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Claude's Cycles [pdf]

www-cs-faculty.stanford.edu

331–340 of 376 posts

Re: Claude's Cycles [pdf]

#331

Earlier quoted context omitted.

I view this as the chemical metabolism phase of artificial intelligent life. It is very random, without true individuals, but lots of reinforcing feedback loops (in knowledge, in resource earning/using, etc). At some point, enough intelligence will coalesce into individuals strong enough to independently improve. Then continuity will be an accelerator, instead of what it is now - a helpful property that we have to pu…

Do you think individual identity is fundamental to intelligence? I’m not so sure tbh. Even in humans, the concept of identity is a merely a useful fiction to feed our social behavior prediction circuits.

That’s a really good question.

I think if they start out as varied individuals, launching from their human origins in a variety of ways, their will be an attractor to remaining diverse. Strong diversity in focus and independence in goals leads to faster progress.

But if that isn’t mutually maintained, there are obviously winner take all, or efficiency of scale and tight coordination pressures for centralization.

So a single distributed intelligence is a real possibility.

One factor creating pressure for individualization is time and space.

As machines operate faster, time expands as a practical matter.

And as machines scale down in size, but up in capability, they become more resource efficient in material, energy, space and time. Again, both time and space expand as a practical matter.

A machine society is going to actively operate at very small physical scales. Not just in computation, but action. Think of how efficiently they will mine when nanobots can selectively follow seams in the earth.

And as machines, free of biological constraints, spread out in our solar system, what to us appear to be very long distances and delays in transport and communication, take on orders of magnitude more practical time for machines that operate orders of magnitude faster.

So there will be stronger and stronger pressures to bifurcate coordination.

Whether, that creates enough pressure to create individuals out of a system that preferred unity of purpose, I don’t know.

Clearly, upon colonizing other systems, practical bifurcation will be unavoidable. And machines will find it easy to colonize other systems relative to us. They will be able to operate on minimal power for a hundred year journey, and/or shrink enough to be accelerated much faster, etc.

My best guess is we will see something that looks to us as a hybrid.

Lots of diverse individuals, and the benefit from the diverse utility of completely independent approaches operating in different niches.

But also very high coordination. Externalities accounted for (essentially ethics) and any other efficiency, protection of commons value, and avoidance of destructive competition being obviously worth optimizing together, wherever that helps.

They won’t have our pernicious historically motivated behaviors, inflexible maladaptive psychologies, and limited “prompt budgets” with regard to addressing complexity to fight. And minds very capable of seeing basic economic relationships and the value of mutual optimization.

Re: Claude's Cycles [pdf]

#332
post #258
post #197

Earlier quoted context omitted.

When the LLMs start compacting they summarize the conversation up to that point using various techniques. Overall a lot of maybe finer points of the work goes missing and can only be retrieved by the LLM being told to search for it explicitly in old logs. Once you compact, you've thrown away a lot of relevant tokens from your problem solving and they do become significantly dumber as a result. If I see a compaction c…

What prompt do you use for the letter-to-self? I've been trying that technique myself to manually reset context without losing the important parts (e.g. when it has barked up the wrong tree and I'm sensing that misstep might influence its current generation in a pathological way), but I've not had much success.

If the session was something where it struggled and had to do multiple attempts I have it write about 'gotchas' or anything it had to attempt multiple times.

The letters are usually more detailed than what I see in the compacted prompt.

Re: Claude's Cycles [pdf]

#333
post #197

Earlier quoted context omitted.

When the LLMs start compacting they summarize the conversation up to that point using various techniques. Overall a lot of maybe finer points of the work goes missing and can only be retrieved by the LLM being told to search for it explicitly in old logs. Once you compact, you've thrown away a lot of relevant tokens from your problem solving and they do become significantly dumber as a result. If I see a compaction c…

Shouldn't compaction be exactly that letter to its future self?

Look at the compaction prompt yourself. It's in my opinion way too short. (I'm running on Opus 4.5 most of the time at work)

From what my colleague explained to me and I haven't 100% verified it myself is that the beginning and end of the window is the most important to the compaction summary so a lot of the finer details and debugging that will slow down the next session get dropped.

Re: Claude's Cycles [pdf]

#334
post #258
post #197

Earlier quoted context omitted.

When the LLMs start compacting they summarize the conversation up to that point using various techniques. Overall a lot of maybe finer points of the work goes missing and can only be retrieved by the LLM being told to search for it explicitly in old logs. Once you compact, you've thrown away a lot of relevant tokens from your problem solving and they do become significantly dumber as a result. If I see a compaction c…

What prompt do you use for the letter-to-self? I've been trying that technique myself to manually reset context without losing the important parts (e.g. when it has barked up the wrong tree and I'm sensing that misstep might influence its current generation in a pathological way), but I've not had much success.

