LLMs may have kicked off this AI boom, but the ceiling is closer than the hype suggests. As models run out of text data to train on, the companies and investors paying attention are already moving on. The next wave isn't better chatbots; it's machines that can understand the physical world. Luma AI, the Bay Area lab that raised over $1.4 billion from a16z, Nvidia, and Amazon, is betting on exactly that. 

On episode of TechCrunch's Equity podcast, we’re bringing you a conversation Rebecca Bellan sat down with Amit Jain, co-founder and CEO of Luma AI, at Web Summit Qatar. Together, the pair dug into where the next trillion-dollar AI opportunity actually gets built, and whether the companies chasing it even know what they're building yet. 

Listen to the full episode to hear about: 

Why video, audio, and images are the real frontier for AI training data, not text 

What an "intelligent world model" actually is, and why Jain thinks most companies building them are getting it completely wrong 

The case for why AI won't kill creative jobs, and why Jain thinks studio heads are the real problem 

How the path from video generation to robotics to AGI is simpler than anyone's making it sound 

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Chapters: 

00:00 Intro 

01:13 Why LLMs are hitting a ceiling 

02:43 The data problem & what comes after LLMs 

04:30 What actually makes a world model a world model 

06:05 Why 3D data is a dead end 

07:39 What Luma is building next 

09:08 How much humans stay in the loop 

10:00 Near-term use cases for agentic video 

11:22 Will AI kill jobs in film & production? 

13:30 Why the entertainment industry is already dying 

15:27 Why we actually need more content, not less 

17:46 Luma's roadmap: generation, understanding, and robotics 

19:54 Outro 

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