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I remember reading and re-reading that article back when it first appeared on the 'net, right after I graduated from CompSci with a big crush on Prolog, paired

I remember reading and re-reading that article back when it first appeared on the 'net, right after I graduated from CompSci with a big crush on Prolog, paired to gigantic gaps in my understanding of it (and of Logic Programming in general). The article looked... not enough. I got a general idea of how Prolog was used in Watson, but not clear enough that I could easily reproduce it myself. Or so I thought back then. Reading it again now, it's clear to me that they used Prolog to implement the rule-based part of their system, whose function was, essentially, to map from an initial parse of a Jeopardy qustion to a semantic representation of the question, then find an answer for it. Similar to what Triska points out in another comment in this thread, this is Prolog's bread and butter and the kind of thing that modern AI approaches can still not do very well, or at all. The downside of course is that they had to encode all those rules in Prolog by hand. Which is not strictly necessary thanks to Inductive Logic Programming approaches, that can learn Prolog programs from data, either on their own, or in an interactive session, collaborating with a human programmer. I hear that IBM now have a dedicated ILP team who seem to be working on problems like that. Let's hope that the Watson debacle doesn't drag the whole thing down with it.

daviddaviddavid 5y ago
Regarding modern AI approaches not being great at what Prolog does, I'm curious if this will ever translate into an uptick in job postings for Prolog (or, at least, rule-based/declarative) jobs. One would expect hybrid systems in which the old school approach played some significant role, but I haven't noticed that happening in the market.
- pinewurst 5y ago
  Rules-based/declarative seems to have ended up as “business rules/logic” in the commercial world (including RPA (feh)). Same uses but devoid of the magic AI glow.
- dunefox 5y ago
  Neurosymbolic AI is a research topic.
- deleted 5y ago
  [deleted]
- nextos 5y ago
  There's some research on inductive logic programming and, program induction, Bayesian programming, etc. I guess it will take some time to become a bit more mature and get to the job market, maybe 5 years? Some groups to look at (not exhaustive): Tenenbaum (MIT), De Raedt (KU Leuven), Muggleton (Imperial).
nextos 5y ago
I was doing lots of Prolog in the past, inspired by The Art / Craft of Prolog plus PAIP, and I also tried to find information to implement a toy Watson but there's next to none. I even talked to some consultants from IBM about this, but all the information I could get was very vague. This might have changed in the meantime. BTW, I had seen your ILP publications in other previous posts and they are quite cool! Contrary to the popular belief, I think there is still a lot of room for logic-based approaches to AI.
- YeGoblynQueenne 5y ago
  Woa, thanks, you make me blush :) All the information that IBM have released about Watson (the original system that won that Jeopardy game) was spread around a dozen reports published in the "IBM Journal of Research and Deelopment". I have the lot on a drive half a continent away, otherwise I'm sure it would be OK to share them. You might be able to find them online, but a very quick look didn't locate them for me. Online versions might be accessible from a university library, although I don't even remember their titles. In short, from memory, Watson started with a shallow parse that was then used to fill in good old frames. If I remember correctly those were then queried by the Prolog rulebase. The shallow parse was by means of a dependency grammar trained from an annotated corpus (so not a language model, say). That's the very high level of it- I read all that back in 2014 or so and I only half-understood it. I seem to remember that one of the reports made a big to-do about a shallow parse being sufficient to solve a good chunk of information retrieval problems.
guenthert 5y ago
Other then that after the hype generated by Watson initially, it seems to have made only a very modest, perhaps underwhelming impact. To those not so familiar with the project, could you elaborate in which sense it has been a debacle?
- YeGoblynQueenne 5y ago
  I don't really know that much about it. It's just that every article I've read after the Jeopardy game, when IBM tried to flog Watson as a super NLP AI for medicine has been strongly negative, to the point that the entire brand has been soiled irreparably to the minds of many, far as a I can tell. More than underwhelming impact, that is.

daviddaviddavid 5y ago

Regarding modern AI approaches not being great at what Prolog does, I'm curious if this will ever translate into an uptick in job postings for Prolog (or, at least, rule-based/declarative) jobs. One would expect hybrid systems in which the old school approach played some significant role, but I haven't noticed that happening in the market.

pinewurst 5y ago
Rules-based/declarative seems to have ended up as “business rules/logic” in the commercial world (including RPA (feh)). Same uses but devoid of the magic AI glow.
dunefox 5y ago
Neurosymbolic AI is a research topic.
deleted 5y ago
[deleted]
nextos 5y ago
There's some research on inductive logic programming and, program induction, Bayesian programming, etc. I guess it will take some time to become a bit more mature and get to the job market, maybe 5 years? Some groups to look at (not exhaustive): Tenenbaum (MIT), De Raedt (KU Leuven), Muggleton (Imperial).

nextos 5y ago

I was doing lots of Prolog in the past, inspired by The Art / Craft of Prolog plus PAIP, and I also tried to find information to implement a toy Watson but there's next to none. I even talked to some consultants from IBM about this, but all the information I could get was very vague. This might have changed in the meantime. BTW, I had seen your ILP publications in other previous posts and they are quite cool! Contrary to the popular belief, I think there is still a lot of room for logic-based approaches to AI.

YeGoblynQueenne 5y ago
Woa, thanks, you make me blush :) All the information that IBM have released about Watson (the original system that won that Jeopardy game) was spread around a dozen reports published in the "IBM Journal of Research and Deelopment". I have the lot on a drive half a continent away, otherwise I'm sure it would be OK to share them. You might be able to find them online, but a very quick look didn't locate them for me. Online versions might be accessible from a university library, although I don't even remember their titles. In short, from memory, Watson started with a shallow parse that was then used to fill in good old frames. If I remember correctly those were then queried by the Prolog rulebase. The shallow parse was by means of a dependency grammar trained from an annotated corpus (so not a language model, say). That's the very high level of it- I read all that back in 2014 or so and I only half-understood it. I seem to remember that one of the reports made a big to-do about a shallow parse being sufficient to solve a good chunk of information retrieval problems.

guenthert 5y ago

Other then that after the hype generated by Watson initially, it seems to have made only a very modest, perhaps underwhelming impact. To those not so familiar with the project, could you elaborate in which sense it has been a debacle?

YeGoblynQueenne 5y ago
I don't really know that much about it. It's just that every article I've read after the Jeopardy game, when IBM tried to flog Watson as a super NLP AI for medicine has been strongly negative, to the point that the entire brand has been soiled irreparably to the minds of many, far as a I can tell. More than underwhelming impact, that is.