Everything Nvidia Announced At Gtc 2025 Groundbreaking Ai Gpu And

Bonisiwe Shabane

-Jan 2, 2026, 10:55 AM

everything nvidia announced at gtc 2025 groundbreaking ai gpu and

Here are the major points NVIDIA founder and CEO Jensen Huang covered in his keynote: NVIDIA is diving deeper into quantum computing with plans to open a dedicated research lab in Boston, founder and CEO Jensen Huang announced Thursday as he kicked off a series of panels at GTC... “It will likely be the most advanced accelerated computing, hybrid quantum computing research lab in the world,” Huang said. The panels at GTC’s inaugural Quantum Day highlighted the critical role accelerated computing will play in advancing the nascent technology. While technologies and approaches to quantum development vary, panelists agreed that GPUs and quantum systems will work hand in hand to unlock new breakthroughs. Charting the Future of Data Center, Cloud, and AI Infrastructure

Last month's NVIDIA GTC 2025 saw the expected announcement of next-generation products in the AI GPU/CPU market that Nvidia has been dominating, if not defining, for the last few years. Interestingly enough, the message for these future generations of product was focused not just on “bigger and better,” but also, “do more and work with your existing hardware investment” - not that future improvements... At GTC 2024, Nvidia introduced their first generation Blackwell GPU architecture designed for AI. The revolutionary GPU offered breakthroughs in accelerated computing, AI inference, ray tracing, and neural rendering, and was suitable for AI models with as many as a trillion parameters. At GTC 2025, the Blackwell follow-on was announced, the Blackwell Ultra Architecture. This new architecture adds performance, efficiency, and security to the existing Blackwell model, including:

InfoQ Homepage News Nvidia Unveils AI, GPU, and Quantum Computing Innovations at GTC 2025 Nvidia presented a range of new technologies at its GTC 2025 event, focusing on advancements in GPUs, AI infrastructure, robotics, and quantum computing. The company introduced the GeForce RTX 5090, a graphics card built on the Blackwell architecture, featuring improvements in energy efficiency, size reduction, and AI-assisted rendering capabilities. Nvidia highlighted the increasing role of AI in real-time, path-traced rendering and GPU performance optimization. In the data center sector, Nvidia announced the Blackwell Ultra GB300 family of GPUs, designed to enhance AI inference efficiency with 1.5 times the memory capacity of previous models. The company also introduced MVLink, a high-speed interconnect technology that enables faster GPU communication, and Nvidia Dynamo, an AI data center operating system aimed at improving management and efficiency.

The DGX Station, a computing platform for AI workloads, was also unveiled to support enterprise AI development. Nvidia’s automotive division revealed a partnership with General Motors to develop AI-powered self-driving vehicles. The company stated that all software components involved in the project have undergone rigorous safety assessments. Additionally, Nvidia introduced Halos, an AI-powered safety system for autonomous vehicles, integrating hardware, software, and AI-based decision-making. In robotics, Nvidia introduced the Isaac GR00T N1, an open-source humanoid reasoning model developed in collaboration with Google DeepMind and Disney Research. The Newton physics engine, also open-source, was announced to enhance robotics training by simulating real-world physics for AI-driven robots.

Nvidia also expanded its Omniverse platform for physical AI applications with the launch of Cosmos, a generative model aimed at improving AI-driven world simulation and interaction. NVIDIA’s GPU Technology Conference (GTC) 2025 has once again set the stage for groundbreaking advancements in artificial intelligence, gaming, and high-performance computing. Led by CEO Jensen Huang, this year’s keynote introduced a series of innovations that could reshape the future of AI-powered technologies. As the tech world eagerly watched, the announcements at GTC 2025 provided insights into NVIDIA’s long-term vision and its expanding dominance in the AI industry. The NVIDIA GPU Technology Conference (GTC) is an annual event where the company unveils its latest breakthroughs in AI, gaming, data centers, and cloud computing. It serves as a platform for researchers, developers, and businesses to explore how NVIDIA’s GPUs and AI solutions are driving the next generation of computing.

