As America turns 250, we put together 250 open AI milestones from the US: open models, datasets, demos, papers, and tools that helped shape the field. They go from attention is all you need, pytorch, gpt2, ULMFIT, llama, imagenet, Lora and hundreds more. They are a reminder of what made America the world’s engine of innovation: - Open science - Open competition - Open ecosystems Builders and scientists building on each other’s work, challenging each other, remixing ideas, and pushing the frontier forward. That is America at its best! And that philosophy is at risk right now in AI. In the coming months, scientists and AI builders will have to decide what side of history they want to be on: an AI future shaped by openness, transparency, participation, and competition, or one increasingly controlled behind closed doors by a few actors optimizing for money, secrecy, and gatekeeping. Let’s make the next 250 even more open! huggingface.co/collections/c…

Happy 250th birthday, America! Founded in Silicon Valley over three decades ago, NVIDIA's roots in American innovation run deep. Today, we're proud to partner with the companies, scientists, developers, and builders using AI to accelerate progress and solve hard problems. Here’s to the next 250 years of American ingenuity, discovery, and breakthroughs.

Today, Valar Atomics became the first nuclear startup to make electricity, and we did it by powering an NVIDIA Spark. This is the first meeting of advanced nuclear and AI; two technologies which will transform the next century. But that’s only the start of our collaboration.

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Thank you to the partners across America helping bring the supply chain home. In 43 states and growing, NVIDIA’s network of American partners and suppliers spans semiconductors, boards, systems, racks, and more. Together, we’re helping create the tools for better healthcare, breakthrough scientific discovery, stronger industrial productivity, and global technology leadership.

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AI is shifting from model training to always-on token production, and that shift demands a new business model. NVIDIA is partnering with AI clouds to deploy large‑scale, multi‑tenant AI factories through revenue-sharing and credit-support. This opens up compute access to the fast‑growing AI ecosystem of startups, model builders, enterprises, research organizations and regional AI players.

Read more about Jaiveer and the Isaac ROS team’s work here: nvda.ws/3SDSqza

Before a robot can change the world, it needs software that builders can trust. NVIDIA robotics engineer Jaiveer Singh leads the team behind Isaac ROS, an open source platform helping developers build autonomous mobile robots, manipulation systems and humanoids with modular, CUDA-accelerated libraries and AI models. “When more people can build robots,” he says, “the future gets here faster.”

Vision AI agents are becoming a practical way to automatically turn video data from the physical world into operational intelligence in factories, cities, warehouses and transportation systems. See how Roboflow, DeepHow, and Linker Vision use NVIDIA Cosmos and NVIDIA Metropolis to generate synthetic data, fine-tune vision models faster, and deploy vision agents at scale. 📰 Read the blog: nvda.ws/4p2whXp

See how AI is creating new opportunities to build in America: nvda.ws/4amGJmA

In this way, the five-layer cake of AI is enabling America to build new industries and reimagine existing ones. It’s helping to increase productivity, add jobs, and bolster the U.S. economy.

But the purpose of this buildout extends far beyond the chips and systems being produced in the U.S. It’s to accelerate what those chips and systems make possible. AI can help scientists discover medicines, forecast weather, and solve problems once beyond reach.

NVIDIA and our partners are investing in American manufacturing, supply chains, energy grids, and skilled workforces.

America is a nation of builders. For 250 years, America has built railroads, power grids, factories, semiconductors, and the internet. Now, America is building again.

Most motion papers tailor one controller to one specific task. This year at SIGGRAPH, our research team asks: can motor control itself be pretrained and reused? Generative Pretrained Controllers, or GPC, turn motor skills into a vocabulary of discrete tokens and train a transformer-based generative controller through next-token prediction. Just like GPT, the same pretrained controller can then be fine-tuned to solve new tasks. Trained on 600 hours of motion, GPC runs in real-time inside a physics simulation, producing natural and physically grounded behaviors for interactive control.

Get the best price for #NVIDIAGTC Berlin conference passes today: ✅ GTC alumni get the biggest savings ✅ Early bird pricing is open to everyone ✅ All discounted pricing ends July 15 🔗nvda.ws/4ashiQs

NVIDIA inference software keeps driving down token costs, long after AI infrastructure is deployed. ⚡ In just one month on NVIDIA Blackwell, software optimizations improved DeepSeek V4 performance by up to 5×, reducing token costs to roughly one-fifth of previous levels. NVIDIA's integrated inference software stack compounds improvements across runtimes, kernels, networking, and hardware, delivering up to 20× higher throughput on the same GPU. Co-designed with NVIDIA GPUs, CPUs, networking, and systems, and powered by CUDA-native open source frameworks, NVIDIA's inference software stack ensures new model breakthroughs and optimizations run on NVIDIA from day zero, and keep improving throughput and lowering cost after deployment. See how @Baseten, @Cognition, @DeepInfra, @togethercompute, and @Cursor_ai are turning continuous software innovation into lower cost per token: nvda.ws/4eRT43m

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We're working with @PalantirTech to bring NVIDIA Nemotron open models into secure, air-gapped environments for U.S. government agencies and critical infrastructure operators. The new engine lets teams train on their own data, run models on their own infrastructure and retain full model ownership.