This will be *really* funny, until you remember 99% of current super hyped AI stuff is running on Python
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(Please don't lob rocks at me. I love Python.)
Is Python not considered to be any good?
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(Please don't lob rocks at me. I love Python.)
Every old timer knows AI is supposed to be written in Prolog.
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Is Python not considered to be any good?
...It's okay. I've programmed in far far worse languages. ...It's got its advantages. It's got it's problems.
️Edit: If you need a serious answer: Much like BASIC, it's a language often used in teaching programming. In that sense, I guess it's much better than BASIC. You can, like, actually use it on real world applications. If you're using BASIC for real world applications in this day and age something has gone really wrong.
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Every old timer knows AI is supposed to be written in Prolog.
One of the guys who taught me Prolog wrote the book: https://www.inf.fu-berlin.de/lehre/SS09/KI/folien/merritt.pdf
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One of the guys who taught me Prolog wrote the book: https://www.inf.fu-berlin.de/lehre/SS09/KI/folien/merritt.pdf
But there is one other, probably even more important advantage: Prolog is a programmer's and software engineer's
dream. It is compact, highly readable, and arguably the "most structured" language of them all. Not only has it done
away with virtually all control flow statements, but even explicit variable assignment too!
These virtues are certainly reason enough to base not only systems but textbooks on this language.The 90s certainly were a different time...
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But there is one other, probably even more important advantage: Prolog is a programmer's and software engineer's
dream. It is compact, highly readable, and arguably the "most structured" language of them all. Not only has it done
away with virtually all control flow statements, but even explicit variable assignment too!
These virtues are certainly reason enough to base not only systems but textbooks on this language.The 90s certainly were a different time...
I highly recommend learning the language. You learn to think about problems from an entirely different perspective, effectively working backwards from the solution, and once you wrap your head around it, it becomes the clear choice for certain applications such as expert systems.
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It sure made sense forty years ago. And I'd bet that the examples in that book are more AI than today's LLMs.
wrote on last edited by [email protected]The dominant approach at the time were Expert Systems. This used a lot of carefully crafted data and manually curated facts that the inference engine can use. It also fit in a MUCH smaller footprint compared to conventional neural networks. But you also don't get real language processing, reasoning beyond the target problem domain, and stuff like that - it's laser focused and built on very small amounts of data. Much of the research from back then centers on using Lisp and Prolog of all things, so BASIC isn't a big stretch.
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The dominant approach at the time were Expert Systems. This used a lot of carefully crafted data and manually curated facts that the inference engine can use. It also fit in a MUCH smaller footprint compared to conventional neural networks. But you also don't get real language processing, reasoning beyond the target problem domain, and stuff like that - it's laser focused and built on very small amounts of data. Much of the research from back then centers on using Lisp and Prolog of all things, so BASIC isn't a big stretch.
Prolog is even better suited for such applications.
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(Please don't lob rocks at me. I love Python.)
dusts off a commodore 64 well time to make my own chatgpt
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Prolog is even better suited for such applications.
wrote on last edited by [email protected]who tf even uses prolog anymore (said the one still using old basic, from when it still had line numbers and everything was goto all the way down)
this is very clearly a self deprecating joke btw