As the driving force behind NVIDIA, Jensen Huang used the GTC 2025 keynote to emphasize the company’s mission to advance AI-driven innovation. His speech focused on AI’s expanding role across industries and how NVIDIA’s latest technologies will shape the future. This year’s GTC covered several crucial topics: One of the most exciting parts of GTC 2025 was the unveiling of next-generation AI hardware and software that promise to redefine computing power. NVIDIA’s GPU Technology Conference (GTC) 2025 is one of the most anticipated tech events, bringing together industry leaders, AI researchers, developers, and enterprises to explore the latest advancements in AI, deep learning, cloud computing,... Led by NVIDIA CEO Jensen Huang, the keynote showcased groundbreaking innovations in AI, data centers, autonomous systems, and gaming technologies.

This year’s event was particularly crucial as AI adoption is accelerating across industries. With the rise of AI-driven applications, generative AI, and high-performance computing, NVIDIA is expected to introduce next-generation GPUs and cutting-edge AI frameworks that will define the future of computing. Whether you’re a developer, researcher, or tech enthusiast, this event has definitely provided insights into the technologies shaping the future. Below are the main highlights that you simply must not miss: Newton is an advanced open-source physics engine developed collaboratively by NVIDIA, Google DeepMind, and Disney Research. Announced at NVIDIA GTC 2025, Newton is designed to enhance robotics simulation, AI training, and real-world physics modeling, making it a powerful tool for developing intelligent humanoid robots and autonomous systems.

Newton enables real-time physics simulations with features such as rigid body dynamics, soft body simulations, and articulated joints, allowing developers to test robotic behaviors in a virtual environment before deploying them in the real... This reduces the need for expensive physical prototypes and accelerates innovation in robotic control, reinforcement learning, and AI-driven automation. On March 18, 2025, NVIDIA’s CEO Jensen Huang took the stage at the SAP Center in San Jose, California, to deliver a highly anticipated keynote at the NVIDIA GTC 2025 conference. Dubbed the “Super Bowl of AI,” this year’s event lived up to its reputation, with Huang unveiling a slew of groundbreaking advancements in AI, robotics, and accelerated computing. As expected, GTC 2025, the world’s premier AI conference, brought together thousands of innovators, developers, and industry leaders to witness NVIDIA’s vision for the future. With that in mind, here’s a rundown of the key announcements that stole the show.

The keynote began with a deep dive into Nvidia’s hardware advancements, focusing on the Blackwell architecture and its successors. A key theme of the keynote was the rise of “physical AI,” which aims to imbue AI systems with a deeper understanding of the physical world. Nvidia is not just a hardware company; it’s also a software powerhouse, providing developers with the tools they need to build and deploy AI applications. NVIDIA’s GPU Technology Conference (GTC) 2025 showcased a sweeping range of AI innovations – from data center supercomputing breakthroughs to robotics, healthcare, and creative applications. This recap expands on the original highlights with deeper insight into real-world use cases demonstrated at GTC, a summary of major announcements (hardware, software platforms, and ecosystem updates), and practical advice for developers looking... GTC 2025’s keynote by CEO Jensen Huang was packed with news that underscores an inflection point in AI computing.

Key announcements included: One of the most prominent themes at GTC 2025 was the impact of AI in healthcare and life sciences. Over 700 healthcare and biotech companies gathered to share breakthroughs, and NVIDIA announced new platforms to accelerate everything from drug discovery to clinical robotics. AI is transforming medicine: NVIDIA’s new Isaac AMR (Autonomous Mobile Robotics) platform is helping develop intelligent robots for healthcare, such as robotic assistants and autonomous imaging devices in hospitals. The image shows a simulated robotic arm performing an ultrasound scan on a patient – one example of how AI-driven robots can assist medical professionals in the near future.* Drug Discovery and Biology: NVIDIA’s BioNeMo platform received significant updates, underscoring how generative AI and large language models are expediting pharmaceutical research.

BioNeMo provides domain-specific AI models for chemistry and biology – at GTC, partners demonstrated how these models are being used in practice. For instance, software firm Sapio Sciences announced integration of BioNeMo’s services into their lab informatics software, allowing researchers to invoke AI models as-a-service for tasks like protein structure prediction and molecule design. This includes models like AlphaFold2 NIM (for protein folding), MoI (Molecule Optimizer) NIM for small-molecule drug design, and DiffDock NIM for molecular docking. These NIM models (more on NIM below) run on NVIDIA’s inference microservice platform, meaning scientists can access powerful AI models via simple API calls in their electronic lab notebooks. The result is a dramatic acceleration of the drug discovery pipeline – tasks like lead identification and optimization that once took months can potentially be done in days using AI. NVIDIA’s Kimberly Powell (VP of Healthcare) noted that pharma is rapidly adopting generative AI in 2025, integrating these models into R&D platforms to push the frontiers of what’s possible.

