I did have to laugh. When Pieter originally wrote, I thought: Just at the moment, is there anybody that wants to talk to a Ph.D. about anything? Even without paying for it? They are much more sought-after as objects of public ridicule or disparagement.
But DaveW says it so much better than I do :) Eric > On May 21, 2025, at 22:26, Prof David West <[email protected]> wrote: > > Pieter noted, > > "Sam Altman seems to suggest that we may soon be able to rent access to a > PhD-level AI for as little as $10,000 to $20,000. Although that will > obviously be a game-changer, I would still make the bar higher than that." > > Sam is making the exact same mistake that Simon and Newell did, nearly 40 > years ago—asserting that Ph.D. "intelligence" is the acme of human > intelligence. So wrong. > > I might even concede that generative AI is capable of Ph.D. level > "intelligence" but that is probably the lowest possible bar to achieve. > > davew, Ph.D. > > > > > On Wed, May 21, 2025, at 12:38 AM, Pieter Steenekamp wrote: >> I agree with your view that what matters is the input and output — what goes >> in and what comes out. From that perspective, I align with most experts in >> AI who acknowledge that while the progress is remarkable, there's still a >> qualitative gap between human and AI outputs when compared at the highest >> levels. Even under this "modified Turing test" lens, top humans still >> maintain the edge. (Though I say this with affection, I wouldn't place my >> bets on some of the Afrikaners featured on recent American talk shows — so >> no, in my opinion, not all humans qualify.) >> >> This naturally leads to the million-dollar question: if — and if so, when — >> AI will surpass the very best humans across all scientific domains. Sam >> Altman seems to suggest that we may soon be able to rent access to a >> PhD-level AI for as little as $10,000 to $20,000. Although that will >> obviously be a game-changer, I would still make the bar higher than that. >> I'm struggling a bit to define this properly, so although it's not a >> definition, for now I'll stick to I'll know it when I see it. >> >> On Wed, 21 May 2025 at 00:40, glen <[email protected] >> <mailto:[email protected]>> wrote: >> Well, the reason I'm lumping the Markov blanket (MB) with the holographic >> principle (HP) is because in either case the innards are occult. This veers >> quite a bit from Nosta's Whole in Every Part or "resolution" rhetoric. But >> it hints at the hairball mysteriousness of whatever it is the LLM is doing >> in those innards and focuses on its output (and, by extension, its input). >> Whereas the analogy between a light hologram and a black hole breaks down is >> that the hologram's 3D pattern is hallucinatory. And even if we don't know >> what's inside a black hole, few people would think the innards of black >> holes just don't exist at all in the same way the 3D shapes of holograms >> "don't exist". There's *enough* information on the sphere, or in the 2D >> surface. That's what makes it holographic. >> >> And from a behaviorist perspective, we can say the same thing about a MB. >> Maybe the state of the innards are somewhat occluded. But through >> manipulation of the outer surface, we can build a good *enough* model of the >> innards. >> >> From this perspective, all this hand wringing about whether an LLM is Truly >> intelligent, or Truly creative, or Truly whatever, is metaphysical hooey. >> What matters is what goes in and what comes out ... similar to holograms, >> MBs, and the surface of a black hole. >> >> >> On 5/20/25 12:21 PM, Pieter Steenekamp wrote: >> > “You can’t see the forest for the trees.” >> > >> > My interpretation of the article, without really focussing on the details >> > of holograms really spoke to me. >> > >> > The author makes three points that I find helpful: >> > >> > LLMs don’t just reflect things—they rebuild meaning from patterns, more >> > like a hologram than a mirror. >> > >> > Just because they sound smooth and fluent doesn’t mean they truly >> > understand. >> > >> > They copy the shape of knowledge, not its substance. >> > >> > I don’t take these ideas too literally, but the metaphors help. LLMs seem >> > to do more than just repeat facts. Sometimes, their answers feel like they >> > see the bigger picture—even if they’re not truly thinking. >> > >> > That’s where I find the hologram metaphor useful. Unlike a mirror, which >> > just shows what’s in front of it, a hologram builds an image from many >> > angles. LLMs don’t just give us back what we said—they sometimes pull >> > together patterns we didn’t notice ourselves. >> > >> > But then of course, Google DeepMind claims that their AI does create new >> > knowledge >> > (https://www.wired.com/story/google-deepminds-ai-agent-dreams-up-algorithms-beyond-human-expertise/ >> > >> > <https://www.wired.com/story/google-deepminds-ai-agent-dreams-up-algorithms-beyond-human-expertise/>), >> > but, I don't get too excited about that - their claim of "new knowledge" >> > is very limited and based on a framework already set by humans. >> > >> > On Tue, 20 May 2025 at 20:39, steve smith <[email protected] >> > <mailto:[email protected]> <mailto:[email protected] >> > <mailto:[email protected]>>> wrote: >> > >> > >> > On 5/20/25 10:19 AM, glen wrote: >> > > I was confused by your post. But that resolved after reading the >> > article. >> > >> > > If we think of Markov blankets and the holographic principle, then >> > the >> > > analogy to a hologram makes a bit more sense. >> > >> > This was outside my consideration when I read it, but I definitely >> > appreciate the gesture toward Markov blankets. I've had an intuition >> > that in some sense the markov Blanket of an "entity" IS the entity for >> > the purposes of other entities interacting with it... a bit like the >> > software contract/interface design business? >> > >> > I'm still pretty perplexed by the cosmological/physics "holographic >> > principle"... just not enough depth or focus applied on my end quite >> > yet? 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