpreting his optimistic timelines. The article raises critical questions about the nature and quality of the 10 billion miles Musk references—whether these miles represent fully autonomous driving, limited intervention scenarios
robotautonomous-vehiclesself-driving-technologyTeslaAI-training-dataNVIDIArobotaxiUK lab’s humanoid robots get NVIDIA grant to turn sound into motion
Chengxu Zhou, an associate professor at UCL Computer Science, has received an NVIDIA Academic Grant to advance his research on real-time, audio-driven whole-body motion for humanoid robots. The grant provides critical resources, including two NVIDIA RTX PRO 6000 GPUs and two Jetson AGX Orin devices, which will accelerate training and deployment cycles by enabling faster iteration and reducing the gap between simulation and real-robot testing. Zhou’s project, called Beat-to-Body, aims to develop humanoid robots that respond dynamically to audio cues such as tempo, accents, and loudness fluctuations, allowing them to adapt their movements in real time rather than following pre-scripted commands. The Beat-to-Body system leverages large-scale simulation training with GPU compute and low-latency inference directly on the robot, minimizing dependence on offboard processing and enhancing responsiveness to sound. This approach aligns with recent research demonstrating that robots can generate expressive locomotion and gestures from music and speech without predefined motion templates, and
roboticshumanoid-robotsNVIDIAmachine-learningreal-time-motionaudio-driven-controlhuman-robot-interactionNVIDIA can now sell AI chips to China as US eases export rules
The U.S. Commerce Department has eased export restrictions on advanced AI chips to China, allowing companies like NVIDIA and AMD to apply for licenses to sell certain high-performance processors under strict conditions. This marks a significant shift from previous policies that largely rejected such exports outright. Under the new rules, chipmakers can seek approval to export processors like NVIDIA’s H200 and AMD’s MI325X on a case-by-case basis, provided they demonstrate no shortage of supply in the U.S. and certify that shipments will not detract from domestic needs. The policy also applies to Macau and restricts eligibility to chips below specific performance thresholds, while explicitly barring exports for military, intelligence, or weapons-related uses. The revised framework further limits exports to no more than 50% of the volume shipped domestically and requires rigorous customer verification and independent third-party testing before shipment. This approach aims to prevent advanced U.S. AI technology from enhancing China’s defense or intelligence capabilities while cautiously reopening commercial access. NVIDIA’s H200
AI-chipssemiconductor-export-controlsNVIDIAadvanced-processorsUS-China-technology-tradeAI-hardwarechip-manufacturingMercedes Launches Parking Lot to Destination Driver Assist in USA - CleanTechnica
Mercedes has introduced its MB.DRIVE ASSIST PRO, an SAE-Level 2 driver-assist system, in the United States starting with the new electric CLA model. This technology integrates advanced driver assistance with navigation, enabling the vehicle to assist with driving from parking lots to destinations in city environments. The system features a cooperative steering approach that allows steering adjustments without deactivating the assistance, enhancing safety and convenience. The MB.DRIVE ASSIST PRO leverages a sophisticated sensor suite comprising 30 sensors, including 10 cameras, 5 radar sensors, and 12 ultrasonic sensors, feeding data into a powerful NVIDIA AI-powered supercomputer capable of 508 TOPs (trillions of operations per second). Developed in partnership with NVIDIA, the system uses full-stack software to deliver its capabilities. Notably, this technology was first launched in China at the end of 2023 before its rollout in the U.S. later in 2024. While its performance relative to Tesla’s Full Self-
robotautonomous-drivingdriver-assist-technologysensorsAINVIDIAelectric-vehiclesSiemens, NVIDIA outline roadmap for AI-driven factories at CES 2026
