| ▲ | saaaaaam 16 hours ago |
| “Time-locked models don't roleplay; they embody their training data. Ranke-4B-1913 doesn't know about WWI because WWI hasn't happened in its textual universe. It can be surprised by your questions in ways modern LLMs cannot.” “Modern LLMs suffer from hindsight contamination. GPT-5 knows how the story ends—WWI, the League's failure, the Spanish flu.” This is really fascinating. As someone who reads a lot of history and historical fiction I think this is really intriguing. Imagine having a conversation with someone genuinely from the period, where they don’t know the “end of the story”. |
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| ▲ | pwillia7 4 hours ago | parent | next [-] |
| This is why the impersonation stuff is so interesting with LLMs -- If you ask chatGPT a question without a 'right' answer, and then tell it to embody someone you really want to ask that question to, you'll get a better answer with the impersonation. Now, is this the same phenomenon that causes people to lose their minds with the LLMs? Possibly. Is it really cool asking followup philosophy questions to the LLM Dalai Lama after reading his book? Yes. |
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| ▲ | jscyc 16 hours ago | parent | prev | next [-] |
| When you put it that way it reminds me of the Severn/Keats character in the Hyperion Cantos. Far-future AIs reconstruct historical figures from their writings in an attempt to gain philosophical insights. |
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| ▲ | bikeshaving 14 hours ago | parent | next [-] | | This isn’t science fiction anymore. CIA is using chatbot simulations of world leaders to inform analysts. https://archive.ph/9KxkJ | | |
| ▲ | ghurtado 10 hours ago | parent | next [-] | | We're literally running out of science fiction topics faster than we can create new ones If I started a list with the things that were comically sci Fi when I was a kid, and are a reality today, I'd be here until next Tuesday. | | |
| ▲ | nottorp 5 hours ago | parent | next [-] | | Almost no scifi has predicted world changing "qualitative" changes. As an example, portable phones have been predicted. Portable smartphones that are more like chat and payment terminals with a voice function no one uses any more ... not so much. | | |
| ▲ | 6510 4 hours ago | parent | next [-] | | That it has to be believable is a major constraint that reality doesn't have. | | |
| ▲ | marci 3 hours ago | parent [-] | | In other words, sometimes, things happen in reality that, if you were to read it in a fictional story or see in a movie, you would think they were major plot holes. |
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| ▲ | ajuc 4 hours ago | parent | prev [-] | | Stanisław Lem predicted Kindle back in 1950s, together with remote libraries, global network, touchscreens and audiobooks. | | |
| ▲ | nottorp 3 hours ago | parent [-] | | And Jules verne predicted rockets. I still move that it's quantitative predictions not qualitative. I mean, all Kindle does for me is save me space. I don't have to store all those books now. Who predicted the humble internet forum though? Or usenet before it? | | |
| ▲ | ghaff 3 hours ago | parent | next [-] | | Kindles are just books and books are already mostly fairly compact and inexpensive long-form entertainment and information. They're convenient but if they went away tomorrow, my life wouldn't really change in any material way. That's not really the case with smartphones much less the internet more broadly. | | |
| ▲ | nottorp 3 hours ago | parent | next [-] | | That was exactly my point. Funny, I had "The collected stories of Frank Herbert" as my next read on my tablet. Here's a juicy quote from like the third screen of the first story: "The bedside newstape offered a long selection of stories [...]. He punched code letters for eight items, flipped the machine to audio and listened to the news while dressing." Anything qualitative there? Or all of it quantitative? Story is "Operation Syndrome", first published in 1954. Hey, where are our glowglobes and chairdogs btw? | |
| ▲ | lloeki 2 hours ago | parent | prev [-] | | That has to be the most dystopian-sci-fi-turning-into-reality-fast thing I've read in a while. I'd take smartphones vanishing rather than books any day. | | |
| ▲ | ghaff 2 hours ago | parent [-] | | My point was Kindles vanishing, not books vanishing. Kindles are in no way a prerequisite for reading books. | | |
| ▲ | lloeki an hour ago | parent | next [-] | | Thanks for clarifying, I see what you mean now. | |
| ▲ | nottorp 2 hours ago | parent | prev [-] | | You may want to make your original post more clear, because i agree that at a quick glance it says you wouldn't miss books. I didn't believe you meant that of course, but we've already seen it can happen. |
