Comment by mindcrime

i am hoping for an slm "turing tape" small language model where the tokens are instructions for a copycat engine

As somebody who considers himself something of a Semantic Web enthusiast / advocate, and has also read GEB, I can totally relate. To me, this is really one of those "THE ISSUE" things: how can we use some notion of formal logic to solve problems, without being forced to give up hope due to incompleteness and/or the Halting Problem. Clearly you have to give up something as a tradeoff for making this stuff tractable, but I suppose it's an open question what you can tradeoff and how exactly that factors into the algorithm, as well as what guarantees (if any) remain...

Well, to the extent that people equate GOFAI with purely symbolic / logic-based processing, then no, not for my money anyway. I think it's possible to construct systems that use elements of symbolic processing along with sub-symbolic approaches and get useful results. I think of it as (although this is something of an over-simplification) taking symbolic reasoning, relaxing some of the constraints that go along with the guarantees that method makes out the outputs, and accepting a (hopefully only slightly) less desirable output. OR, think about flipping the whole thing around, get an output from, say, an LLM where there might be hallucination(s), and then use a symbolic reasoning system to post-process the output to ensure veracity before sending it to the user. Amazon has done some work along those lines, for example. https://aws.amazon.com/blogs/machine-learning/reducing-hallu...

Anyway this is all somewhat speculative, and I don't want to overstate the "weight" of anything I seem to be claiming here. This is just the direction my interests and inclinations have taken me in.