Lean is a GOFAI symbolic logic engine. Combining NN LLMs with symbolic proof engines appears to me to be the way to go. NNs are statistical inference; Lean (and others) are logical inference.

Amen. I owned and rode a 1977 Ducati 900ss, an ancestor of Mr. Thompson's ride. It was bullet-fast and had the turning radius of an aircraft carrier. Every time I took it out for a frolic, I was dead straight stone sober. Every. Single. Time.

But at least Thompson did not do a Jackson Pollack pavement painting. My sincere apologies if I caused you any distress.

Sir: While Mr. Thompson's life choices were less than optimal, I defy you to find a better motorcycle road test than the Song of the Sausage Creature:

http://www.latexnet.org/~csmit...

And here is Cycle World's posthumous write-up of same:

https://www.cycleworld.com/201...

My last remark was a bit of whimsy -- I would find it amusing if an unresolved great question in computational complexity was resolved by a computer. I wasn't trying to imply anything.

As for how long it's going to take, who knows ? Fermat's Last Theorem took 358 years, and lots of very bright bulbs took a swing at it, including Gauss and Euler (although both found a bit of traction).

So we will be having the solution to P ?= NP directly, then ? :) Sweet Jesus, maybe so...

I believe you may be confusing statistical inference with logical inference. LLMs use linear algebra to do the former. The latter is the province of propositional and predicate logic (expert systems, theorem provers, etc., for example, Prolog).

What constitutes a "thinking" LLM ?

Quantum blockchain - a distributed ledger where all transactions co-exist in superposition with their reversals. Now we're talkin' about some awesome accounting. Might have saved Elizabeth Holmes the prison time.

Given your handle, I would hope you remember Cover Oregon:

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

Should read "harebrained" instead of "hairbrained". Hares are probably more intelligent than hairs, but what do I know, I'm just chimp++.

Do we infer causality from phenomena that, at their core, are stochastic ? What is the nature of this "time" thing that we refer to ? Are these macro notions just a helpful mirage ? In "Word and Object", from W.V.O. Quine, it was a startling revelation to me that scientific method does not arrive at truth like a mathematical limit, but is rather a way at truth. Which fits with the saying that "all models are wrong, but some are more useful than others."

you can have a baby in one month" -- quotation from chairman Musk

"This is just an ad homonym argument."

Perfect. Made my day.

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

A 747 needs a hangar, not a nightstand.