What Big Tech Missed And How Startups Can Still Win

Y Combinator

Resumen

This video features an in-depth conversation with Alex Lebrun, founder of Ami Labs, discussing the challenges of building AI startups and the transition from LLMs to world models. Lebrun shares insights from his journey at Wit.ai, his time at Meta, and his current mission to create machines with common sense. He explains why world models, which learn from sensory data rather than just text, represent the next frontier in AI, and offers advice on balancing ambitious long-term visions with practical, narrow go-to-market strategies.

Capítulos

  1. 0:00Costo y expectativas
  2. 0:36Orígenes: Algolia, Wit.ai
  3. 5:01Filosofía de 'ser temprano'
  4. 9:01Amilabs: IA aplicada
  5. 11:41Modelos del mundo vs. LLMs
  6. 17:01Limitaciones de VLA y LLMs
  7. 21:31Grandes empresas y startups
  8. 28:21Liderazgo de Yann y Alex

Temas tratados

  • The pressure of high-funding expectations
  • The early days of Wit.ai and Facebook acquisition

+5 temas más (contenido completo al seguir el canal)

Extracto de la transcripción

I told the team yesterday that the real cost of this 1.2 billion was not dilution. Uh the real cost is is expectations. Not only are from our investors because I think our investors they they understood and they agree on the long-term vision of the company, but the expectations you create in the outside world and if you raise 20 million and you do nothing for 2 years or or people don't see anything uh coming out of it for 2 years, then it's very very hard to survive. >> So, we I actually met Alex. Uh fun fact, we actually did the same YC batch. Uh back then Alex was building Wit AI and we were building Algolia as I was in winter 14, quite a while ago. Uh except Alex has done four companies, like one before, two after. I've only done one, so like I cannot compare. So, I'm super impressed by your like all your background and everything you've done. What do you remember from Wit? Like wit.a…