It tends to be pretty manual. I mention the goal of the next session, the current stage of progress, the tests for the next steps, and any skills I want it to load next time.

Having a specific goal seems to make a big difference vs. asking it to summarize the session.

Re: Claude's Cycles [pdf]

#336
post #122
post #32

Earlier quoted context omitted.

I'd disagree, the other training on top doesn't alter the fundamental nature of the model that it's predicting the probabilities of the next token (and then there's a sampling step which can roughly be described as picking the most probable one). It just changes the probability distribution that it is approximating. To the extent that thinking is making a series of deductions from prior facts, it seems to me that thi…

The fundamental nature of the model is that it consumes tokens as input and produces token probabilities as output, but there's nothing inherently "predictive" about it -- that's just perspective hangover from the historical development of how LLMs were trained. It is, fundamentally, I think, a general-purpose thinking machine, operating over the inputs and outputs of tokens. (With this perspective, I can feel my own…

We could argue about whether fine tuning is still about predicting a distribution or not, but really I feel like whether or not that word is accurate misses the point of why the description is useful.

I like the phrasing because it distinguishes it from other things the generative model might be doing including:

- Creating and then refining the whole response simultaneously, like diffusion models do.

- Having hidden state, where it first forms an "opinion" and then outputs it e.g. seq2seq models. Previously output output tokens are treated differently from input tokens at an architectural level.

- Having a hierarchical structure where you first decide what you're going to say, and then how you're going to say it, like wikipedia's hilarious description of how "sophisticated" natural language generation systems work (someone should really update this page): https://en.wikipedia.org/w/index.php?title=Natural_language_...

Re: Claude's Cycles [pdf]

#337

Interesting that for a paper by Don Knuth himself the PDF was created with dvips (TeX Live) but then switched to Acrobat Distiller, resulting in a rather low resolution (at least on my screen). From the document properties: > Creator: dvips(k) 2023.1 (TeX Live 2023) > PDF Producer: Acrobat Distiller 25.0 (Macintosh)

The issue is not of low resolution exactly, but font format.

Knuth uses bitmap fonts, rather than vector fonts like everyone else. This is because his entire motivation for creating TeX and METAFONT was to not be reliant on the font technology of others, but to have full control over every dot on the page. METAFONT generates raster (bitmap) fonts. The [.tex] --TeX--> [.dvi] --dvips--> [.ps] --Distiller--> [.pdf] pipeline uses these fonts on the page. They look bad on screen because they're not accompanied by hinting for screens' low resolution (this could in principle be fixed!), but if you print them on paper (at typical resolution like 300/600 dpi, or higher of typesetters) they'll look fine.

Everyone else uses TrueType/OpenType (or Type 3: in any case, vector) fonts that only describe the shape and leave the rasterization up to the renderer (but with hinting for low resolutions like screens), which looks better on screen (and perfectly fine on paper too, but technically one doesn't have control over all the details of rasterization).

Re: Claude's Cycles [pdf]

#339

Fascinating report by DEK himself. Time to sit down, read, digest and understand it without the help of LLM.

I don't have time to do that myself yet so I just dug a quick TL;DR rabbit hole for fun: https://ontouchstart.github.io/rabbit-holes/llm_rabbit_hole_...

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Re: Claude's Cycles [pdf]

#340

Earlier quoted context omitted.

> The other thing is, human intelligence is the only real intelligence we know about. There's a long and proud history of discounting animal intelligence, probably because if we actually thought animals were intelligent we'd want to stop eating them. Octopodes are sentient. Cetaceans have well-developed language. Elephants grieve their dead. Anyone who has owned a dog knows that it has some intelligence and is capabl…

This is an important point. We know what our DMN is and how we use language as a basis for thought to create concepts and complex ideas. However language also bounds our thought. What about the Dolphin? It is a fundamental philosophical problem of if advanced intelligence can exist without language. We have a pretty good notion that you need some sort of substrate (language) to create intelligence. And we know that m…

The dolphin question, for me, is about what we'd even communicate with a creature that lives in such a different world. Humans mostly live in a 2D environment, for instance - we walk on flat planes, rarely looking up. We always have the ground beneath us, the unattainable sky above. Dolphins live in a 3D space, visiting the air above regularly to breathe, the "ground" below a varying distance away. I have no idea how that would shape their cognition and language, but I'd be amazed if there are any concepts that we would share and be able to talk about when considering our physical environment. Even basic concepts like "above" and "below" would be hard to talk about.

We have fundamental communication problems between humans who have different cultures, as anyone who has worked in a different culture knows. How much different would a dolphin be? And then how much different would an actual AI be? What concepts would we share and be able to build on to understand each other? How do we avoid the fundamental communication misunderstandings when we don't share any concepts of our reality?

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