Jensen Huang (黃仁勳)

AI is taking off and the world is responding. We brought the pre-game to the center of the AI universe. Everyone's coming to Computex. >> Hello, Taiwan. We are watching this magic happen. The future is just a little too exciting. You're with me? Surprise guest. >> [laughter] >> The lineup is absolute A-list leadership. This is huge. We will have 10 trillion-dollar companies. Let's be honest, Taiwa

And because Open Claw is open source, everybody can learn how to use it. And so this heart This harness is called a harness, essentially an operating system around the large language model. This harness is extremely useful and it's really good to learn how to use. And so that's what That's what this This event is about. They show you show you what open source agents can do and then you can go crea

My name is Steve Stein, product marketing here at Nvidia. HP Discover is around the corner and Nvidia is returning as a visionary sponsor this year. Aentic AI is the defining theme 2026. At Discover, you'll see firsthand how to build agents and the infrastructure that fuels them. We have sessions to educate you on the latest agentic advancements and late night events to dive deep with Invidians. S

This is a technology that has the potential to automate many aspects of human labor very soon. And I'm curious the degree to which you feel a responsibility for making that transition go well. >> What AI will do is to make tasks that we do in our job more efficient. Our job is not to wrangle a spreadsheet. Our job is not to type into a keyboard. Our job is generally more meaningful than that. I'm

My name is Eduardo Alvarez. I'm a senior technical leader at NVIDIA. When we think about tokenomics, a part that's ignored sometimes is the role that engineers have in optimizing the cost of inference systems. If you look at the tokenomics equation, that denominator, which is your GPUs throughput, is something that obviously engineers have an incredible role in everything from optimizing kernels

And with NVIDIA, we're bringing CX enterprise co-worker capabilities into the NeMo cloud enterprise agent platform, enabling brands to deploy Adobe's customer experience intelligence within NVIDIA's secure, policy-governed Open Shell runtime. So, you get the best of both worlds. The rapid innovation of these AI platforms and the rock-solid, proven capabilities of Adobe CX enterprise.

And so I think we have to be careful and really ground ourselves on to talking about the facts. The facts are this. The facts are AI has created more than half a million jobs in the last couple years. The facts are AI is our greatest our best opportunity to reindustrialize the United States, to bring manufacturing jobs back to United States. The facts are that's going to generate hundreds of thous

When it comes to inference TCO, token cost is the metric that determines whether AI can scale efficiently and profitably in the real world, not compute cost or FLOPS per dollar. It’s the one TCO metric that directly accounts for hardware performance, software optimization, ecosystem support and real-world utilization — and NVIDIA delivers the lowest cost per token in the industry is available thro

AI isn’t just about chatbots and automation—startups are finding unexpected, creative ways to apply it to the world's hardest problems in ways you might not imagine. In this session, we’ll spotlight 25 innovative use cases that reveal the breadth and depth of what’s possible when bold founders with big visions meet cutting-edge technology. Get ready to expand your view of AI’s potential and discov

I love to tell people that my whole training as an atmospheric physicist is being completely thrown out the window as we realize there's a better way to simulate the atmosphere that involves learning directly from the data. These are fully AI predictions covering the entire United States of the details of storm and cloud evolution learned directly from geostationary satellites and radar. This mo

#PhysicalAI is reshaping manufacturing from design to factory floor. Leaders from @abb , @JLRYouTube, and @TulipInterfaces reveal how AI-powered simulation, synthetic data, and real-time video analytics are driving breakthrough efficiency across the full product lifecycle. Read the full @HM26 blog: https://blogs.nvidia.com/blog/ai-manufacturing-hannover-messe Discovery synthetic data for physical

There's no question that bringing everybody along is is really the single most important thing to do. And and the fact of the matter is it is unlikely most people will lose a job to AI. It is most likely that most people will lose to lose a job to somebody who uses AI. And so we have to make sure that everybody use AI. Um it is also the case you you hear many examples of this where somebody used t

LEM Surgical’s Dynamis system is the first FDA‑cleared humanoid surgical platform for spine surgery. Using NVIDIA Isaac for Healthcare and Cosmos Transfer to train the autonomous arms, Dynamis is powered by NVIDIA Jetson AGX Thor™ and Holoscan and lets surgeons maintain precise tool tracking even when line‑of‑sight is blocked. This integrated, navigation‑based robotic platform supports thoracic, l

I asked Jensen about TPU competition, Nvidia’s lock on the ever more bottlenecked supply chain needed to make advanced chips, whether we should be selling AI chips to China, why Nvidia doesn’t just become a hyperscaler, how it makes its investments, and much more. Enjoy! Watch on YouTube ; listen on Apple Podcasts or Spotify. Sponsors Crusoe’s cloud runs on state-of-the-art Blackwell GPUs, with Ve

Introducing NVIDIA Ising, [music] an open family of AI models created for the workloads that define the path [music] to useful quantum computing. Ising calibration is a pre-trained vision [music] language model that rapidly automates the tasks needed to keep quantum processors running. Ingesting measurement [music] results, it identifies necessary corrections, dramatically accelerating what once w