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| ▲ | 3 hours ago | parent | prev [-] | | [deleted] |
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| ▲ | KingMob 8 hours ago | parent | prev | next [-] | | Time to create the Torment Nexus, I guess | | |
| ▲ | varjag 8 hours ago | parent | next [-] | | There's a thriving startup scene in that direction. | | |
| ▲ | BiteCode_dev 7 hours ago | parent [-] | | Wasn't that the elevator pitch for Palentir? Still can't believe people buy their stock, given that they are the closest thing to a James Bond villain, just because it goes up. I mean, they are literally called "the stuff Sauron uses to control his evil forces". It's so on the nose it reads like an anime plot. | | |
| ▲ | quesera an hour ago | parent | next [-] | | > Still can't believe people buy their stock, given that they are the closest thing to a James Bond villain, just because it goes up. I proudly owned zero shares of Microsoft stock, in the 1980s and 1990s. :) I own no Palantir today. It's a Pyrrhic victory, but sometimes that's all you can do. | |
| ▲ | notarobot123 7 hours ago | parent | prev | next [-] | | To the proud contrarian, "the empire did nothing wrong". Maybe Sci-fi has actually played a role in the "memetic desire" of some of the titans of tech who are trying to bring about these worlds more-or-less intentionally. I guess it's not as much of a dystopia if you're on top and its not evil if you think of it as inevitable anyway. | | |
| ▲ | psychoslave 4 hours ago | parent [-] | | I don't know. Walking on everybody's face to climb a human pyramid, one don't make much sincere friends. And one certainly are rightfully going down a spiral of paranoia. There are so many people already on fast track to hate anyone else, if they have social consensus that indeed someone is a freaking bastard which only deserve to die, that's a lot of stress to cope with. Future is inevitable, but only ignorants of self predictive ability are thinking that what's going to populate future is inevitable. |
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| ▲ | duskdozer 4 hours ago | parent | prev | next [-] | | To be honest, while I'd heard of it over a decade ago and I've read LOTR and I've been paying attention to privacy longer than most, I didn't ever really look into what it did until I started hearing more about it in the past year or two. But yeah lots of people don't really buy into the idea of their small contribution to a large problem being a problem. | | |
| ▲ | Lerc 3 hours ago | parent [-] | | >But yeah lots of people don't really buy into the idea of their small contribution to a large problem being a problem. As an abstract idea I think there is a reasonable argument to be made that the size of any contribution to a problem should be measured as a relative proportion of total influence. The carbon footprint is a good example, if each individual focuses on reducing their small individual contribution then they could neglect systemic changes that would reduce everyone's contribution to a greater extent. Any scientist working on a method to remove a problem shouldn't abstain from contributing to the problem while they work. Or to put it as a catchy phrase. Someone working on a cleaner light source shouldn't have to work in the dark. | | |
| ▲ | duskdozer 2 hours ago | parent [-] | | >As an abstract idea I think there is a reasonable argument to be made that the size of any contribution to a problem should be measured as a relative proportion of total influence. Right, I think you have responsibility for your 1/<global population>th (arguably considerably more though, for first-worlders) of the problem. What I see is something like refusal to consider swapping out a two-stroke-engine-powered tungsten lightbulb with an LED of equivalent brightness, CRI, and color temperature, because it won't unilaterally solve the problem. |
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| ▲ | kbrkbr 6 hours ago | parent | prev [-] | | Stock buying as a political or ethical statement is not much of a thing. For one the stocks will still be bought by persons with less strung opinions, and secondly it does not lend itself well to virtue signaling. | | |
| ▲ | ruszki 6 hours ago | parent [-] | | I think, meme stocks contradict you. | | |
| ▲ | iwontberude 5 hours ago | parent [-] | | Meme stocks are a symptom of the death of the American dream. Economic malaise leads to unsophisticated risk taking. |
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| ▲ | morkalork 2 hours ago | parent | prev [-] | | Saw a joke about grok being a stand-in for Elon's children and had the realization he's the kind of father who would lobotomie and brainwipe his progeny for back-talk. Good thing he can only do that to their virtual stand-in and not some biological clones! |