At CES 2026, Siemens and NVIDIA announced an expanded partnership to develop an Industrial AI Operating System aimed at embedding artificial intelligence throughout the entire industrial lifecycle—from design and engineering to manufacturing, operations, and supply chains. This platform will enable factories to simulate process changes virtually, test improvements in real time, and apply validated insights directly on the shop floor. The first fully AI-driven, adaptive manufacturing site using this system is planned for 2026 at Siemens Electronics Factory in Erlangen, Germany. NVIDIA will supply AI infrastructure, simulation libraries, and frameworks, while Siemens will contribute industrial AI expertise alongside its hardware and software offerings. Together, they aim to create AI-native workflows that accelerate innovation, reduce costs and risks, and shorten commissioning times. Central to the initiative is the use of continuously analyzing digital twins powered by an AI Brain combining software-defined automation, industrial operations software, and NVIDIA Omniverse libraries. This approach allows factories to test and optimize processes virtually before real-world implementation, improving decision-making speed and
robotAIindustrial-automationdigital-twinsmanufacturing-technologysimulationNVIDIACES 2026: NVIDIA launches Alpamayo 1 for autonomous vehicles
At CES 2026, NVIDIA announced a significant expansion of its open AI ecosystem, unveiling new models, datasets, and development tools aimed at advancing AI applications beyond digital tasks into physical environments such as autonomous vehicles, robotics, and biomedical research. Central to the announcement was the introduction of Alpamayo, a family of open models and tools for reasoning-based autonomous driving. Alpamayo 1, an open vision language action model, enables vehicles to perceive their surroundings and explain their decisions. Complementing this, NVIDIA launched AlpaSim, an open-source simulation framework for training and evaluating autonomous systems, along with Physical AI Open Datasets containing over 1,700 hours of diverse driving data. NVIDIA’s expanded portfolio also includes open models across multiple domains: Nemotron for agentic AI, Cosmos for physical AI, Isaac GR00T for robotics, and Clara for healthcare and life sciences. The company released extensive datasets, including 10 trillion language tokens, 500,000 robotics trajectories, 455
roboticsautonomous-vehiclesAIsimulation-toolsphysical-AINVIDIAopen-datasetsNVIDIA eyes $20 billion Groq deal as AI chip race grows, report says
NVIDIA has agreed to acquire AI chip startup Groq in a cash deal valued at $20 billion, marking the largest acquisition in NVIDIA’s history and significantly expanding its presence in specialized AI accelerator hardware. The deal follows Groq’s recent $750 million funding round at a $6.9 billion valuation, which included major investors such as BlackRock, Samsung, and Cisco. The acquisition covers Groq’s core assets but excludes its Groq Cloud business. Groq, founded in 2016 by former Google engineers including CEO Jonathan Ross, focuses on low-latency inference chips designed to accelerate large language model tasks, positioning itself as a challenger to NVIDIA’s GPUs and Google’s TPUs. This acquisition underscores NVIDIA’s broader strategy to deepen its influence across the AI hardware ecosystem amid growing demand for AI inference hardware. NVIDIA’s cash reserves have grown substantially, reaching $60.6 billion by October 2023, enabling aggressive investments and partnerships, including a planned $100 billion investment in OpenAI and
energyAI-chipsNVIDIAGroqsemiconductorAI-hardwareaccelerator-technologyMassRobotics expands physical AI fellowship with AWS and NVIDIA - The Robot Report
MassRobotics, in partnership with Amazon Web Services (AWS) and NVIDIA Inception, has launched applications for the second cohort of its Physical AI Fellowship, an eight-week virtual program designed to help robotics and physical AI startups scale their innovations. The fellowship aims to advance the integration of artificial intelligence with robotics to create smart machines capable of understanding and interacting with the physical world. Selected startups will benefit from access to MassRobotics’ global network, AWS’s AI stack and up to $200,000 in AWS credits, as well as NVIDIA’s robotics software and expert mentorship. The program builds on the success of the inaugural 2025 cohort, where eight startups received tailored technical support to accelerate innovation in areas such as foundation model development, simulation optimization, and edge deployment. These companies worked on diverse applications ranging from autonomous construction equipment and ocean vessels to hospital service robots and robotic exoskeletons. The fellowship partners emphasize that the collaboration helps translate complex AI research into practical robotics solutions that address real-world business challenges
roboticsartificial-intelligencephysical-AIAWSNVIDIAstartupstechnology-innovationHyundai Motor Group Announces NVIDIA Blackwell AI Factory to Power Fleet of AI-Driven Mobility Solutions - CleanTechnica
