| ▲ | Davidbrcz 9 hours ago |
| Refreshing stories between all the AI ones (and crypto/web3 before that) |
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| ▲ | linguae 8 hours ago | parent | next [-] |
| Ironically, once upon a time Prolog and logic programming in general were part of the cutting-edge of AI. There's quite a fascinating history of Japan's fifth-generation computing efforts in the 1980s when Japan focused on logic programming and massively parallel computing. My former manager, who is from Japan, earned his PhD in the 1990s in a topic related to constraint logic programming. |
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| ▲ | copx 6 hours ago | parent | next [-] | | I remember when so-called "expert systems" written in Prolog or LISP were supposed to replace doctors. Then came the (first) AI winter after people realized how unrealistic that was. Nowadays LLMs are supposed to replace doctors.. and that makes even less sense given that LLMs are error-prone by design. They will hallucinate, you cannot fix that because of their probabilistic nature, yet all the money in the world is thrown at people who preach LLMs will eventually be able to do every human job. The second AI winter cannot come soon enough. | |
| ▲ | fc417fc802 8 hours ago | parent | prev [-] | | Even now NEC makes some cool massively parallel chips and accelerators that I wish were more mainstream because they look like they'd be fun to play with. |
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| ▲ | thesz 8 hours ago | parent | prev [-] |
| You said AI: https://github.com/stassa/louise Louise (Patsantzis & Muggleton 2021) is a machine learning system that learns Prolog programs.
Louise is a Meta-Interpretive Learning (MIL) system. MIL (Muggleton et al. 2014), (Muggleton et al. 2015), is a new setting for Inductive Logic Programming (ILP) (Muggleton, 1991). ILP is a form of weakly-supervised machine learning of logic programs from examples of program behaviour (meaning examples of the inputs and outputs of the programs to be learned). Unlike conventional, statistical machine learning algorithms, ILP approaches do not need to see examples of programs to learn new programs and instead rely on background knowledge, a library of pre-existing logic programs that they reuse to compose new programs.
This is what was done by Douglas Lenat from late 1970-s on [1]. He did his work using Lisp, this thing does something close using Prolog.[1] https://en.wikipedia.org/wiki/Eurisko |