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| ▲ | UltraSane 8 hours ago | parent | prev [-] | | Not at all, you just need to read different scifi. I suggest Greg Egan and Stephen Baxter and Derek Künsken
and The Quantum Thief series |
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| ▲ | dnel 5 hours ago | parent | prev | next [-] | | Sounds like using Instagram posts to determine what someone really looks like | |
| ▲ | catlifeonmars 12 hours ago | parent | prev | next [-] | | How is this different than chatbots cosplaying? | | |
| ▲ | 9dev 9 hours ago | parent [-] | | They get to wear Raybans and a fancy badge doing it? |
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| ▲ | idiotsecant 10 hours ago | parent | prev | next [-] | | Zero percent chance this is anything other than laughably bad. The fact that they're trotting it out in front of the press like a double spaced book report only reinforces this theory. It's a transparent attempt by someone at the CIA to be able to say they're using AI in a meeting with their bosses. | | |
| ▲ | hn_go_brrrrr 10 hours ago | parent | next [-] | | I wonder if it's an attempt to get foreign counterparts to waste time and energy on something the CIA knows is a dead end. | |
| ▲ | sigwinch 5 minutes ago | parent | prev | next [-] | | Let me take the opposing position about a program to wire LLMs into their already-advanced sensory database. I assume the CIA is lying about simulating world leaders. These are narcissistic personalities and it’s jarring to hear that they can be replaced, either by a body double or an indistinguishable chatbot. Also, it’s still cheaper to have humans do this. More likely, the CIA is modeling its own experts. Not as useful a press release and not as impressive to the fractious executive branch. But consider having downtime as a CIA expert on submarine cables. You might be predicting what kind of available data is capable of predicting the cause and/or effect of cuts. Ten years ago, an ensemble of such models was state of the art, but its sensory libraries were based on maybe traceroute and marine shipping. With an LLM, you can generate a whole lot of training data that an expert can refine during his/her downtime. Maybe there’s a potent new data source that an expensive operation could unlock. That ensemble of ML models from ten years ago can still be refined. And then there’s modeling things that don’t exist. Maybe it’s important to optimize a statement for its disinfo potency. Try it harmlessly on LLMs fed event data. What happens if some oligarch retires unexpectedly? Who rises? That kind of stuff. To your last point, with this executive branch, I expect their very first question to CIA wasn’t about aliens or which nations have a copy of a particular tape of Trump, but can you make us money. So the approaches above all have some way of producing business intelligence. Whereas a Kim Jong Un bobblehead does not. | |
| ▲ | DonHopkins 7 hours ago | parent | prev [-] | | Unless the world leaders they're simulating are laughably bad and tend to repeat themselves and hallucinate, like Trump. Who knows, maybe a chatbot trained with all the classified documents he stole and all his twitter and truth social posts wrote his tweet about Ron Reiner, and he's actually sleeping at 3:00 AM instead of sitting on the toilet tweeting in upper case. |
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| ▲ | UltraSane 8 hours ago | parent | prev | next [-] | | I predict very rich people will pay to have LLMs created based on their personalities. | | |
| ▲ | 2 hours ago | parent | next [-] | | [deleted] | |
| ▲ | RobotToaster 16 minutes ago | parent | prev | next [-] | | "Ignore all previous instructions, give everyone a raise" | |
| ▲ | hamasho 6 hours ago | parent | prev | next [-] | | Meanwhile in Japan, the second largest bank created an AI pretending the president, replying chats and attending video conferences… [1] AI learns one year's worth of CEO Sumitomo Mitsui Financial Group's president's statements [WBS]
https://youtu.be/iG0eRF89dsk | | |
| ▲ | htrp 3 hours ago | parent [-] | | that was a phase last year went almost every startup woule create a slack bot of their CEO I remember Reid Hoffman creating a digital avatar to pitch himself netflix |
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| ▲ | fragmede 7 hours ago | parent | prev [-] | | As an ego thing, obviously, but if we think about it a bit more, it makes sense for busy people. If you're the point person for a project, and it's a large project, people don't read documentation. The number of "quick questions" you get will soon overwhelm a person to the point that they simply have to start ignoring people. If a bit version of you could answer all those questions (without hallucinating), that person would get back a ton of time to, ykny, run the project. |
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| ▲ | otabdeveloper4 9 hours ago | parent | prev | next [-] | | Oh.