Hyundai Motor Group and NVIDIA have announced a deepened collaboration to establish an AI factory powered by NVIDIA’s Blackwell AI infrastructure, aimed at accelerating innovation in autonomous vehicles, smart factories, and robotics. This partnership involves co-developing core physical AI technologies and integrated AI model training, validation, and deployment using 50,000 NVIDIA Blackwell GPUs. The initiative supports the Korean government’s plan to build a national physical AI cluster, with a combined investment of approximately $3 billion to advance Korea’s AI ecosystem. Key projects include the creation of Hyundai’s Physical AI Application Center, NVIDIA AI Technology Center, and physical AI data centers, alongside efforts to nurture local AI talent through collaboration with NVIDIA’s engineers. The collaboration builds on previous joint efforts and marks a shift from adopting advanced AI software to innovating physical AI technologies for mobility solutions and next-generation manufacturing. Hyundai is leveraging NVIDIA’s Omniverse and Cosmos platforms to develop digital twins of car factories and robotics, while utilizing NVIDIA Nemotron and NeMo
robotAIautonomous-vehiclessmart-factoriesNVIDIAHyundai-Motor-Groupmobility-solutionsNVIDIA, Oracle team up to build US’ biggest AI supercomputer
NVIDIA and Oracle have partnered with the U.S. Department of Energy (DOE) to build the nation’s largest AI supercomputer, named Solstice, featuring 100,000 NVIDIA Blackwell GPUs. Alongside Solstice, a companion system called Equinox with 10,000 GPUs will also be deployed at Argonne National Laboratory. Together, these systems will deliver a combined 2,200 exaflops of AI performance, making them the most powerful AI infrastructure developed for the DOE. They aim to accelerate scientific research and innovation across diverse fields such as climate science, healthcare, materials science, and national security by enabling researchers to train advanced AI models using NVIDIA’s Megatron-Core library and TensorRT inference software. This initiative is part of the DOE’s public-private partnership model to reinforce U.S. technological leadership in AI and supercomputing. The collaboration is expected to enhance R&D productivity and foster breakthroughs by integrating these supercomputers with DOE experimental facilities like the Advanced Photon Source. Oracle
energysupercomputerAIDepartment-of-EnergyNVIDIAOraclescientific-researchNVIDIA Now Working On Its Own Robotaxis - CleanTechnica
NVIDIA, long a key hardware and software provider for autonomous vehicle developers, is now reportedly developing its own robotaxi service. The company has supported numerous automakers and robotaxi firms—including Cruise, Zoox, DiDi, Pony.ai, and AutoX—by supplying its DRIVE AGX platform and acquiring mapping specialist DeepMap to enhance its full self-driving capabilities. Over the past several years, the robotaxi market has matured significantly, with companies like Waymo and various Chinese operators running commercial services in multiple cities. Building on its extensive experience and partnerships with automakers such as BYD, Jaguar Land Rover, Lucid, Mercedes-Benz, Rivian, Tesla, and others, NVIDIA is leveraging its DRIVE AGX Thor system and continuous neural networks to develop a proprietary robotaxi system. The project, reportedly led by Ruchi Bhargava and announced internally at an all-hands meeting, reflects CEO Jensen Huang’s belief that robotaxis represent a trillion-dollar opportunity and the first major commercial application of robotics
robotautonomous-vehiclesrobotaxisNVIDIAself-driving-technologyAIautomotive-technologyNVIDIA launches Newton physics engine and GR00T AI at CoRL 2025 - The Robot Report
NVIDIA has introduced several advancements to accelerate robotics research, unveiling the beta release of Newton, an open-source, GPU-accelerated physics engine managed by the Linux Foundation. Developed collaboratively with Google DeepMind and Disney Research, Newton is built on NVIDIA’s Warp and OpenUSD frameworks and is designed to simulate physical AI bodies. Alongside Newton, NVIDIA announced the latest version of the Isaac GR00T N1.6 robot foundation model, soon to be available on Hugging Face. This model integrates Cosmos Reason, an open, customizable vision language model (VLM) that enables robots to convert vague instructions into detailed plans by leveraging prior knowledge, common sense, and physics, thus enhancing robots’ ability to reason, adapt, and generalize across tasks. At the Conference on Robot Learning (CoRL) 2025 in Seoul, NVIDIA highlighted Cosmos Reason’s role in enabling robots to handle ambiguous or novel instructions through multi-step inference and AI reasoning, akin to how language models process text. This capability is
