Mateusz Bagiński

~[agent foundations]

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Why did FHI get closed down? In the end, because it did not fit in with the surrounding administrative culture. I often described Oxford like a coral reef of calcified institutions built on top of each other, a hard structure that had emerged organically and haphazardly and hence had many little nooks and crannies where colorful fish could hide and thrive. FHI was one such fish but grew too big for its hole. At that point it became either vulnerable to predators, or had to enlarge the hole, upsetting the neighbors. When an organization grows in size or influence, it needs to scale in the right way to function well internally – but it also needs to scale its relationships to the environment to match what it is.

I don't quite get what actions are available in the heat engine example.

Is it just choosing a random bit from H or C (in which case we can't see whether it's 0 or 1) OR a specific bit from W (in which case we know whether it's 0 or 1) and moving it to another pool?

Any thoughts on Symbolica? (or "categorical deep learning" more broadly?)

All current state of the art large language models such as ChatGPT, Claude, and Gemini, are based on the same core architecture. As a result, they all suffer from the same limitations.

Extant models are expensive to train, complex to deploy, difficult to validate, and infamously prone to hallucination. Symbolica is redesigning how machines learn from the ground up. 

We use the powerfully expressive language of category theory to develop models capable of learning algebraic structure. This enables our models to have a robust and structured model of the world; one that is explainable and verifiable.

It’s time for machines, like humans, to think symbolically.

  1. How likely is it that Symbolica [or sth similar] produces a commercially viable product?
  2. How likely is it that Symbolica creates a viable alternative for the current/classical DL?
    1. I don't think it's that different from the intentions behind Conjecture's CoEms proposal. (And it looks like Symbolica have more theory and experimental results backing up their ideas.)
      1. Symbolica don't use the framing of AI [safety/alignment/X-risk], but many people behind the project are associated with the Topos Institute that hosted some talks from e.g. Scott Garrabrant or Andrew Critch.
  3. What is the expected value of their research for safety/verifiability/etc?
    1. Sounds relevant to @davidad's plan, so I'd be especially curious to know his take.
  4. How likely is it that whatever Symbolica produces meaningfully contributes to doom (e.g. by advancing capabilities research without at the same time sufficiently/differentially advancing interpretability/verifiability of AI systems)?

(There's also PlantingSpace but their shtick seems to be more "use probabilistic programming and category theory to build a cool Narrow AI-ish product" whereas Symbolica want to use category theory to revolutionize deep learning.)

I'm not aware of any, but you may call it "hybrid ontologies" or "ontological interfacing".

There is an unsolved meta-problem but the meta-problem is an easy problem.

(I skipped straight to ch7, according to your advice, so I may be missing relevant parts from the previous chapters if there are any.)

I probably agree with you on the object level regarding phenomenal consciousness.

That being said, I think it's "more" than a meme. I witnessed at least two people not exposed to the scientific/philosophical literature on phenomenal consciousness reinvent/rediscover the concept on their own.

It seems to me that the first-person perspective we necessarily adopt makes inclines to ascribe to sensations/experiences some ineffable, seemingly irreducible quality. My guess is that we (re)perceive our perception as a meta-modality different from ordinary modalities like vision, hearing, etc, and that causes the illusion. It's plausible that being raised in a WEIRD culture contributes to that inclination.

A butterfly conjecture: While phenomenal consciousness is an illusion, there is something to be said about the first-person perspective being an interesting feature of some minds (sufficiently sophisticated? capable of self-reflection?). It can be viewed as a computational heuristic that makes you "vulnerable" to certain illusions or biases, such as phenomenal consciousness, but also:

  • the difficulty to accept one-boxing in the Newcomb's problem
  • mind-body dualism
  • the naive version of free will illusion, difficulty in accepting physicalism/determinism
  • (maybe) the illusion of being in control over your mind (various sources say that meditation-naive people are often surprised to discover how little control they have over their own mind when they first try meditation)

A catchy term for this line of investigation could be "computational phenomenology".

Wouldn't total updatelessness amount to constantly taking one action? If not, I'm missing something important and would appreciate an explanation of what it is that I'm missing.

My impression was that people stopped seriously working on debate a few years ago

ETA: I was wrong

I think a proof of not-not-X[1] is more apt to be called "a co-proof of X" (which implies X if you [locally] assume the law of the excluded middle).


  1. Or, weaker, very strong [evidence of]/[argument for] not-not-X. ↩︎

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