jsomae
@jsomae@lemmy.ml
- Comment on Hertz, showing the difference between science and engineering 4 hours ago:
Mm for instance, I think in some contexts markets are pretty powerful, like prediction markets are pretty good at predicting things. (Not saying they’re flawless – polymarket likely overpredicted Trump’s victory). Or that benign-looking regulation is frequently detrimental to the public – while not libertarians at all, Abundance makes a good case for repealing a lot of regulation related to construction. Such regulation is often motivated by people who want to preserve the value of their homes, even though on the surface it appears to be about environmental concerns. (Obviously, I think the environment is important, so we shouldn’t just repeal everything. Just that we should be more critical of such regulation.) Another example is how the U.S. banned civilian supersonic aviation in its airspace because of disruptive sonic booms; apparently the technology now exists to keep such booms very quiet, but the regulation persists, because it’s not booms which were banned but instead supersonic speed as a proxy for booms.
- Comment on Hertz, showing the difference between science and engineering 1 day ago:
When talking with libertarians you should keep in mind they have completely different axiomatic values. It is often the case that they understand a certain policy would be on net bad for everyone, they simply don’t care. They are rarely utilitarian about those issues.
I get along much better with libertarians who justify libertarianism with values extrinsic to just “muh freedom” – they are usually much more willing to yield ground in places where I can convince them that a libertarian policy would be net negative, and they have also moved me to be more open minded about some things I thought I would never agree with.
- Comment on AGI achieved 🤖 3 days ago:
I know IPA but I can’t read English text written in pure IPA as fast as I can read English text written normally. I think this is the case for almost anyone who has learned the IPA and knows English.
- Comment on AGI achieved 🤖 3 days ago:
More like calling out people who can’t read romaji, I think. It’s just not a natural encoding for most Japanese people, even if they can work it out if you give them time.
- Comment on AGI achieved 🤖 4 days ago:
I mean, among people who are proficient with IPA, they still struggle to read whole sentences written entirely in IPA. Similarly, people who speak and read chinese struggle to read entire sentences written in pinyin. I’m not saying people can’t do it, just that it’s much less natural for us (even though it doesn’t really seem like it ought to be.)
- Comment on Anon plays Metroid 4 days ago:
based.
game doesn’t save your hitpoints, starts you at 30 hp every time
cringe.
- Comment on AGI achieved 🤖 4 days ago:
When we see LLMs struggling to demonstrate an understanding of what letters are in each of the tokens that it emits or understand a word when there are spaces between each letter, we should compare it to a human struggling to understand a word written in IPA format (/sʌtʃ əz ðɪs/) even though we can understand the word spoken aloud perfectly fine.
- Comment on AGI achieved 🤖 4 days ago:
This is deepseek model right? OP was posting about GPT o3
- Comment on AGI achieved 🤖 4 days ago:
Yes that’s right, LLMs are context-free. They don’t have internal state. When I say “update on new information” I really mean “when new information is available in its context window, its response takes that into account.”
- Comment on AGI achieved 🤖 4 days ago:
Well – and I don’t meant this to be antagonistic – I agree with everything you’ve said except for the last sentence where you say “and therefore you’re wrong.” Look, I’m not saying LLMs function well, or that they’re good for society, or anything like that. I’m saying that tokenization errors are really their own thing that are unrelated to other errors LLMs make. If you want to dunk on LLMs then yeah be my guest. I’m just saying that this one type of poor behaviour is unrelated to the other kinds of poor behaviour.
- Comment on AGI achieved 🤖 4 days ago:
as I said, postmodernist lol. I’m coming from the absolutist angle.
- Comment on AGI achieved 🤖 5 days ago:
in what context? LLMs are extremely good at bridging from natural language to API calls. I dare say it’s one of the few use cases that have decisively landed on “yes, this is something LLMs are actually good at.” Maybe not five nines of reliability, but language itself doesn’t have five nines of reliability.
- Comment on AGI achieved 🤖 5 days ago:
The claim is not that all LLMs are agents, but rather that agents (which incorporate an LLM as one of their key components) are more powerful than an LLM on its own.
We don’t know how far away we are from recursive self-improvement. We might already be there to be honest; how much of the job of an LLM researcher can already be automated? It’s unclear if there’s some ceiling to what a recursively-improved GPT4.x-w/e can do though; maybe there’s a key hypothesis it will never formulate on the quest for self-improvement.
- Comment on AGI achieved 🤖 5 days ago:
Turns out spicy autocomplete can contribute to the bottom line. Capitalism :(
- Comment on AGI achieved 🤖 5 days ago:
Well yeah. You’re preaching to the choir lol.
- Comment on AGI achieved 🤖 5 days ago:
I suppose if you’re going to be postmodernist about it, but that’s beyond my ability to understand. The only complete solution I know to Theseus’ Ship is “the universe is agnostic as to which ship is the original. Identity of a composite thing is not part of the laws of physics.” Not sure why you put scare quotes around it.
