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 Support the show on Patreon! http://patreon.com/aiinsideshow Subscribe to the YouTube channel! http://www.youtube.com/@aiinsideshow Note: Time codes subject to change depending on dynamic ad insertion by the distributor. 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 Learn more about your ad choices. Visit megaphone.fm/adchoices
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