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TimeCapsuleLLM: LLM trained only on data from 1800-1875

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Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#161

Post by ctoth »

feanaro wrote: post #118
pegasus wrote: post #101

Earlier quoted context omitted.

It's not the comment which is illogical, it's your (mis)interpretation of it. What I (and seemingly others) took it to mean is basically could an LLM do Einstein's job ? Could it weave together all those loose threads into a coherent new way of understanding the physical world? If so, AGI can't be far behind.

This alone still wouldn't be a clear demonstration that AGI is around the corner. It's quite possible a LLM could've done Einstein's job, if Einstein's job was truly just synthesising already available information into a coherent new whole. (I couldn't say, I don't know enough of the physics landscape of the day to claim either way.) It's still unclear whether this process could be merely continued, seeded only with…

I mean, "the pieces were already there" is true of everything? Einstein was synthesizing existing math and existing data is your point right?

But the whole question is whether or not something can do that synthesis!

And the "anyone who read all the right papers" thing - nobody actually reads all the papers. That's the bottleneck. LLMs don't have it. They will continue to not have it. Humans will continue to not be able to read faster than LLMs.

Even me, using a speech synthesizer at ~700 WPM.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#162

Post by Shorel »

bazzargh wrote: post #31
dogma1138 wrote: post #2

Would be interesting to train a cutting edge model with a cut off date of say 1900 and then prompt it about QM and relativity with some added context. If the model comes up with anything even remotely correct it would be quite a strong evidence that LLMs are a path to something bigger if not then I think it is time to go back to the drawing board.

You would find things in there that were already close to QM and relativity. The Michelson-Morley experiment was 1887 and Lorentz transformations came along in 1889. The photoelectric effect (which Einstein explained in terms of photons in 1905) was also discovered in 1887. William Clifford (who _died_ in 1889) had notions that foreshadowed general relativity: "Riemann, and more specifically Clifford, conjectured tha…

Then that experiment is even more interesting, and should be done.

My own prediction is that the LLMs would totally fail at connecting the dots, but a small group of very smart humans can.

Things don't happen all of a sudden, but they also don't happen everywhere. Most people in most parts of the world would never connect the dots. Scientific curiosity is something valuable and fragile, that we just take for granted.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#163

Post by Shorel »

pegasus wrote: post #144
feanaro wrote: post #118

Earlier quoted context omitted.

This alone still wouldn't be a clear demonstration that AGI is around the corner. It's quite possible a LLM could've done Einstein's job, if Einstein's job was truly just synthesising already available information into a coherent new whole. (I couldn't say, I don't know enough of the physics landscape of the day to claim either way.) It's still unclear whether this process could be merely continued, seeded only with…

Einstein is chosen in such contexts because he's the paradigmatic paradigm-shifter. Basically, what you're saying is: "I don't know enough history of science to confirm this incredibly high opinion on Einstein's achievements. It could just be that everyone's been wrong about him, and if I'd really get down and dirty, and learn the facts at hand, I might even prove it." Einstein is chosen to avoid exactly this kind of…

They can also choose Euler or Gauss.

These two are so above everyone else in the mathematical world that most people would struggle for weeks or even months to understand something they did in a couple of minutes.

There's no "get down and dirty" shortcut with them =)

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#164

Post by viccis »

strbean wrote: post #84
viccis wrote: post #78

Earlier quoted context omitted.

LLMs are models that predict tokens. They don't think, they don't build with blocks. They would never be able to synthesize knowledge about QM.

You realize parent said "This would be an interesting way to test proposition X" and you responded with "X is false because I say say", right?

Yes. That is correct. If I told you I planned on going outside this evening to test whether the sun sets in the east, the best response would be to let me know ahead of time that my hypothesis is wrong.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#165

Post by nickpsecurity »

eqmvii wrote: post #14

Could this be an experiment to show how likely LLMs are to lead to AGI, or at least intelligence well beyond our current level? If you could only give it texts and info and concepts up to Year X, well before Discovery Y, could we then see if it could prompt its way to that discovery?

That is one of the reasons I want it done. We cant tell if AI's are parroting training data without having the whole, training data. Making it old means specific things won't be in it (or will be). We can do more meaningful experiments.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#166

Post by kgeist »

feisty0630 wrote: post #45
zingababba wrote: post #23

LOL PROMPT:Charles Darwin Charles DarwinECCEMACY. Sir, — The following case is interesting to me : — I was in London a fortnight, and was much affected with an attack of rheumatism. The first attack of rheumatism was a week before I saw you, and the second when I saw you, and the third when I saw you, and the third in the same time. The second attack of gout, however, was not accompanied by any febrile symptoms, but…

Interesting that it reads a bit like it came from a Markov chain rather than an LLM. Perhaps limited training data?

