Teaching your AI new tricks.
Santa Clara, CA
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NVIDIA AI retweeted
Ten years ago at NVIDIA GTC 2016, our CEO @JensenHuang introduced DGX-1, our first AI supercomputer.
Since then, NVIDIA DGX has transformed from a single system into a blueprint for AI factories. What hasn’t changed is the reason why we build DGX: to test the systems and work through the details of interconnects, cooling, and software so our partners and customers have a proven foundation to build on.
Charlie Boyle, our VP of DGX Systems, looks back at how DGX got its start, what’s changed, and what comes next.
Thanks to everyone who’s been on this journey with us. #DecadeOfDGX
Watch the full video: nvda.ws/4yQkRJW
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Love this news. More doctors around the world will be able to use OpenEvidence for free. Congrats to @OpenEvidence and @AnthropicAI 💚
“Medicine is a field where you don't need to squint to see the benefits of AI. It's your mom, it's your dad, it's your sister, it's your brother. And it's the doctors who will care for them in their most vulnerable moments.”
Yesterday, during the UN General Assembly, we announced a partnership with @AnthropicAI to make OpenEvidence available free of charge to physicians in low- and middle-income countries, placing life-saving medical AI into the hands of physicians worldwide, regardless of the economics.
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NVIDIA AI retweeted
🚀 New benchmark alert: SWE-Serve (research.nvidia.com/benchmar…)
Can AI agents develop inference engine and make it serve real models?
Our team at @nvidia built 53 tasks from real @sgl_project engineering work to find out. The chart shows why live-serving tests matter. 🧵
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Our new Nemotron 3 Diarization model + @pollenrobotics Reachi Mini + DGX Spark
Great work Andi @huggingface 🙌
Voice agents still don’t understand who’s speaking to them. That’s a huge gap compared with humans, hidden by all the “phone-call” demos. But that changes today!
NVIDIA is open-sourcing Nemotron 3 Diarization: a model that can reliably track speakers in live conversations, under a commercial-friendly license! In my tests, the quality is really good with one-second speech chunks. So we can use it for voice agents!
I tested it with Reachy Mini and speech-to-speech running on a DGX Spark. It’s super fun to see the robot notice a new voice, ask for a name, and remember it.
The model has day-zero integration with Transformers!
Kudos to the NVIDIA team for shipping useful tools for the whole community!
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When several people talk at once, a transcript can get messy fast.
Our new Nemotron 3 Diarization model tracks who spoke when, even when voices overlap. It handles up to eight speakers, has 100M parameters, and is now available on @huggingface 🤗
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Nemotron 3 Diarization ranked #1 of 12 systems in @voicearena_ai's initial Diarization-Bench results. Its 14.72% error rate was ~24% lower than the runner-up.
Here’s a four-speaker comparison from the benchmark.
Full results: voicearena.com/diarization-b…
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We also put together a live demo on @huggingface if you want to try it yourself: huggingface.co/spaces/nvidia…
And, a blog with more on how it works and how to get started: huggingface.co/blog/nvidia/n…
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Figuring out a data center’s carbon footprint means piecing together a lot of messy data, from parts lists and documents to supplier emails.
Sluicebox built an AI supplier agent called Lucy to help. Using NVIDIA Nemotron 3 Ultra, Lucy collects and checks supplier data so engineers can understand the impact of their choices while they’re still designing.
In Sluicebox’s tests, Nemotron improved accuracy, cut costs by 51–80% and delivered responses up to 2x faster.
See how it works: nvda.ws/4iIQi4e
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Ask the Experts: Evaluating Agent Skills | Nemotron Labs nitter.net/i/broadcasts/1lKQRWXyD…
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NVIDIA AI retweeted
vLLM integrated PyNvVideoCodec to offload video decoding from CPU to GPU's NVDEC.
Result: 2x+ throughput at 8×H100, CPU bottleneck gone! This is huge for video captioning at scale (AV training, metadata), and ships with CUDA vLLM releases.
🔗 vllm.ai/blog/2026-09-18-pynv…
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And the winners are ....
Congratulations to our #NVIDIAGTC Berlin Golden Ticket winners!
Chosen by our panel of judges @asierarranz @choroukmalmoum @SteveNouri @mervenoyann @itsjohnnynunez and @googlecloud, these six winners will join us in Berlin next month:
🏆 Lucas Hudson
🏆 James Kane
🏆 Devin Nicholson
🏆 Aaron Nowak
🏆 Vladimir Shirokun
🏆 Stefan Trauth
Thanks to everyone who participated and shared your projects - we loved seeing what this community is building with open models.
See you at GTC!
What are you building with open models? Show us what you’re working on and you could be headed to #NVIDIAGTC Berlin. 🎫
Your Golden Ticket includes:
→ Free conference pass
→ VIP seating for Jensen’s keynote
→ Exclusive NVIDIA merch
→ Access to special events
Submissions are open Aug 18 – Sep 10, 2026.
Details and how to enter: nvda.ws/4wFdunb
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Your LLM endpoint works. But how does it perform when traffic increases?
NVIDIA Dynamo AIPerf helps you measure TTFT, ITL, latency and throughput at scale, then test with realistic traffic patterns you can reliably repeat.
Read the blog: nvda.ws/4hdIeGd
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Seattle Spark Hack Winners Livestream Spotlight: LiveKit & Memo nitter.net/i/broadcasts/1qKVmyRlX…
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What happens when you give a world model 32 images of a place we know very well?
World Labs put Atlas to the test on Voyager.
Atlas brings text, images, video, and 3D into a shared spatial context, enabling one model to generate new views, reconstruct scenes, and simulate worlds. With Voyager, you can now see that in action in real time.
Pretrained from scratch on NVIDIA Blackwell GPUs. Take a look around 👇
From 32 input images to real-time flight through @nvidia's Voyager headquarters.
Trained on NVIDIA Blackwell GPUs, Atlas uses these images as 3D spatial context to generate new views, letting you explore with pixel-perfect camera control.
Take a look around.
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At Dumfries House in Scotland, our CEO @JensenHuang joined His Majesty The King and global leaders to discuss how AI can serve the public good.
Jensen's message: capability and safety must advance together, expanding opportunity and putting AI to work for people.
ALT His Majesty King Charles III walks with NVIDIA CEO Jensen Huang.
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NVIDIA AI retweeted
Introducing CUDA Rust!
CUDA Rust lets you write GPU kernels natively in Rust, not just launch them from it.
Two paths: cuda-oxide for SIMT kernels compiled to PTX, and cutile-rs for Tile-based programming on stable Rust. Both can catch aliasing errors at compile time.
Technical blog: nvda.ws/4hm1bHS
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NVIDIA AI retweeted
AI leadership won’t be won by a few technology companies.
It will be built by every company, industry, researcher, teacher, student, and startup with the opportunity to participate.
That's why both open and closed models matter.
NVIDIA CEO @JensenHuang at #AllInSummit:
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Images rarely show an object’s full 3D geometry.
At #ECCV2026, our research team introduced Axolotl3D, a multimodal and occlusion-aware 3D generation model. It combines images, camera data and partial geometry to reconstruct missing regions while preserving observed ones, achieving state-of-the-art results across single- and multi-view settings.
Project page: research.nvidia.com/labs/sil…
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How can a 30B-parameter model activate just 3B parameters per token and still draw on the full model’s capacity?
Learn how dense and MoE models use parameters differently, and what that means for throughput, memory and serving complexity.
Check out our new technical explainer: nvda.ws/4Aaix21
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