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TechCrunch Disrupt 2026’s new Real World AI Stage features Nvidia, robots, and extinct animals

On our new Real World AI stage, we’ll be focusing on the intersection between the digital and physical, and all the ways we’ll continue to see a blending of the two.

TechCrunch Events

Publisher TechCrunch AI

Sep 2, 2026 at 10:24 PM UTC · 4 분 소요

TechCrunch Disrupt 2026’s new Real World AI Stage features Nvidia, robots, and extinct animals
Image via TechCrunch AI
번역 중…

At our past TechCrunch Disrupt events, AI has taken center stage, both throughout our programming and in a stage of its own. This year, the technology, implications, and players are so rapidly developing and widespread that we’re expanding the single AI stage into two!

The AI Stage will continue as you’d expect, with a rundown of sessions and speakers available for review right here. But the Real World AI Stage is brand-new for TechCrunch Disrupt 2026.

On this stage, we’ll be focusing on that intersection between the digital and physical, and all the ways we’ll continue to see a blending of the two, as autonomous hardware goes beyond self-driving cars and enters public spaces, battlefields, our homes, and even potentially helps extinct species reenter Earth.

It’s a packed lineup featuring speakers from Shield AI, Colossal Biosciences, FieldAI, Foxglove, and more still to come. You can join in on all the excitement October 13 to 15 at San Francisco’s Moscone West, so register to attend right here.

But in the meantime, here’s the breakdown of our Real World AI Stage lineup:

Robots Are Waiting for Their ChatGPT Moment. Here Is What Is Standing in the Way

Large language models had the internet. Self-driving cars have millions of hours of road data. Robots have neither. That data gap is the single biggest reason most experts believe general-purpose robotic intelligence is still years away, despite the breakthroughs happening everywhere else in AI. A new wave of startups is racing to close it, building the data pipelines, simulation environments, and foundation models that could trigger the same capability explosion we saw with LLMs. This session asks the hard question: what does the ChatGPT moment for physical AI actually require, and how close are we really?