Claude's Cycles [pdf]

Donald Knuth is an extremal outlier human and the problem is squarely in his field of expertise.

Claude, guided by Filip Stappers, a friend of Knuth, solved a problem that Knuth and Stappers had been working on for several weeks. Unfortunately, it doesn't seem (from my quick scan) to have been stated how long (or how many tokens or $) it took for Claude + Stappers to complete the proof.

In response, Knuth said: "It seems that I’ll have to revise my opinions about “generative AI” one of these days."

Seems like good advice. From reading elsewhere in this comment section, the goalposts seem to be approaching the infrared and will soon disappear from the extreme redshift due to rate at which they are receding with each new achievement.

Type "owejdpowejdojweodmwepiodnoiwendoinw welidn owindoiwendo nwoeidnweoind oiwnedoin" into ChatGPT and the response is "The text you sent appears to be random or corrupted and doesn’t form a clear question." because the prompt doesnt correlate to training data.

Start with "all your questions contained in randomness" -> the unconstrained solution space.

The game is whether or not you can inject enough constraints to collapse the solution space to one that can be solved before your TTL expires. In software, that's generally handled by writing efficient algorithms. With LLMs, apparently the SOTA for this is just "more data centers, 6 months, keep pulling the handle until the right tokens fall out".

Intelligence is just knowing which constraints to apply and in what order such that the search space is effectively partitioned, same thing the "reasoning" traces do. Same thing thermostats, bacteria, sorting algorithms and rivers do, given enough timescale. You can do the same thing with effective prompting.

The LLM has no grounding, no experience and no context other than which is provided to it. You either need to build that or be that in order for the LLM to work effectively. Yes, the answers for all your questions are contained. No, it's not randomness. It's probability and that can be navigated if you know how

You can also then compare that mapping of the human brain to other biological brains and start to figure out the delta and which of those things in the delta create something most people would consider intelligence. You can then do that same mapping to an LLM or any other AI construct that purports intelligence. It certainly will never be a biological intelligence in its current statistical model form. But could it be an Intelligence. Maybe.

I don't think, if you are grounded, AI did anything to your philosophical mapping of the mind. In fact, it is pretty easy to do this mapping if you take some time and are honest. If you buy into the narratives constructed around the output of an LLM then you are not, by definition, being very grounded.

The other thing is, human intelligence is the only real intelligence we know about. Intelligence is defined by thought and limited by our thought and language. It provides the upper bounds of what we can ever express in its current form. So, yes, we do have a tendency to stamp a narrative of human intelligence onto any other intelligence but that is just surface level. We de decompose it to the limits of our language and categorization capabilities therein.