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Comment by TheUndead96 | Hacker News Reader

I think Prolog and logic programming will have a second renaissance. I think at the very least a general artificial intelligence would require a logical inference engine similar to Prolog.

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I don’t think it will come back as AI, the statistical/differentiable approach proved much more powerful given the amount of data.

I think it will come back in programming tools / program synthesis though. There are many use cases for it and not enough people using in production.

> There are many use cases for it

would you mind expanding on this?

it's been on my backburner to learn prolog, but i have gotten a sense that it could be useful as a side-tool during development.

Equational reasoning makes TDD and property based testing trivial (encode rules by examples, base cases and corner cases, which is the most natural way for humans to think); rule-based system are easier to extend and correct by design (bounded set of possible states); provides more powerful and elegant query languages (E.g. Datalog).

See https://youtu.be/OyfBQmvr2Hc (skip to 1h mark to see some examples)

I think it's actually the complete opposite. The current biomimetism direction being privileged by the modern A.I. trends is most likely the correct way to achieve "True" A.I.

However, Inference-based A.I. is actually needed to properly tackle many of the business problems that are being thrown at ML systems today. Explainability and bias reduction can probably only be be taken so far with the current approaches, and I suspect that this "so far" is not far enough for many tasks. It's definitely the case from a practical standpoint today.

So inference-based A.I. is due for a comeback indeed, but I'd say AGI is looking like one of the main areas where the current techniques might work.

The inference-based methods in AI qre more likely to he of the "probabilistic graphical models" variety (there are already marriages of Bayesian and Deep Learning techniques), and less likely to be of the "first order predicate calculus" variety. We humans don't have a particularly strong logical inference engine either - unless properly trained, people make the silliest logical mistakes and arrive at wrong conclusions all the time.

Right, I meant "prolog-style formal inference engine". My point is that this "human imperfection" also present in probabilistic engines have artifacts that are fundamentally at odds with many business requirements where we are attempting to shoehorn then.

It's almost more of a cultural issue than a technical one. The level of explainability currently desired from automated systems is possibly not achievable, simply because we want to uphold them to a different standard.

Do any of the non-artificial intelligences walking around out there contain a logical inference engine similar to Prolog?

https://en.m.wikipedia.org/wiki/Datomic

Datomic is cool but not an intelligence, artificial or not. The GP was trying to point out that having a prolog-style inference engine is not required for intelligence and pointing to humans as a counterexample to prove why not.

Sorry, I parsed the grandparent as:

?- applicationof(prolog, X), domain(X, Y), nonai(Y).

> non-artificial intelligences walking around out there

I'm not sure what you mean by this. Do you mean people? I don't think our 'inference engine' is much like Prolog, no.

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” (Edsger W. Dijkstra)

--is what he means.

I got nice sentence

Do any birds flying around have engines?

I want to agree with you, but I also want to agree with the hypothetical rebuttal GP is making in my mind:

> Yes, they do have engines similar to those found in planes, cars, etc. and so do humans - fuel goes in, chemistry happens, and energy is provided for physical movement in the form of rotation, flapping, or one foot in front of the other.

Idk who I agree with, I suppose it's a fairly pointless exercise in 'how similar constitutes 'similar'' all the way down.

Yes. Logic wasn't conjured up from abstract ideas, but from a concerted effort to distill the essence of what humans (regular, average people) find reasonable and convincing. (To mention just one example, there is a reason one of George Boole's major works is called "The Laws of Thought".)

Our strategies for understanding language also involve inference and unification that is similar to logic programming. This is not to say the exact semantics and evaluation strategy of Prolog is what humans carry around, but part of our cognitive apparatus clearly operates in a manner similar to logic, and by extension Prolog.

I discussed this topic with one of the inventors of Prolog recently: https://thesearch.space/episodes/1-the-poet-of-logic-program...

I have no doubt that human or other intelligences can emulate and even to some extent intuit these rules. If you believe that's a _requirement_ for their intelligence, I think that's a stronger claim. Not one I'd vehemently argue against, but not one I'd personally be comfortable making.

I don't believe we emulate a set of rules that were somehow arbitrarily created at some point in history. I believe logic is something we discover (not invent) and it has roots in both human cognition and the physical world, and it's not fully known or understood exactly how they emerge. Hence, logic is still a developing field, and logic programming has indeed contributed to it.

"Intelligence" is a vague term, but if you mean the ability to act rationally or even in a coherently self-interested way, then surely logic has something to do with it.

I don't really mean anything special by intelligence, but let's flatter ourselves that humans are born with some measure of it. I personally find it more likely than not that our particular form of intelligence is able to then _learn_ various rules of logical inference as a kind of metapattern. When I say 'emulate' I mean that we can, if we want, sit down with a pencil and paper and _force_ ourselves to evaluate things exactly via these rules, even if we don't instinctively follow them (or do so fuzzily).

Obviously I could very easily be wrong, and we could possess hard coded rules of logical inference which form part of the basis for all the other things we do that you might call intelligence. But I'm not sure that anyone should claim "a general artificial intelligence would require a logical inference engine similar to Prolog".

Plotkin's thesis! You had an interview with Kowalski? Wow :)

You're on my wish list for interviewees too :)

Wot me? Haha! Wait another 20 years maybe! But thanks, that's so kind :D

I listened to this a few weeks ago -- looking forward to the next episode!

I'm pretty sure reasoning is important towards that goal, but how that is achieved is much less clear. Perhaps some probabilistic additions at the least.

I doubt it. Prolog is inherently based on DFS that usually leads to inefficient algorithms. Cut operator then turns any source into an unreadable mess.

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