In all the hype and debate and excitement and frustration around AI, I think sometimes the fact that we've achieved something really cool gets lost. I want to talk about that a bit, which I'll try to do in a simple way, without too much math or computer science.

There's a surprising amount of intelligence encoded in applied language. To me that's the most remarkable insight in LLM technology. Except it's not really surprising at all. The whole point of language is to encode intelligence. Communication, at its core, is about sharing intelligence. LLMs agents are a way of turning the intelligence encoded in language, particularly written language, into useful work.

You might imagine that language is just the starting point when building LLMs. That it gets converted into computer stuff and then it's not language anymore. But in a way it's language all the way down. Distill language into math and then run gradient descent on it and the intelligence (for lack of a better term) bubbles out.

Forgive that hyperbole, but there is something a little bit magical about it, and the technology is entirely unmagical. The magic is in the language.

At the core the tech is pretty simple. First you go and get all of the language. Just completely idiotic amounts of applied language. Because there's a threshold: if you don't use enough language you don't get a useful result. The more language you use, assuming it's good quality, the more useful the result.

After you have all of the language, you convert it into tokens, which are essentially pieces of words represented as numbers. You also compute a compressed version of the relationships between the tokens. The frontier labs don't say how much this costs publicly anymore but it's safe to say hundreds of millions in compute are required for this process. Each time you do it.

Once you've determined the token relationships, you've pre trained an LLM. You have the initial weights. At this point your LLM can output credible prose pretty reliably when you run inference on the weights. Meaning that you can take a given set of language tokens (a prompt) and determine which token should come next, over and over again, until you have a response. The fluency of the prose can be uncanny, and there are latent tendencies towards useful output, but you can't really do much with it yet.

The next step, fine tuning, modifies the weights in order to nudge the inference towards useful things like instruction following, tool use and reasoning. Or a simulacrum of reasoning. Fine tuning is a massive, multi step, iterative process that turns your LLM into a useful tool that can do more than output believable prose.

Something that's really fascinating to me about fine tuning is that what you're training is still the language relationship weights, and what comes out during inference is still language. But now it's language that is more likely to result in useful output and behaviors. Language is the substrate that LLMs reason through. A model that's more likely to infer the words "but what if I look at it another way" is more likely to consider multiple possibilities. A model that reliably infers language around tool use in appropriate situations is an agent. The behavior is encoded in the language.

After tens of millions in fine tuning costs, assuming you got it right, you have the core of a LLM that can function as an AI agent. You can put it in a harness and ask it to do things in the language of your choice and it will actually be able to do them a shockingly high percentage of the time. It can even do things that weren't explicitly part of the training. That's something which has never happened before outside of science fiction. Until recently it was one of those computer sciencey things that was probably going to happen someday, after we were all dead.

It sucks that this tech revolution is being driven by the capital class, and that it's happening as a mad dash for market domination and golden IPOs. In a more perfect world technology derived from collective human intelligence would be a public good rather than a profit driver.

But nevertheless, the ability to imprint some part of human intelligence into an autonomous agent is a remarkable achievement. One that we can't yet see the full size of. And it's possible not because we typed instructions into an interface, but because we've spent centuries encoding our intelligence into language.

Not sure where this goes but I am looking for an app to help fill in between other reading practice we do with our 5 year old.

This won't be the main tool to help them learn, just trying to find something fun to help learn a bit. Does anyone have recommendations for fun and educational reading apps?

Hi
Seems we need to compile jpegli from git.

https://github.com/google/jpegli

I'm not able to do this at present.
Maybe a tildean person here is. :-)

I want to experiment and compare results with my installed mozjpeg.

Anybody know where there is a jpegli precompiled?
Something to drop into Linux usr/local/bin.
Or a windows executable to use with wine.

Blogpost... https://opensource.googleblog.com/2024/04/introducing-jpegli-new-jpeg-coding-library.html

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Well, the time is about up for this month's CGA, so I hope everyone that gave Lufia II a shot enjoyed it and defeated the Sinstrals forever. JK, it's a prequel, we know they came back :)

Please feel free to talk freely about the game in the comments and let everyone know how far you got, what you liked, and what you didn't.

I was able to finish the game and I beat the ancient cave (my true goal) on my second attempt. Did anyone else give the ancient cave a try?

Our next host is u/Boojum with the amazing game The Legend of Zelda: A Link to the Past. I'm super excited about this one, even though I've played it a dozen times, as it is my favorite Zelda game.

He's Canadian and he'll always have the most ridiculous source (see the post title) or the worst, goalpost-moving response ("who said that?" "how?" "well the lady said there was no impact because they just didn't get their $50M payday but they still had all the medicine." "I don't think the number is zero, but it's not what people said it would be.")

I know the easiest answer is just ignore him like most people do. But it is so infuriating when there are hundreds of thousands of people actively dying.

Have you watched any movies recently you want to discuss? Any films you want to recommend or are hyped about? Feel free to discuss anything here.

Please just try to provide fair warning of spoilers if you can.