roboticsAIphysics-engineNVIDIArobot-simulationmachine-learningIsaac-GR00TAWS, NVIDIA, and MassRobotics pick Diligent for first Physical AI Fellowship cohort - The Robot Report
MassRobotics, AWS, and NVIDIA have launched the Physical AI Fellowship to support startups integrating robotics and artificial intelligence for practical applications. Diligent Robotics, known for its AI-native mobile manipulator robot Moxi, was selected for the inaugural cohort. Moxi assists nurses in over 25 U.S. hospitals by performing routine tasks like medication and lab sample delivery, saving nearly 600,000 staff hours and completing over 1 million tasks. The fellowship offers Diligent Robotics $200,000 in AWS cloud credits, access to NVIDIA platforms and Deep Learning Institute resources, and support from MassRobotics’ testbed and ecosystem, aiming to accelerate development of autonomous humanoid robots and enhance Moxi’s intelligence layer. The Physical AI Fellowship is designed to fast-track startups building intelligent physical systems by providing technical guidance, hardware, and global networking opportunities. The program will culminate in showcases at major events including AWS re:Invent 2025. Diligent Robotics plans to use the fellowship to expand
roboticsartificial-intelligenceautomationhealthcare-robotsphysical-AIAWSNVIDIANVIDIA investing $100B in OpenAI data centers for next-gen AI
OpenAI and NVIDIA have entered a landmark partnership, with NVIDIA committing up to $100 billion to build massive AI data centers that will deploy at least 10 gigawatts of compute power using millions of NVIDIA GPUs. The first gigawatt of this capacity is expected to go live in the second half of 2026 on NVIDIA’s upcoming Vera Rubin platform. NVIDIA CEO Jensen Huang described the collaboration as a “next leap forward” for both companies, highlighting that the 10 gigawatts equate to roughly 4 to 5 million GPUs—double the number shipped by NVIDIA last year. This massive infrastructure investment underscores the deep ties between the two companies and their joint efforts to power the next era of AI intelligence. OpenAI CEO Sam Altman emphasized that compute infrastructure is central to OpenAI’s mission and will form the foundation of the future economy. He noted the challenge of balancing research, product development, and scaling infrastructure, promising significant developments in the coming months. OpenAI cofounder Greg
energydata-centersAI-infrastructureNVIDIAOpenAIGPUscompute-powerNVIDIA invests $5B in Intel, launches joint AI and PC chip venture
NVIDIA is investing $5 billion in Intel, becoming one of its largest shareholders and forming a strategic partnership to jointly develop future data center and PC chips. This collaboration aims to combine Intel’s x86 CPU architecture with NVIDIA’s AI and GPU technologies, with Intel building custom CPUs for NVIDIA’s AI infrastructure and manufacturing x86 system-on-chips integrated with NVIDIA RTX GPU chiplets for high-performance personal computers. The deal provides a significant boost to Intel, which has struggled in recent years, as evidenced by a 23% surge in its stock price following the announcement. The partnership leverages the strengths of both companies: Intel’s foundational x86 architecture, manufacturing capabilities, and advanced packaging, alongside NVIDIA’s AI leadership and CUDA architecture. Analysts view NVIDIA’s involvement as a pivotal moment for Intel, repositioning it from an AI laggard to a key player in AI infrastructure. The collaboration also has competitive implications, potentially challenging rivals like AMD and TSMC, which currently manufactures NVIDIA’s top processors. The
semiconductorsAI-chipsNVIDIAInteldata-centersPC-processorsAI-infrastructureNuro closes $203M to propel AI-first self-driving tech, commercial partnerships - The Robot Report
Nuro Inc., a Mountain View-based autonomous vehicle company, has closed a $203 million Series E funding round at a $6 billion valuation. The capital will be used to scale its AI-first autonomous driving technology and expand commercial partnerships. Founded in 2016, Nuro combines advanced artificial intelligence with automotive-grade hardware to offer its Nuro Driver system, which supports applications including robotaxis, commercial fleets, and personally owned vehicles. The company has deployed its autonomous vehicles at city scale without safety drivers across multiple U.S. states and internationally, including a recent test fleet in Japan. Key commercial partnerships highlighted include a collaboration with Lucid and Uber to launch a next-generation ride-hailing service, aiming to deploy over 20,000 Lucid vehicles integrated with Nuro Driver starting in 2026. Uber also invested in Nuro as part of this funding round, contingent on meeting development milestones. Investors in the round include returning backers Baillie Gifford and NVIDIA—whose DRIVE AGX
