Yann LeCun, Meta’s chief AI scientist and Turing Award winner, joins us to discuss the limits of today’s LLMs, why generative AI may be hitting a wall, what’s missing for true human-level intelligence, the real meaning of AGI, Meta’s open-source strategy with Llama, the future of AI assistants in smart glasses, why diversity in AI models matters, and how open models could shape the next era of innovation
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CHAPTERS:
0:00:00 - Podcast begins
0:01:40 - Introduction to Yann LeCun, Chief AI Scientist at Meta
0:02:11 - The limitations and hype cycles of LLMs, and historical patterns of overestimating new AI paradigms.
0:05:45 - The future of AI research, and the need for machines that understand the physical world, can reason and plan, and are driven by human-defined objectives
0:14:47 - AGI Timeline, human-level AI within a decade, with deep learning as the foundation for advanced machine intelligence
0:21:35 - Why true AI intelligence requires abstract reasoning and hierarchical planning beyond language capabilities, unlike today's neural networks that rely on computational tricks
0:30:24 - Meta's open-source LLAMA strategy, empowering academia and startups, and commercial benefits
0:36:10 - The future of AI assistants, wearable tech, cultural diversity, and open-source models
0:42:52 - The impact of immigration policies on US technological leadership and STEM education
0:44:26 - Does Yann have a cat?
0:45:19 - Thank you to Yann LaCun for joining the AI Inside podcast
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