NVIDIA GTC Washington, DC: Live Updates on What’s Next in AI

If you want to solve the world’s hard problems, you start in the open.

That was the distilled, non-negotiable takeaway from the GTC DC panel, “Open-Source AI 101: Enabling American Innovation.” A brain trust of developers, researchers and capital experts made the case that transparent collaboration is the new path to national advantage. Forget the closed-off labs of the past — the engine powering today’s breakthroughs is open to everyone.

The panel was an all-star lineup of open-AI evangelists: NVIDIA’s Ankit Patel and Bryan Catanzaro, AI2/UW’s Noah Smith and OSS Capital Founder Joseph Jacks. They cut through the noise with clarity, defining what “open source” means for innovation at speed.

Efficiency Unlocks Innovation

The central theme is simple: open models drastically accelerate innovation. They slash the time and cost it takes a startup, university lab or government agency to build a critical application. It is, as the panelists argued, the most efficient way to scale the sheer volume of AI expertise required to solve hard problems.

For the venture capital perspective, Jacks was direct that open models unlock “huge amounts of leverage and efficiency in R&D because they didn’t have to build the pre-training models.”

This democratization of capability means innovation can now come from anywhere. As Patel noted, this current AI boom is built on a proven foundation: “How many of you remember Linux and PHP and MySQL and nginx and all that… that was the foundation, the open-source foundation of the internet era, right?”

Trust and Cooperation: The Killer Features

The discussion in D.C. always returns to trust, and here, open source delivers a crucial feature: transparency. For an industry fostering rapid change, the ability to inspect the AI model’s inner workings is the critical layer of accountability.

AI2/UW’s Smith gave a striking metaphor to describe the futility of closed AI for scientific progress: “Trying to study the state of artificial intelligence scientifically from proprietary models is like trying to do astronomy from pictures in the sky printed in a newspaper, you can’t do it, right?”

NVIDIA’s Catanzaro argued that the core dangers of AI are fundamentally dangers of control, making openness a safer societal bet.

“I think one of the big dangers of closed systems is about control,” Catanzaro said. “And since AI is a technology about ideas, I think that inherently it is safer” when open.

Catanzaro later expanded on this idea, emphasizing the benefit of having diverse perspectives collaborate on one model: “One of the things that we’ve definitely seen over the past few years [in the] development of AI is that openness has really moved the field along.”

The message from the panelists to D.C. policymakers was unambiguous: Open-source AI creates an ecosystem that is more resilient, more innovative and, by being transparent, more trustworthy.

Watch the full session on NVIDIA On-Demand.