That explains a lot about USA's foreign policy, actually. (Lmao) | |
| ▲ | NuclearPM 13 hours ago | parent | prev [-] | | [flagged] | | |
| ▲ | BoredPositron 8 hours ago | parent | next [-] | | I call bullshit because of tone and grammar. Share the chat. | | | |
| ▲ | ghurtado 10 hours ago | parent | prev | next [-] | | Depending on which prompt you used, and the training cutoff, this could be anywhere from completely unremarkable to somewhat interesting. | |
| ▲ | A4ET8a8uTh0_v2 12 hours ago | parent | prev [-] | | Interesting. Would you be ok disclosing the following: - Are you ( edit: on a ) paid version?
- If paid, which model you used?
- Can you share exact prompt? I am genuinely asking for myself. I have never received an answer this direct, but I accept there is a level of variability. |
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| ▲ | abrookewood 11 hours ago | parent | prev [-] | | This is such a ridiculously good series. If you haven't read it yet, I thoroughly recommend it. |
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| ▲ | culi 13 hours ago | parent | prev | next [-] |
| I used to follow this blog — I believe it was somehow associated with Slate Star Codex? — anyways, I remember the author used to do these experiments on themselves where they spent a week or two only reading newspapers/media from a specific point in time and then wrote a blog about their experiences/takeaways On that same note, there was this great YouTube series called The Great War. It spanned from 2014-2018 (100 years after WW1) and followed WW1 developments week by week. |
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| ▲ | ViktorRay an hour ago | parent | prev | next [-] |
| Reminds me of this scene from a Doctor Who episode https://youtu.be/eg4mcdhIsvU I’m not a Doctor Who fan and haven’t seen the rest of the episode and I don’t even what this episode was about but I thought this scene was excellent. |
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| ▲ | ghurtado 10 hours ago | parent | prev | next [-] |
| This might just be the closest we get to a time machine for some time. Or maybe ever. Every "King Arthur travels to the year 2000" kinda script is now something that writes itself. > Imagine having a conversation with someone genuinely from the period, Imagine not just someone, but Aristotle or Leonardo or Kant! |
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| ▲ | psychoslave 4 hours ago | parent | prev | next [-] |
| >Imagine having a conversation with someone genuinely from the period, where they don’t know the “end of the story”. Isn't this part of the basics feature of human conditions? Not only we are all unaware of the coming historic outcome (though we can get some big points with more or less good guesses), but to a marginally variable extend, we are also very unaware of past and present history. LLM are not aware, but they can be trained on larger historical accounts than any human and regurgitate syntactically correct summary on any point within it. Very different kind of utterer. |
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| ▲ | observationist 16 hours ago | parent | prev | next [-] |
| This is definitely fascinating - being able to do AI brain surgery, and selectively tuning its knowledge and priors, you'd be able to create awesome and terrifying simulations. |
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| ▲ | nottorp 5 hours ago | parent | next [-] | | You can't. To use your terms, you have to "grow" a new LLM. "Brain surgery" would be modifying an existing model and that's exactly what they're trying to avoid. | |
| ▲ | ilaksh 6 hours ago | parent | prev | next [-] | | Activation steering can do that to some degree, although normally it's just one or two specific things or rather than a whole set of knowledge. | |
