Connectionists: Yann Le Cun and Stephen Hanson on Yann's new vision of AI

[Stephen José Hanson]

In the last year, Yann Le Cun has posted a new vision for AI, partly avoiding the ambiguous complexity of LLM, and AGI, he focuses on
explicit reasoning systems, going beyond the implicit classification systems which have been so successful with Deep Learning.  Like other AI leaders, he realized that  somethingthay must be scaled down before scaling up.  It would be better to get the reasoning sense of a non-human mammal, say a cat, then jump to human reasoning, Yann argues.

This also underscores, I think,  much of the problem with LLM--e.g. ChatBOTs, which probably  will be a concern for classicial lingustics, nonetheless are inscructable.

At the same time critics have emerged, because when one provides enough detail of a specific vision it is both courageous and risky.   Our favorite critic/troll, Gary Marcus wrote several critiques (see  the one below), and  Yann and Jake Browning tried to clarify, and deflate some of the Marcus arguments, as many of them  appear to almost perversely misunderstand the difference between complex Nerual Network architectures and symbolic systems from the 1970s (which mostly didn't work).

Here is the conversation in whole focused entirely on Yann's new AI vision.  Cheers and Happy Holidays--Steve

https://www.youtube.com/watch?v=4s2S2l2OvdM&t=32s

The  description of the paper and critques.

https://ai.facebook.com/blog/yann-lecun-advances-in-ai-research/

https://www.technologyreview.com/2022/06/24/1054817/yann-lecun-bold-new-vision-future-ai-deep-learning-meta/

https://garymarcus.substack.com/p/how-new-are-yann-lecuns-new-ideas

https://www.noemamag.com/what-ai-can-tell-us-about-intelligence/

*(due to a small mic issue, we have also closed captioned the conversation)

--
Stephen José Hanson
Professor, Psychology Department
Director, RUBIC (Rutgers University Brain Imaging Center)
Member, Executive Committee, RUCCS
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