A couple of additional thoughts:
1. She goes on to point out that the field has become an intellectual monoculture, with the neurosymbolic approach largely abandoned, and massive funding going to the pure connectionist (neural network) approach
Just to nitpick... that is largely true, but with the caveat that there has been something of a resurgence of interest in neuro-symbolic AI over just the last couple of years. There's been a series of "Neuro-Symbolic AI Summer School" events[1][2][3] going on since 2022 with the next one coming up in August. And there have been recent books[4][5] published specifically on neuro-symbolic AI. You'll also find recent papers on neuro-symbolic AI on arXiv[6]. So for those who are interested in this topic, there is definitely activity underway "out there".
2. Including LLMs somewhere in the next evolution of AI makes sense to me, but leaving them at the core may be a mistake.
I've spent a lot of time thinking about this, and generally agree with this sentiment. Some kind of fusion of LLM's (or "connectionism" in general) and symbolic processing seems desirable, but I'm not sure that we should rely on LLM's to be "core" and try to just layer symbolic processing on top of what we get from the LLM. I have my own thoughts on how such an integration might work, but it's all still speculative at the moment. But I find the whole notion worthy enough to invest time and attention into it, for whatever that is worth.
[1]: https://ibm.github.io/neuro-symbolic-ai/events/ns-summerscho...
[2]: https://neurosymbolic.github.io/nsss2023/
[3]: https://neurosymbolic.github.io/nsss2024/
[4]: https://www.amazon.com/Neuro-Symbolic-AI-transparent-trustwo...
[5]: https://www.iospress.com/catalog/books/handbook-on-neurosymb...
YuriNiyazov•6h ago
hooah•5h ago
''' In my 2018 Deep Learning: A Critical Appraisal for example, I wrote
Despite all of the problems I have sketched, I don’t think that we need to abandon deep learning.
Rather, we need to reconceptualize it: not as a universal solvent, but simply as one tool among many, a power screwdriver in a world in which we also need hammers, wrenches, and pliers, not to mentions chisels and drills, voltmeters, logic probes, and oscilloscopes. '''
kgwgk•4h ago
2018: While none of this work has yet fully scaled towards anything like full-service artificial general intelligence, I have long argued (Marcus, 2001) that more on integrating microprocessor-like operations into neural networks could be extremely valuable.
2022: Where people like me have championed “hybrid models” that incorporate elements of both deep learning and symbol-manipulation, Hinton and his followers have pushed over and over to kick symbols to the curb.