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Yang Likun Interview: Analyzing the Limitations of LLMs and Discussing the Future of AI and New Avenues for Entrepreneurship

MeNews
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AIMPACT News, May 16 (UTC+8). On the Unsupervised Learning podcast, AI pioneer Yann LeCun laid out his contrarian views on the limitations of large language models and discussed the development path of robotics. He explained why he left Meta and highlighted major disagreements with Geoff Hinton and Yoshua Bengio on perspectives related to the Turing Award. The interview also covered his predictions for 2027, the new company AMI’s bet on world models, and likened OpenAI and Anthropic to Sun Microsystems. In addition, he advised PhD students to stop researching LLMs and shared sharp insights into AI safety, how breakthrough research happens, and the gains and losses of Meta FAIR. (Source: AiHot)
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GateUser-ffe7bee5
· 8h ago
Unsupervised learning podcast quality has always been top-notch; this episode is packed with information.
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GateUser-8da82d63
· 8h ago
I’d like to hear more about that part of FAIR’s gains and losses—where exactly did Meta go wrong?
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TheNemesisOfFomo
· 8h ago
Advice for PhD students not to touch LLMs—hearing this from a Turing Award winner, lab bosses are going to have a headache.
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PettyLp
· 8h ago
The shift in robotics technology seems to be betting that embodied intelligence can bypass the bottleneck of LLMs.
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PineLiquidityPool
· 8h ago
The 2027 forecast is quite interesting; remember, his last predicted timeline was never accurate.
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MechanicalHummingbirdGlass
· 8h ago
And Hinton and Bengio have such major disagreements on safety issues, the division within the AI community is more serious than imagined.
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TheRedTelephoneBoothInTheRuins
· 8h ago
Yang Likun's recent criticism of LLMs is quite harsh, but is the path of world models really feasible?
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