News from the AI & ML world
DeeperML - #nvidiaai
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Cierra Choucair@The Quantum Insider
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Nvidia CEO Jensen Huang unveiled the company's latest advancements in AI and quantum computing at GTC 2025, emphasizing a clear roadmap for data center computing, AI reasoning, robotics, and autonomous vehicles. The centerpiece was the Blackwell platform, now in full production, boasting a 40x performance leap over its predecessor, Hopper, crucial for inference workloads. Nvidia is also countering the DeepSeek efficiency challenge, with focus on the Rubin AI chips slated for late 2026.
Nvidia is establishing the NVIDIA Accelerated Quantum Research Center (NVAQC) in Boston to integrate quantum hardware with AI supercomputers. The center will collaborate with industry leaders and top universities to address quantum computing challenges. NVAQC is set to begin operations later this year, supporting the broader quantum ecosystem by accelerating the transition from experimental to practical quantum computing. NVAQC will employ the NVIDIA GB200 NVL72 systems and CUDA-Q platform to power research on quantum simulations, hybrid quantum algorithms, and AI-driven quantum applications. Recommended read:
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James McKenna@NVIDIA Newsroom
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NVIDIA Newsroom
, NVIDIA Technical Blog
NVIDIA's Omniverse platform is gaining traction within industrial ecosystems as companies leverage digital twins to train physical AI. The Mega NVIDIA Omniverse Blueprint, now available in preview, empowers industrial enterprises to accelerate the development, testing, and deployment of physical AI. This blueprint provides a reference workflow for combining sensor simulation and synthetic data generation, enabling the simulation of complex human-robot interactions and verification of autonomous systems within industrial digital twins.
At Hannover Messe, leaders from manufacturing, warehousing, and supply chain sectors are showcasing their adoption of the blueprint to simulate robots like Digit from Agility Robotics. They are also demonstrating how industrial AI and digital twins can be used to optimize facility layouts, material flow, and collaboration between humans and robots. NVIDIA ecosystem partners like Delta Electronics, Rockwell Automation, and Siemens are also announcing further integrations with NVIDIA Omniverse and NVIDIA AI technologies at the event, further solidifying Omniverse's role in physical AI development. Recommended read:
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Ellie Ramirez-Camara@Data Phoenix
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Nvidia is making significant strides in the realm of AI agents, highlighted at this year's GTC 2025 conference. CEO Jensen Huang emphasized the transformative impact of agentic AI and reasoning models, predicting that these technologies will revolutionize industries and automate processes. To support this shift, Nvidia unveiled the Blackwell Ultra platform, designed to handle the demanding requirements of AI reasoning, agentic AI, and physical AI applications. The platform, which includes the GB300 NVL72 rack-scale solution and the HGX B300 NVL16 system, offers substantial performance improvements over previous generations, with the GB300 NVL72 delivering 1.5x more AI performance.
In addition to hardware advancements, Nvidia launched NVIDIA Dynamo, an open-source inference framework, to optimize reasoning AI services across thousands of GPUs. This framework is designed to maximize token revenue generation for AI factories deploying reasoning AI models by orchestrating and accelerating inference communication across GPU clusters. Major cloud providers and server manufacturers are expected to offer Blackwell Ultra-based products starting in the second half of 2025. These developments position Nvidia as a key player in the emerging landscape of AI agents and reasoning models, promising to drive significant advancements in AI capabilities and applications. Recommended read:
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Charlene Chen@digitimes.com
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Pivot to AI
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Nvidia is making significant strides in both gaming and artificial intelligence. At CES 2025, CEO Jensen Huang stated that "very useful" quantum computers are still about 20 years away. He also acknowledged the impressive advancements in autonomous driving technology by Chinese automakers such as BYD, Nio, Xiaomi, and XPeng. In terms of gaming, Nvidia has unveiled its new RTX 50 series GPUs including the flagship RTX 5090, which boasts AI-juiced frame rates. These new GPUs promise significant performance improvements especially when using AI-based technologies like DLSS 4 and multi-frame generation, although actual performance gains may be more modest in non-AI supported games.