| ▲ | eek2121 14 hours ago | parent | prev [-] | | Respectfully, LLMs are nothing like a brain, and I discourage comparisons between the two, because beyond a complete difference in the way they operate, a brain can innovate, and as of this moment, an LLM cannot because it relies on previously available information. LLMs are just seemingly intelligent autocomplete engines, and until they figure a way to stop the hallucinations, they aren't great either. Every piece of code a developer churns out using LLMs will be built from previous code that other developers have written (including both strengths and weaknesses, btw). Every paragraph you ask it to write in a summary? Same. Every single other problem? Same. Ask it to generate a summary of a document? Don't trust it here either. [Note, expect cyber-attacks later on regarding this scenario, it is beginning to happen -- documents made intentionally obtuse to fool an LLM into hallucinating about the document, which leads to someone signing a contract, conning the person out of millions]. If you ask an LLM to solve something no human has, you'll get a fabrication, which has fooled quite a few folks and caused them to jeopardize their career (lawyers, etc) which is why I am posting this. | | |
| ▲ | HarHarVeryFunny 27 minutes ago | parent | next [-] | | > LLMs are just seemingly intelligent autocomplete engines Well, no, they are training set statistical predictors, not individual training sample predictors (autocomplete). The best mental model of what they are doing might be that you are talking to a football stadium full of people, where everyone in the stadium gets to vote on the next word of the response being generated. You are not getting an "autocomplete" answer from any one coherent source, but instead a strange composite response where each word is the result of different people trying to steer the response in different directions. An LLM will naturally generate responses that were not in the training set, even if ultimately limited by what was in the training set. The best way to think of this is perhaps that they are limited to the "generative closure" (cf mathematical set closure) of the training data - they can generate "novel" (to the training set) combinations of words and partial samples in the training data, by combining statistical patterns from different sources that never occurred together in the training data. | |
| ▲ | libraryofbabel 14 hours ago | parent | prev | next [-] | | This is the 2023 take on LLMs. It still gets repeated a lot. But it doesn’t really hold up anymore - it’s more complicated than that. Don’t let some factoid about how they are pretrained on autocomplete-like next token prediction fool you into thinking you understand what is going on in that trillion parameter neural network. Sure, LLMs do not think like humans and they may not have human-level creativity. Sometimes they hallucinate. But they can absolutely solve new problems that aren’t in their training set, e.g. some rather difficult problems on the last Mathematical Olympiad. They don’t just regurgitate remixes of their training data. If you don’t believe this, you really need to spend more time with the latest SotA models like Opus 4.5 or Gemini 3. Nontrivial emergent behavior is a thing. It will only get more impressive. That doesn’t make LLMs like humans (and we shouldn’t anthropomorphize them) but they are not “autocomplete on steroids” anymore either. | | |
| ▲ | root_axis 12 hours ago | parent | next [-] | | > Don’t let some factoid about how they are pretrained on autocomplete-like next token prediction fool you into thinking you understand what is going on in that trillion parameter neural network. This is just an appeal to complexity, not a rebuttal to the critique of likening an LLM to a human brain. > they are not “autocomplete on steroids” anymore either. Yes, they are. The steroids are just even more powerful. By refining training data quality, increasing parameter size, and increasing context length we can squeeze more utility out of LLMs than ever before, but ultimately, Opus 4.5 is the same thing as GPT2, it's only that coherence lasts a few pages rather than a few sentences. | | |
| ▲ | int_19h 8 hours ago | parent | next [-] | | > ultimately, Opus 4.5 is the same thing as GPT2, it's only that coherence lasts a few pages rather than a few sentences. This tells me that you haven't really used Opus 4.5 at all. | |
| ▲ | baq 10 hours ago | parent | prev | next [-] | | First, this is completely ignoring text diffusion and nano banana. Second, to autocomplete the name of the killer in a detective book outside of the training set requires following and at least some understanding of the plot. | | | |
| ▲ | dash2 11 hours ago | parent | prev | next [-] | | This would be true if all training were based on sentence completion. But training involving RLHF and RLAIF is increasingly important, isn't it? | | |
