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]>> 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? Or as you might frame it "i'm not smart enough".
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