For a full rundown of the keynotes' announcements, check out all you gotta know below.
Nvidia GTC 2025: Latest updates
Prepare for next-level AI
Welcome!
How to watch Nvidia’s event
Nvidia is preparing its big event for our viewing pleasure.
(Image credit: Nvidia)
The company will hit the stage onTuesday, March 18, at 10 a.m. PT / 1 p.m.
It seriously is that easy.
Even if you’ve never written a line of code, something at this keynote should excite you.
Like today, it had a big keynote.
We tested theRTX 50 GPUs in-depthand were impressed with what we saw.
We will learn ’s AI pushat 1 p.m.
(Image credit: Nvidia)
ET today when the keynote kicks off.
This tiny computer, targeted at developers, offers a super chip for AI.
What are AI Foundation Models?
We expect Nvidia to talk about AI foundation models (Nvidia NIM microservices) during its keynote today.
If you’re not sure what that is, you’re not alone.
Give ourglossary of AI termsa quick read to learn about these and other AI phrases.
NIM microservices and AI Blueprints give PC developers and enthusiasts the building blocks to explore the magic of AI.
If you want to know more, check outNvidia’s blog post from January.
Nvidia Cosmos
Let’s get to the really exciting stuff: robots in AI!
That means we could see many more developers taking advantage using AI robots.
Will it come today during Nvidia’s keynote?
15 minutes to go… Read more about my hands-on and in-depth look at the tech running it!
And trust me, it looks insanely cool!
It works by essentially programming in a set of rules (or workflows) for it to stick to.
If there’s something I’m expecting to see, it’s definitely this.
The stream has started!
I wonder if this is running with RTX neural rendering?
And the stock price shows investors are a little nervous about what this will entail.
Two minutes left!
Of course this is a supercomputer, but let them cook.
Maybe it’s to find just the right leather jacker for Jensen!
Let the show begin!
Jensen’s on stage, and it’s time to learn what Nvidia has in store.
Strap in the leather jacket fit is good and Huang has no teleprompter!
It’ll be interesting to see how Nvidia’s AI tech can impact these areas.
Fingers crossed he puts it on the stock list for some lucky gamer to buy.
This graph looks familiar… We saw something similar to this at Nvidia’sCES 2025keynote.
Nvidia wants…to grow San Jose?
The demands of agentic AI and reasoning have been far greater than any company expected.
This results in a whole lot more tokens being used easily 100x more tokens.
How is this done?
This, of course, has drastically increased the amount of power needed.
Jensen’s shooting his shot and projecting $1 trillion in revenue by 2028.
And here’s where those AI frameworks can apply.
Well, I never knew a GPU could be used as a 5G radio.
But the signal processing capabilities of CUDA cores are there!
*
*don’t expect your iPhone to have RTX in it next year.
This is for companies!
Full self driving?
Nvidia is teaming up with GM to help create autonomous cars.
Nvidia Halos is a commitment to safety and transparency in self-driving cars.
Every line of code in FSD programs Nvidia is cooking will be safety assessed by a third party.
This could be huge for Waymo!
Now we’re seeing the reasoning model in action for self-driving!
Omniverse and Cosmos is able to train itself, learn from variations and improve itself evaluating its surroundings.
This is a crazy huge step forward!
So that’s why scaling up to these racks is important for the future of AI computation.
And for the business of AI, extreme efficiency is important here.
To demonstrate this, Nvidia put Llama’s traditional model up against Deepseek R1’s reasoning model.
The one shot took 439 tokens short time but got the answer wrong.
Meanwhile, DeepSeek took almost 9,000 tokens, a lot more computation and time.
It’s able to customize a data center to suit your uses.
Also Perplexity is partnered up for this!
It is a massive uplift from Hopper - what many companies are currently using.
a 25X uplift
RIP Hopper.
Blackwell just annihilated Hopper with 40X more tokens generated for the same revenue.
This will be significant for AI companies!
Time for some Photonics to improve the bandwidth and speed up data transfer.
We’ve seen some of this happening in the background, asNvidia did announce a partnership with TSMC.
wait…did the stream just go down?
Can anyone else verify?
That Spark looks mighty DIGITS-ish.
Companies like Asus, Dell, HP and Lenovo are jumping in to build these for enterprise.
Let’s talk about robots!
To solve a work crisis, Nvidia’s bringing general robots to the party.
Time to find out more about Physical AI!
Policies are tested via the digital twin to establish how these will work in the real world.
And then they’re deployed to work.
Nvidia Groot N1 is the AI model that will launch the robotics AI!
We’re finding out how they can work collaboratively, learn independently and optimize across many environments.
Damn, this robot has better drip than me.
Omniverse with Cosmos brings it altogether
We heard about these a little at CES!
Named Newton, Nvidia has partnered with Google DeepMind and Disney!
Oh, and that Groot N1 foundational model for robots?
It’s going to be completely open source!
Expect to see faster development in this area than you think!
And that’s GTC!
As predicted, very data-center focused, but we got a lot to glean from that too!
Just how powerful, you ask?
Yeah,a lot.
But with Nvidia’s Halos safety system in place, it makes self-driving cars far safer on the road.
That’s just an oversimplified version of it.
For a deeper dive into it all, Nvidia explains it in more detail in the video!
Quantum computing
Nvidia is building a research center in Boston to spearhead its advancements in quantum computing.
The NVAQC is expected to begin operations later this year.
Surgical robots
Nvidia detailed its vision for robotic surgeons and fully automated hospitals.
Nvidia aims to address the challenges associated with training robots withNvidia Cosmos.
This can be employed locally or via Nvidia DGX Cloud or other cloud or data center infrastructure.
AI has transformed every layer of the computing stack.
With these new DGX personal AI computers, AI can span from cloud services to desktop and edge applications.
If you’re in one of the aforementioned fields, DGX Spark could be beneficial.
(Image credit: Nvidia)
(Image credit: Nvidia)
