Hi Adrian! You’re doing great work Scryer Prolog, keep up the good work! :)
Readit Newsgorkempacaci commented on Native compilation of Prolog predicates with Cranelift [pdf] files.adrianistan.eu/talk... · Posted by u/aarroyoc
This is seriously impressive performance. I think there's a high probability Nvidia attempts to acquire Cerebras.
They're considering an IPO. I'd say an acquisition is unlikely. Even then, they'd be worth more to Facebook or MS.
nvidia hates this one little trick
My workplace currently has a similar problem where a resource leak can be greatly increased with certain unpredictable/unknown traffic conditions.
Our half-day workaround implementation was the same thing, just cycle the cluster regularly automatically.
Since we're running on AWS, we just double the size of the cluster, wait for the instances to initialize, then rapidly decommission the old instances. Every 2 hours.
It's shockingly stable. So much so that resolving the root cause isn't considered a priority and so we've had this running for months.
How about the costs? Isn’t this a very expensive bandaid? How is it not a priority? :)
gorkempacaci commented on Use Prolog to improve LLM's reasoning shchegrikovich.substack.c... · Posted by u/shchegrikovich
>> Why not run the full set?
Most likely cherry-picking. The approach is only going to work well in domains where Prolog is commonly used to write solutions to problems, like logical puzzles or constraint problems etc.
Yeah probably.
gorkempacaci commented on Use Prolog to improve LLM's reasoning shchegrikovich.substack.c... · Posted by u/shchegrikovich
Yeah I’m a huge proponent of this general philosophy, but after being introduced to prolog itself for a third of a semester back in undergrad I decided to stay far, far away. The vision never quite came through as clearly as it did for the other wacky languages, namely the functional family (Lisp and Haskell in my case). I believe you on the fundamental termination issues, but just basic phrasing seemed unnecessarily convoluted…
Since you seem like an expert: is there a better technology for logical/constraint programming? I loved predicate calculus in school so it seems like there should be something out there for me, but so far no dice. This seems kinda related to the widely-discussed paradigm of “Linear Programming”, but I’ve also failed to find much of interest there behind all the talk of “Management Theory” and detailed mathematical efficiency comparisons.
I guess Curry (from above) might be the go-to these days?
Curious to know what part of syntax you found convoluted. If you remember any examples I’d appreciate it.
Maybe you want a constraint programming environment instead. As example check out Conjure from St Andrews:
https://conjure.readthedocs.io/en/latest/tutorials-notebook....
More generally there are the theorem provers like Coq, etc., but their use cases are even more specific.
gorkempacaci commented on Use Prolog to improve LLM's reasoning shchegrikovich.substack.c... · Posted by u/shchegrikovich
The generated programs are only technically Prolog programs. They use CLPFD, which makes these constraint programs. Prolog programs are quite a bit more tricky with termination issues. I wouldn’t have nitpicked if it wasn’t in the title.
Also, the experiment method has some flaws. Problems are hand-picked out of a random subset of the full set. Why not run the full set?
gorkempacaci commented on Design Patterns Are Temporary, Language Features Are Forever ptrtojoel.dev/posts/desig... · Posted by u/delifue
If I may nitpick, the call to children’s accept methods should be in the visitor, not the parent. Imagine you’re writing an XMLGeneratorVisiter. The visit method for the parent would print <parent>, call child accepts, and then print </parent>. If you do it the way it is done here you lose the control on when the children are visited.
Also, the point of the visitor pattern is not just pattern matching/polymorphism. Of course you could do it with polymorphism or conditionals or whatever. But the visitor pattern reduces coupling and increases cohesion. So you get a more maintainable, testable code base. Pattern matching with a candied switch doesn’t give you that.
Prolog is very, very dead. I love Prolog with all my heart, but it excells at problems that are solved today much more efficiently using neuronal networks. So it's utterly obsolete.
The issue of Prolog is that you need to code your rules manually. Doing ML with Prolog is possible, but very clumsy. Better stick to Python.
Speed is irrelevant, because most problems suitable for Prolog are exponential. Implementation is irrelevant, because SWI-Prolog does all you need with good integrations, except that it's a bit slower. But that's irrelevant, see above.
Learning Prolog is a great experience for any advanced computer science student. It amazes, doesn't it?
Prolog was never good at the things they thought it would be at, like AI, which is better done by ML today, specifically often like you said, with NNs. But it turned out to be good for other things, and those use cases are still alive today, even though there are many competitors. Look at Tiobe index, Prolog's usage is constant just under 1 percent, and has been for decades. So it's good for something.
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