- Comment on AGI achieved 🤖 5 days ago:
sorry, I only have a regular brain, haven’t updated to the metaphysical edition :/
- Comment on AGI achieved 🤖 5 days ago:
Hallucinations aren’t relevant to my point here. I’m not defending that AIs are a good source of information, and I agree that hallucinations are dangerous (either that or misusing LLMs is dangerous). I also admit that for language learning, artifacts caused from tokenization could be very detrimental to the user.
The point I am making is that LLMs struggling with these kind of tokenization artifacts is poor evidence for assuming anything about their behaviour on other tasks.
- Comment on AGI achieved 🤖 5 days ago:
Because LLMs operate at the token level, I think it would be a more fair comparison with humans to ask why humans can’t produce the IPA spelling words they can say, /nɔr kæn ðeɪ ˈizəli rid θɪŋz ˈrɪtən ˈpjʊrli ɪn aɪ pi ˈeɪ/ despite the fact that it should be simple to – they understand the sounds after all. I’d be impressed if somebody could do this too! But that most people can’t shouldn’t really move you to think humans must be fundamentally stupid because of this one curious artifact.
- Comment on AGI achieved 🤖 5 days ago:
Well that’s a recent improvement. GPT3 was very bad at that, and GPT4 still makes mistakes.
- Comment on AGI achieved 🤖 5 days ago:
Congrats, you’ve discovered reductionism. The human brain also doesn’t know things, as it’s composed of electrical synapses made of molecules that obey the laws of physics and direct one’s mouth to make words in response to signals that come from the ears.
Not saying LLMs don’t know things, but your argument as to why they don’t know things has no merit.
- Comment on AGI achieved 🤖 5 days ago:
You’re right, I shouldn’t have called it a riddle. Still, being a fucking thought experiment doesn’t preclude having a solution. Theseus’ ship is another famous fucking thought experiment, which has also been solved.
- Comment on AGI achieved 🤖 5 days ago:
nice
- Comment on AGI achieved 🤖 5 days ago:
This might well be true yeah. But that’s still good news for AI companies who want to replace humans – bar’s lower than they thought.
- Comment on AGI achieved 🤖 5 days ago:
The Rowan Atkinson thing isn’t misunderstanding, it’s understanding but having been misled. I’ve literally done this exact thing myself, say something was a hoax (because in the past it was) but then it turned out there was newer info I didn’t know about. I’m not convinced LLMs as they exist today don’t prioritize sources – if trained naively, sure, but these days they can, for instance, integrate search results, and can update on new information. If the LLM can answer correctly only after checking a web search, and I can do the same only after checking a web search, that’s a score of 1-1.
because we know what “understanding” is
Really? Who claims to know what understanding is? Do you think it’s possible there can ever be an AI (even if different from an LLM) which is capable of “understanding?” How can you tell?
- Comment on AGI achieved 🤖 5 days ago:
oh does he have a treatise on the subject?
- Comment on AGI achieved 🤖 5 days ago:
The LLM isn’t aware of its own limitations in this regard. The specific problem of getting an LLM to know what characters a token comprises has not been the focus of training. It’s a totally different kind of error than other hallucinations, it’s almost entirely orthogonal, but other hallucinations are much more important to solve, whereas being able to count the number of letters in a word or add numbers together is not very important, since as you point out, there are already programs that can do that.
- Comment on AGI achieved 🤖 5 days ago:
Can you explain the difference between understanding the question and generating the words that might logically follow? I’m aware that it’s essentially a more powerful version of how auto-correct works, but why should we assume that shows some lack of understanding at a deep level somehow?
- Comment on AGI achieved 🤖 5 days ago:
Transformers were pretty novel in 2017, I don’t know if they were really around before that.
Anyway, I’m doubtful that a larger corpus is what’s needed at this point. (Though that said, there’s a lot more text remaining in instant messager chat logs like discord that probably have yet to be integrated into LLMs. Not sure.) I’m also doubtful that scaling up is going to keep working, but it wouldn’t surprise that much me if it does keep working for a long while. My guess is that there’s some small tweaks to be discovered that really improve things a lot but still basically like like repetitive training as you put it.
- Comment on AGI achieved 🤖 5 days ago:
what do you mean by spell fine? They’re just emitting the tokens for the words. Like, it’s not writing “strawberry,” it’s writing tokens <302, 1618, 19772>, which correspond to st, raw, and berry respectively. If you ask it to put a space between each letter, that will disrupt the tokenization mechanism, and it’s going to be quite liable to making mistakes.
I don’t think it’s really fair to say that the lookup 19772 -> berry counts as the LLM being able to spell, since the LLM isn’t operating at that layer. It doesn’t really emit letters directly. I would argue its inability to reliably spell words when you force it to go letter-by-letter or answer queries about how words are spelled is indicative of its poor ability to spell.