Another highlight was Evo 2, described as the world’s largest biology foundation model, trained on 9.3 trillion nucleotide sequences across 128,000 species. Evo 2, developed with the Arc Institute, can predict gene function and even generate synthetic genomic sequences. This kind of foundation model for genomics exemplifies how AI is tackling previously unsolved problems in biology – in Powell’s words, “we are starting to achieve exponential levels of biological intelligence by representing biology... For developers and researchers, these announcements mean that a wealth of pre-trained scientific models (for proteins, DNA, molecules) are readily available via NVIDIA’s platforms to integrate into drug discovery pipelines. NVIDIA GTC 2025 unveiled groundbreaking AI and GPU innovations, including the GeForce RTX 5090, Grace Blackwell supercomputing, AI-powered robotics, self-driving advancements, and the NVIDIA Dynamo OS. Get the full recap of Jensen Huang’s keynote and what these developments mean for the future of AI, gaming, and automation.

Under the hood, the RTX 5090 boasts 21,760 CUDA cores and next-gen ray tracing and tensor cores, delivering roughly 30% higher raster graphics performance over the RTX 4090 in early tests . Its switch to faster GDDR7 memory nearly doubles memory bandwidth (1.8 TB/s vs ~1.0 TB/s on the 4090) for better handling of high-resolution textures and complex scenes . The RTX 5090 introduces DLSS 4 with multi-frame generation, enabling big leaps in frame rates by using AI to create additional frames . Altogether, these architectural improvements give creators and gamers “unprecedented AI horsepower” and the ability to game with full ray tracing at lower latency . In short, the GeForce RTX 5090 pushes the cutting edge in GPU performance while improving power and cooling efficiency – a rare generational feat. NVIDIA announced a broad collaboration with General Motors (GM) to infuse AI across the automaker’s operations – from autonomous and assisted driving to factory automation.

Under this partnership, GM will use NVIDIA’s accelerated computing and software platforms to develop next-generation smart vehicles, AI-driven factories, and even robotic systems . For example, GM plans to leverage the NVIDIA DRIVE AGX in-car computer (based on the latest Blackwell GPU architecture) as the brain of its future vehicles, capable of up to 1,000 trillion operations per... This should enable more intelligent and safer self-driving capabilities and personalised in-car experiences. On the manufacturing side, GM is tapping into NVIDIA Omniverse and Isaac simulation tools to create digital twins of assembly lines and train AI models for factory robotics . By virtually testing production scenarios and AI-powered robots (for tasks like material handling and precision welding), GM can optimise its factories for efficiency and safety before implementing changes in the real world . The partnership’s scope even extends to enterprise AI solutions, as GM looks to accelerate vehicle design and engineering with generative AI and simulation.

Overall, this GM–NVIDIA alliance exemplifies how AI and simulation can transform the auto industry: smarter vehicles, more efficient manufacturing, and innovative consumer experiences, all driven by cutting-edge NVIDIA platforms . The impact could be industry-wide, setting new benchmarks for AI use in transportation and production. NVIDIA introduced NVIDIA Halos, a comprehensive safety framework for autonomous vehicles that treats safety as end-to-end mission – “from the cloud to the car”. Halos unifies NVIDIA’s hardware and software safety technologies with its latest AI research to ensure that every component of an AV system meets rigorous safety standards . It spans everything from safety-focused system-on-chips and the Drive OS (an ASIL-certified automotive operating system) to simulation tools and validation services, all working in concert. Halos defines safety on multiple levels: platform safety (with hundreds of built-in hardware safety mechanisms), algorithmic safety (validation of AI models and perception algorithms), and ecosystem safety (data sets, monitoring, and compliance) .

At the development stage, it provides guardrails during design, deployment, and validation to catch issues early . In practice, this means an automaker can pick and choose NVIDIA’s state-of-the-art chips, software modules, and testing tools via Halos to build their AV stack with confidence in its safety .

Everything Nvidia Announced At Gtc 2025 Groundbreaking Ai Gpu And

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