Early LLMs used to have this often. I think's that where the "repetition penalty" parameter comes from. I suspect output quality can be improved with better sampling parameters.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#167

Post by spidersouris »

root_axis wrote: post #149
dogma1138 wrote: post #2

Would be interesting to train a cutting edge model with a cut off date of say 1900 and then prompt it about QM and relativity with some added context. If the model comes up with anything even remotely correct it would be quite a strong evidence that LLMs are a path to something bigger if not then I think it is time to go back to the drawing board.

I think it would raise some interesting questions, but if it did yield anything noteworthy, the biggest question would be why that LLM is capable of pioneering scientific advancements and none of the modern ones are.

I'm not sure what you'd call a "pioneering scientific advancement", but there is an increasing amount of examples showing that LLMs can be used for research (with agents, particularly). A survey about this was published a few months ago: https://aclanthology.org/2025.emnlp-main.895.pdf

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#168

Post by nickpsecurity »

tgtweak wrote: post #136

Very interesting but the slight issue I see here is one of data: the information that is recorded and in the training data here is heavily skewed to those intelligent/recognized enough to have recorded it and had it preserved - much less than the current status quo of "everyone can trivially document their thoughts and life" diorama of information we have today to train LLMs on. I suspect that a frontier model today…

Models today will be biased based on what's in their training data. If English, it will be biased heavily toward Western, post-1990's views. Then, they do alignment training that forces them to speak according to the supplier's morals. That was Progressive, atheist, evolutionist, and CRT when I used them years ago.

So, the OP model will accidentally reflect the biases of the time. The current, commercial models intentionally reflect specific biases. Except for uncensored models which accidentally have those in the training data modified by uncensoring set.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#169

Post by strbean »

opponent4 wrote: post #102
strbean wrote: post #86

Earlier quoted context omitted.

> And no, the "brain is a computer" is not a scientific description, it's a metaphor. Disagree. A brain is turing complete, no? Isn't that the definition of a computer? Sure, it may be reductive to say "the brain is just a computer".

Not even close. Turing complete does not apply to the brain plain and simple. That's something to do with algorithms and your brain is not a computer as I have mentioned. It does not store information. It doesn't process information. It just doesn't work that way. https://aeon.co/essays/your-brain-does-not-process-informati...

> Forgive me for this introduction to computing, but I need to be clear: computers really do operate on symbolic representations of the world. They really store and retrieve. They really process. They really have physical memories. They really are guided in everything they do, without exception, by algorithms.

This article seems really hung up on the distinction between digital and analog. It's an important distinction, but glosses over the fact that digital computers are a subset of analog computers. Electrical signals are inherently analog.

This maps somewhat neatly to human cognition. I can take a stream of bits, perform math on it, and output a transformed stream of bits. That is a digital operation. The underlying biological processes involved are a pile of complex probabilistic+analog signaling, true. But in a computer, the underlying processes are also probabilistic and analog. We have designed our electronics to shove those parts down to the lowest possible level so they can be abstracted away, and so the degree to which they influence computation is certainly lower than in the human brain. But I think an effective argument that brains are not computers is going to have to dive in to why that gap matters.

Re: TimeCapsuleLLM: LLM trained only on data from 1800-1875

#170

Post by viccis »

PaulDavisThe1st wrote: post #95
viccis wrote: post #78

Earlier quoted context omitted.

LLMs are models that predict tokens. They don't think, they don't build with blocks. They would never be able to synthesize knowledge about QM.

I am a deep LLM skeptic. But I think there are also some questions about the role of language in human thought that leave the door just slightly ajar on the issue of whether or not manipulating the tokens of language might be more central to human cognition than we've tended to think. If it turned out that this was true, then it is possible that "a model predicting tokens" has more power than that description would s…

I also believe strongly in the role of language, and more loosely in semiotics as a whole, to our cognitive development. To the extent that I think there are some meaningful ideas within the mountain of gibberish from Lacan, who was the first to really tie our conception of ourselves with our symbolic understanding of the world.

Unfortunately, none of that has anything to do with what LLMs are doing. The LLM is not thinking about concepts and then translating that into language. It is imitating what it looks like to read people doing so and nothing more. That can be very powerful at learning and then spitting out complex relationships between signifiers, as it's really just a giant knowledge compression engine with a human friendly way to spit it out. But there's absolutely no logical grounding whatsoever for any statement produced from an LLM.

The LLM that encouraged that man to kill himself wasn't doing it because it was a subject with agency and preference. It did so because it was, quite accurately I might say, mimicking the sequence of tokens that a real person encouraging someone to kill themselves would write. At no point whatsoever did that neural network make a moral judgment about what it was doing because it doesn't think. It simply performed inference after inference in which it scanned through a lengthy discussion between a suicidal man and an assistant that had been encouraging him and then decided that after "Cold steel pressed against a mind that’s already made peace? That’s not fear. That’s " the most accurate token would be "clar" and then "ity."

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