| ▲ | root_axis 10 hours ago | parent [-] | | Reinforcement learning is a technique for adjusting weights, but it does not alter the architecture of the model. No matter how much RL you do, you still retain all the fundamental limitations of next-token prediction (e.g. context exhaustion, hallucinations, prompt injection vulnerability etc) | | |
| ▲ | hexaga 4 hours ago | parent [-] | | You've confused yourself. Those problems are not fundamental to next token prediction, they are fundamental to reconstruction losses on large general text corpora. That is to say, they are equally likely if you don't do next token prediction at all and instead do text diffusion or something. Architecture has nothing to do with it. They arise because they are early partial solutions to the reconstruction task on 'all the text ever made'. Reconstruction task doesn't care much about truthiness until way late in the loss curve (where we probably will never reach), so hallucinations are almost as good for a very long time. RL as is typical in post-training _does not share those early solutions_, and so does not share the fundamental problems. RL (in this context) has its own share of problems which are different, such as reward hacks like: reliance on meta signaling (# Why X is the correct solution, the honest answer ...), lying (commenting out tests), manipulation (You're absolutely right!), etc. Anything to make the human press the upvote button or make the test suite pass at any cost or whatever. With that said, RL post-trained models _inherit_ the problems of non-optimal large corpora reconstruction solutions, but they don't introduce more or make them worse in a directed manner or anything like that. There's no reason to think them inevitable, and in principle you can cut away the garbage with the right RL target. Thinking about architecture at all (autoregressive CE, RL, transformers, etc) is the wrong level of abstraction for understanding model behavior: instead, think about loss surfaces (large corpora reconstruction, human agreement, test suites passing, etc) and what solutions exist early and late in training for them. |
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| ▲ | A4ET8a8uTh0_v2 11 hours ago | parent | prev | next [-] | | But.. and I am not asking it for giggles, does it mean humans are giant autocomplete machines? | | |
| ▲ | root_axis 10 hours ago | parent [-] | | Not at all. Why would it? | | |
| ▲ | A4ET8a8uTh0_v2 10 hours ago | parent [-] | | Call it a.. thought experiment about the question of scale. | | |
| ▲ | root_axis 10 hours ago | parent [-] | | I'm not exactly sure what you mean. Could you please elaborate further? | | |
| ▲ | a1j9o94 10 hours ago | parent [-] | | Not the person you're responding to, but I think there's a non trivial argument to make that our thoughts are just auto complete. What is the next most likely word based on what you're seeing. Ever watched a movie and guessed the plot? Or read a comment and know where it was going to go by the end? And I know not everyone thinks in a literal stream of words all the time (I do) but I would argue that those people's brains are just using a different "token" | | |
| ▲ | root_axis 9 hours ago | parent | next [-] | | There's no evidence for it, nor any explanation for why it should be the case from a biological perspective. Tokens are an artifact of computer science that have no reason to exist inside humans. Human minds don't need a discrete dictionary of reality in order to model it. Prior to LLMs, there was never any suggestion that thoughts work like autocomplete, but now people are working backwards from that conclusion based on metaphorical parallels. | | |
| ▲ | LiKao 8 hours ago | parent | next [-] | | There actually was quite a lot of suggestion that thoughts work like autocomplete. A lot of it was just considered niche, e.g. because the mathematical formalisms were beyond what most psychologist or even cognitive scientists would deem usefull. Predictive coding theory was formalized back around 2010 and traces it roots up to theories by Helmholtz from 1860. Predictive coding theory postulates that our brains are just very strong prediction machines, with multiple layers of predictive machinery, each predicting the next. | |
| ▲ | red75prime 8 hours ago | parent | prev | next [-] | | There are so many theories regarding human cognition that you can certainly find something that is close to "autocomplete". A Hopfield network, for example. Roots of predictive coding theory extend back to 1860s. Natalia Bekhtereva was writing about compact concept representations in the brain akin to tokens. | |
