I have some friends who teach at the post-secondary level who ask their students to have ChatGPT write an essay, and as an assignment the student has to grade it, and justify the grade. I thought that was a constructive approach. Probably not what OpenAI is going to be promoting, though.

Where are you seeing this?

One of his former students and colleagues is a friend of mine, he broke the news on his Facebook page.

Thanks.

Lenat (along with Hofstadter) inspired me to come to the US for grad school in hopes of doing AI research. I ended up not going into AI, but still bear a soft spot for Eurisko and Copycat.

I’ve wanted someone to try to build bridges between Cyc, HTM (Numenta) and the FARGitechture for so many years

speaking of which… it’d be great to find a community of more-than-me who can’t stop thinking about FCCA. The book is most famous for being the first product ever sold by Amazon, but I think it deserves a lot more attention

what's FCCA?

Fluid Concepts and Creative Analogies

Hofstadter’s least famous book I guess

published after GEB

Ah! I bought it and read it. And then forgot about it. And then I heard about it and was like, Oh that sounds interesting. So I wanted to buy it again. And Amazon told me "You already bought that book before, are you sure?", and I was like "Oh yes I did, and I read it before, thanks!"

I’ve had a strong hunch for years that the copycat/etc. architecture could generalize to so many more use cases, but I don’t think anyone’s tried very hard to turn it into a framework rather than a collection of one-offs

If you compare it to SHRDLU, which was famously a pile of spaghetti hacks, it definitely deserves to be further along the spectrum towards “generally applicable to multiple problem domains”

I think that's a good hunch. Most of the techniques in FCCA (here, I am using the acronym!) seemed to me, at the time of reading, basically unimplementable. Today, thanks to LLMs, this might have changed. If one were to use an LLM as the API to the natural language text, and implement some copycat processes on top of that, the result might be interesting.

e.g. first-class modeling of concepts and their relationships (i.e. the “slipnet”)… the conceptual relationships are part of how the system works, not just a bunch of tags

Cyc has higher-order reasoning, so the concepts really do have semantic functions

With ANNs you hope they’ll learn the concepts but good luck explaining anything 🙂

Denny Vrandečić could you say more about the association you’re seeing between FCCA and LLMs? My recollection is the FCCA problem domains were mainly about simpler symbolic systems

IIRC (which may not be the case, as said, I previously forgot I have even read the book!), a lot of the work in FCCA is in the space of concepts. The best way we can get to concepts is through natural language texts. But until recently, our ability to write code against natural language text was limited. This has dramatically changed with LLMs, as we can now use text like a database (it's expensive, but we can!). So it should be possible to implement the reasoning algorithms from FCCA and have them run on a text corpus.

Again, I might misremember everything.

There are two ways I can interpret what you’re saying, probably both wrong:

• use an LLM to help populate nodes and edges in the slipnet — basically semantic autocomplete?
• build an FCCA system that understands/learns grammar?

I think 1. Not just help, but do it automatically.