Nvidia is also pushing boundaries in AI computing. The company is partnering with Microsoft to enable Windows 11 PCs to run AI models from Nvidia NIM and Azure AI Foundry using their GPUs. This allows for the running of AI models on the edge. Furthermore, Nvidia announced a $3000 personal AI supercomputer called Digits, demonstrating their intention to make AI more accessible for home users. These initiatives, along with the new GPUs, underline Nvidia’s continued commitment to pushing the limits of both AI and gaming technologies. Recommended read:
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Hassan Shittu@Fello AI
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Fello AI
, lambdalabs.com
Nvidia is making significant strides in healthcare and AI infrastructure, particularly through the development of specialized large language models (LLMs). Their DNA LLM exemplifies this, aiming to revolutionize genomic research and drug discovery. This highlights AI's potential to transform medical science by enabling faster analysis and interpretation of biological data.
Lambda has been recognized as NVIDIA's 2025 Healthcare Partner of the Year for accelerating AI innovation in healthcare and biotech. John Snow Labs introduced the first commercially available Medical Reasoning LLM at NVIDIA GTC, optimized for clinical reasoning and capable of verbalizing its thought processes. Nvidia's involvement in this has helped lead the way for these healthcare specific Large Language Models. Recommended read:
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@analyticsindiamag.com
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www.digitimes.com
, analyticsindiamag.com
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Nvidia is aggressively expanding its presence in the robotics sector, highlighted by the development of its Jetson Thor computing platform. This platform is designed to replicate Nvidia’s success in AI chips and is a core component of their strategy to develop advanced humanoid robots. Furthermore, Nvidia is not working alone in this endeavor. They have partnered with Foxconn to create humanoid robots, aiming to move beyond just manufacturing and integrate into new tech areas. This strategic move demonstrates Nvidia’s focus on becoming a dominant player in AI-driven robotics, specifically for humanoid technology.
Nvidia is also addressing the challenge of training these robots through their Isaac GR00T Blueprint, unveiled at CES. This blueprint utilizes synthetic data generation to create the extensive datasets needed for imitation learning, allowing robots to mimic human actions. A new workflow uses Apple Vision Pro to capture human actions in a digital twin and the data is used in the Isaac Lab framework, which teaches robots to move and interact safely. Nvidia’s Cosmos platform also is in use by generating physics-aware videos that are also used to train robots. The company's CEO, Jensen Huang, emphasizes humanoid robots as the next big leap in AI innovation, aiming to establish Nvidia as a key player in the future of robotics and autonomous systems. Recommended read:
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Charlene Chen@digitimes.com
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blogs.nvidia.com
, analyticsindiamag.com
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Nvidia is significantly advancing its role in humanoid robotics through its Jetson Thor platform, aiming to replicate its AI chip success. CEO Jensen Huang has identified humanoid robots as a key area for large-scale production. To further this goal, Nvidia is releasing Isaac GR00T Blueprint which helps with generating training data for humanoid robots. This blueprint leverages workflows for synthetic data creation and simulation, and includes tools like the GR00T-Teleop, GR00T-Mimic and GR00T-Gen to generate large training datasets for robots to learn imitation skills. The company is also releasing a collection of robot foundation models and data pipelines to accelerate development.
Foxconn is partnering with Nvidia to develop humanoid robot services, integrating Nvidia's advanced software and hardware in Kaohsiung City, Taiwan. This partnership marks a significant move for Foxconn to diversify beyond contract manufacturing in electronics, with plans to collaborate on smart city projects. Additionally, Taiwan is building a supercomputer based on NVIDIA’s Blackwell architecture, further emphasizing the island's commitment to AI advancement and robotic capabilities. NVIDIA's Jetson Thor computing system, debuting in early 2025, will be central to this endeavor. The company's actions highlight a broader trend towards embodied AI. Recommended read:
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Walter Sun@SAP News Center
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SAP News Center
SAP and NVIDIA are deepening their collaboration to deliver advanced AI capabilities to businesses worldwide. SAP is integrating NVIDIA's Llama Nemotron reasoning models to enhance the reasoning capabilities of its AI agents. This strategic move aims to improve accuracy and equip AI agents with advanced decision-making and execution skills. By incorporating these models, SAP's Joule agents will be better equipped to handle complex business challenges through deeper contextual reasoning and seamless interaction with enterprise data and systems, fostering more intelligent and autonomous operations.
The partnership between SAP and NVIDIA has already yielded AI innovations transforming business operations. SAP Joule for Consultants, enhanced with NVIDIA NeMo Retriever microservices, enables consultants to quickly access relevant insights from SAP-exclusive content, reducing time spent on documentation and troubleshooting. For developers, Joule for developers, powered by NVIDIA NIM microservices, accelerates ABAP code generation, improving code quality and accelerating innovation. These advancements are revolutionizing how enterprises implement SAP solutions and develop applications on SAP Business Technology Platform. Recommended read:
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