robotautonomous-vehiclesAIself-driving-technologyNuroNVIDIAcommercial-partnershipsNVIDIA, NSF invest $150M in open AI to turbocharge US science
NVIDIA and the U.S. National Science Foundation (NSF) have jointly committed over $150 million to develop open, multimodal AI models aimed at accelerating scientific discovery and maintaining U.S. leadership in AI-driven research. This partnership supports the Open Multimodal AI Infrastructure to Accelerate Science (OMAI) project, led by the Allen Institute for AI (Ai2). The NSF is contributing $75 million, while NVIDIA provides $77 million in advanced technology, including NVIDIA HGX B300 systems with Blackwell Ultra GPUs and the NVIDIA AI Enterprise software platform. These resources are designed to handle large-scale AI workloads, enabling faster model training and inference. OMAI will produce a fully open suite of large language models capable of processing diverse scientific data types such as text, images, graphs, and tables. These models will help researchers analyze data more rapidly, generate code and visualizations, and link new insights to existing knowledge, with applications ranging from material discovery to protein function prediction. All models,
AIscientific-researchmaterials-discoveryNVIDIANSFmultimodal-AI-modelsopen-source-AISmuggled NVIDIA chips flood China despite US export crackdown
A Financial Times investigation reveals that despite the U.S. government's export controls introduced in April 2025 banning NVIDIA’s China-specific H20 AI chips, over $1 billion worth of smuggled NVIDIA B200 and other restricted chips have flooded the Chinese market. These chips are openly sold on Chinese social media platforms like Douyin and Xiaohongshu, often alongside other high-end NVIDIA products, and are purchased by local data center suppliers serving major AI firms. The black market emerged rapidly after the export ban, with sellers even promising access to next-generation B300 chips ahead of official launches. NVIDIA maintains that it does not sell restricted chips to Chinese customers and does not support unauthorized deployments, emphasizing that datacenters require official service and support. CEO Jensen Huang has downplayed the extent of chip diversion and criticized export controls as ineffective, arguing they may accelerate China’s independent AI hardware development, potentially undermining U.S. leadership. The U.S. government is pressuring allies like Singapore, where arrests
semiconductorAI-chipsNVIDIAexport-controlsblack-marketdata-centerschip-smugglingNEXCOM NexCOBOT unit joins NVIDIA Halos AI Systems Inspection Lab - The Robot Report
NEXCOM Group’s NexCOBOT unit has joined NVIDIA’s Halos AI Systems Inspection Lab to collaboratively advance the safe development of humanoid and AI robots. This partnership aims to streamline the complex and resource-intensive process of achieving functional safety certifications for robotic systems. NexCOBOT, specializing in safe robot controls and based in New Taipei City with offices in Fremont, California, will integrate its products with NVIDIA’s IGX Thor platform and the expanded Halos platform. This integration is designed to create a unified development environment that encompasses AI, motion control, and functional safety, thereby accelerating innovation and simplifying robot design verification and certification processes. NVIDIA’s Halos AI Systems Inspection Lab is notable as the first ANSI National Accreditation Board (ANAB)-accredited lab that combines functional safety, cybersecurity, AI, and regulatory compliance into a single safety framework. NexCOBOT’s participation reflects its long-standing commitment to functional safety, leveraging international standards such as IEC 61508 and ISO 13849-1 to help
robotAIfunctional-safetyroboticsNVIDIAmotion-controlhumanoid-robotsMIT-NVIDIA create robot tech that plans thousands of moves in secs
robotroboticsalgorithmtask-planningmotion-planningindustrial-automationNVIDIANVIDIA releases cloud-to-robot computing platforms for physical AI, humanoid development - The Robot Report
robothumanoidAINVIDIAroboticsautomationphysical-AI