Today, AI data centers are token factories. AI infrastructure TCO is often judged by compute cost and FLOPS per $. But these are just inputs, where cost per token is what is actually delivered. Consider the same NVIDIA Blackwell to Hopper generational gains measured three ways: • FLOPS per dollar: ~2x improvement • Cost per million tokens: ~35x lower • Tokens per second per megawatt: ~50x higher T

“The ChatGPT moment for self-driving cars has arrived.” At GTC, NVIDIA revealed breakthroughs in autonomous driving—from reasoning AI with Alpamayo to robotaxi-ready platforms with Hyperion—alongside partners including Uber. Learn more about the announcements featured in this video: • Press Release: BYD, Nissan & More Adopt NVIDIA DRIVE Hyperion for Level 4 Vehicles 👉 Read the announcement: https:

To the creators, the pioneers, and the builders of the future: CUDA was made for you. Since 2006, six million developers across 200 countries have used CUDA to transform computing. What began as a platform has become the engine of the Accelerated Age. With 900+ CUDA-X libraries, you are accelerating science, reshaping industries, and giving machines the power to see, learn, and reason. From drug d

Static systems waste time, energy, and resources. AI-powered infrastructure changes that. With NVIDIA Metropolis Blueprint for video search and summarization (VSS), running on NVIDIA's AI-RAN base station, AI agents run continuously at the edge, analyzing real-time data streams from connected sensors over 5G. These agents enable live monitoring of urban environments, AI-powered 3D digital twins fo

And this has been a huge missing part of the quantum computing community. Access to open AI models to really use the latest in AI technology to help us accelerate how we get to these useful quantum applications. And so in video I sing at launch has got two sets of models in it. It's got models for doing calibration. That means for tweaking [music] quantum hardware very quickly to correct any kind

Discover AI for quantum with NVIDIA Ising—the first open source AI model family built to accelerate the path to useful quantum computing. In this video, learn how accelerated quantum supercomputers could unlock breakthroughs in drug discovery, materials science, and optimization, and why getting there requires advanced qubit hardware, accelerated computing, and purpose-built AI. NVIDIA Ising intro

(0:00) Gavin Baker joins the show! (0:30) Andrej Karpathy joins Anthropic; hypergrowth and profitability (12:42) Why Americans have turned on AI, anti-human perception (27:22) Trump pulls AI EO, US-China AI relationship, dystopian AI layoffs (45:19) SpaceX S-1 tear down! Breaking down the three major businesses and the case for a $2T valuation (1:11:22) Nvidia smashes earnings but stock falls, why

Hi, I'm Neil Kano. I'm going to be talking to you today about edgetocloud video anomaly detection. Just doing a quick intro because Terry Demiba's session at AIDv did have some audio technical difficulties for the first few minutes. I'm his manager Devril leader at Quadrant and I'm going to give you a short intro before handing over to Terry for the live presentation. So today we're talking about

We were able to cut almost about 76% of our job costs as a result of this migration. >> 76? >> 76. It's It's phenomenal. Right? I mean, for for the engineers out there, [music] like we were able to cut down the number of cores required by like 62%. The The memory footprint print we we could drop it by like 80%. So, phenomenal results. The results speak for themselves.

As AI coding tools evolve from autocomplete to autonomous agents, software development itself is being redefined. This talk by Cursor's Amrita Venkatraman explores the "third era" of AI software development, where fleets of cloud-based agents collaborate as persistent teammates instead of one-off assistants. She traced the shift from keystroke-level Tab completion to synchronous, in-editor agents,

(0:00) Bestie intros! Thoughts on the LA mayor election (4:38) SpaceX-Anthropic deal, Elon Web Services, SpaceX IPO valuation, Anthropic's insane growth trajectory (26:48) Is Anthropic the next great monopoly? Early signals or major overreaction? (35:21) "FDA for AI" freakout, how the White House thinks about AI safety (52:01) Flipping AI's negative perception: Giving, healthcare and education inn

As AI factories scale and token costs become a defining competitive variable, the way businesses measure infrastructure ROI needs to change. In this episode, Shruti Koparkar from NVIDIA's Accelerated Computing team breaks down tokenomics—the four-pillar framework of token utility, supply, demand, and monetization—and reveals why NVIDIA Blackwell's architecture delivers 50x more tokens per watt tha

LangChain has surpassed 1 billion downloads—and the framework that started as a weekend project is now the harness powering the next generation of production-grade AI agents. In this episode, Harrison Chase, co-founder & CEO of LangChain, breaks down the architecture behind deep agents, explains why systems like Claude Code, Manus, and Deep Research all share the same foundational pattern, and lay

I'm Era. I'm going to be talking about eval uh specifically u AI evals like coding agent evals and stuff. And I'm going to talk about how they're broken and how you could still use them. Anyway, uh before I start, I just I want to say one thing. It's just like it boggles my mind when when you're like when you're working on something and you're like cooped up in a room for so long and you just like

"Snap processes more than 10 petabytes of experimentation data every single morning—and with NVIDIA GPU-accelerated Apache Spark on Google Cloud, Snap cut job costs by 76%, reduced memory usage by 80%, and eliminated 120 terabytes of disk spill from its pipelines. Prudhvi Vatala, head of engineering platforms at Snap, joins the NVIDIA AI Podcast to break down how he and his team completely moderni