Lots to catch up on. Cheryl and I have quietly been out of town for a week (SF Bay Area, and Las Vegas). I'll be following up topically ASAP on material relevant to my prior David Eagleman "Inner Cosmos" post. Got a good bit of reading down while gone.
New book coming shortly, reviewed in Science Magazine.
apropos, see "AI Slop and Scientific Publishing."
"Uncertainty?" "Two Cheers for Uncertainty."
SUBSTACK UPDATE: THE LATEST FROM BEN GOERTZEL
Proposing an experimental OmegaHive loop for turning agentic coding into cumulative, testable progress toward human-level AGI and maybe beyond — we are actually building this now, and playing with preliminary versions!
Among the many interesting things that popped up at the AGI-26 conference last week in San Francisco, one of them stuck out for me as being of particular “meta-level” importance.
What I’m talking about is how many conference attendees I talked to who were trying to have their agent hives code AGI for them, by taking a whole bunch of papers off the internet (including my own papers, and others from the Hyperon team) and asking their agents to bash them all together into an AGI codebase and make it tick.
One form this takes uses our own OmegaClaw system. OmegaClaws are agentic loops that wrap up LLMs together with knowledge graphs built on the Hyperon AtomSpace infrastructure, with fairly sophisticated reasoning and pattern matching running over them. The symbolic component supplies the agents with more episodic memory, more long-term memory, more of a sense of self than a vanilla coding agent has. So you take a system like that — not yet an AGI, but possessing a powerful agentic loop, some memory, some reasoning, some notion of who its mother is — and you tell it: download these 25 of Ben’s papers, turn them into code, integrate them into your memory, reason with them, extend yourself.
I think this sort of process has in it the seeds of a workable approach to building AGI.
The main problematic issue here, as anyone who has done a lot of AI research will tell you, is the gap between having a software component that sort of works in some small test — and/or, say, whose workings you can even prove correct with some nice math — and having something that really works at scale and in real life…
Okeee Dokeee, then. I'm a reasonably intelligent guy with a fairly lengthy and varied digitech Sheet, but this cat is well above my pay grade.
Ben is involved with this AGI academic offering:
Tuition for the M.S. will set you back about $32k. Worth it? Were I not 80+ and increasingly physically ailing, I'd consider ponying up.
Another Ben Goertzel thingy:
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This is yet another riveting book. Read a ton of it while returning home to BWI from LAS on Southwest. Lotta dots starting to connect. All of the current Usual Suspects and then some. Musk, Thiel, Zuckerberg, Altman, Page, Brin, Karp...
RETURN TO SOME ADAPTIVE EVOLUTIONARY GROUNDING
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More ASAP...
