The AI industry is obsessed with making models smarter. But what if they’re building the wrong kind of intelligence? In launching his new venture, humans&, Eric Zelikman sees an opportunity to shift the focus from pure IQ to building models with EQ. Sarah Guo is joined by Eric Zelikman, formerly of Stanford and xAI, who shares his journey from AI researcher to founder. Eric talks about the challenges of building human-centric AI, integrating long-term memory in models, and the importance of creating AI systems that work collaboratively with humans to unlock their full potential. Plus, Eric shares his views on abunance and what he’s looking for in talent for humans&.

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Chapters:

00:00 – Eric Zelikman Introduction

00:29 – Eric’s Early Interest in AI

01:29 – Challenges in AI and Automation

02:25 – Research Contributions

06:14 – Q-STaR and Scaling Up AI

08:14 – Current State of AI Models

15:23 – Human-Centric AI and Future Directions

22:08 – Eric’s New Venture: humans&

35:33 – Recruitment Goals for humans&

36:57 – Conclusion