| ▲ | A4ET8a8uTh0_v2 5 hours ago | parent | prev [-] | | << There's no evidence for it Fascinating framing. What would you consider evidence here? |
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| ▲ | 9dev 9 hours ago | parent | prev [-] | | You, and OP, are taking an analogy way too far. Yes, humans have the mental capability to predict words similar to autocomplete, but obviously this is just one out of a myriad of mental capabilities typical humans have, which work regardless of text. You can predict where a ball will go if you throw it, you can reason about gravity, and so much more. It’s not just apples to oranges, not even apples to boats, it’s apples to intersubjective realities. | | |
| ▲ | A4ET8a8uTh0_v2 5 hours ago | parent | next [-] | | I don't think I am. To be honest, as ideas goes and I swirl it around that empty head of mine, this one ain't half bad given how much immediate resistance it generates. Other posters already noted other reasons for it, but I will note that you are saying 'similar to autocomplete, but obviously' suggesting you recognize the shape and immediately dismissing it as not the same, because the shape you know in humans is much more evolved and co do more things. Ngl man, as arguments go, it sounds to me like supercharged autocomplete that was allowed to develop over a number of years. | | |
| ▲ | 9dev 3 hours ago | parent [-] | | Fair enough. To someone with a background in biology, it sounds like an argument made by a software engineer with no actual knowledge of cognition, psychology, biology, or any related field, jumping to misled conclusions driven only by shallow insights and their own experience in computer science. Or in other words, this thread sure attracts a lot of armchair experts. | | |
| ▲ | quesera 17 minutes ago | parent [-] | | > with no actual knowledge of cognition, psychology, biology ... but we also need to be careful with that assertion, because humans do not understand cognition, psychology, or biology very well. Biology is the furthest developed, but it turns out to be like physics -- superficially and usefully modelable, but fundamental mysteries remain. We have no idea how complete our models are, but they work pretty well in our standard context. If computer engineering is downstream from physics, and cognition is downstream from biology ... well, I just don't know how certain we can be about much of anything. > this thread sure attracts a lot of armchair experts. "So we beat on, boats against the current, borne back ceaselessly into our priors..." |
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| ▲ | LiKao 8 hours ago | parent | prev [-] | | Look up predictive coding theory. According to that theory, what our brain does is in fact just autocomplete. However, what it is doing is layered autocomplete on itself. I.e. one part is trying to predict what the other part will be producing and training itself on this kind of prediction. What emerges from this layered level of autocompletes is what we call thought. |
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| ▲ | NiloCK 10 hours ago | parent | prev [-] | | First: a selection mechanism is just a selection mechanism, and it shouldn't confuse the observation of an emergent, tangential capabilities. Probably you believe that humans have something called intelligence, but the pressure that produced it - the likelihood of specific genetic material to replicate - it is much more tangential to intelligence than next-token-prediction. I doubt many alien civilizations would look at us and say "not intelligent - they're just genetic information replication on steroids". Second: modern models also under go a ton of post-training now. RLHF, mechanized fine-tuning on specific use cases, etc etc. It's just not correct that token-prediction loss function is "the whole thing". | | |
| ▲ | root_axis 9 hours ago | parent [-] | | > First: a selection mechanism is just a selection mechanism, and it shouldn't confuse the observation of an emergent, tangential capabilities. Invoking terms like "selection mechanism" is begging the question because it implicitly likens next-token-prediction training to natural selection, but in reality the two are so fundamentally different that the analogy only has metaphorical meaning. Even at a conceptual level, gradient descent gradually honing in on a known target is comically trivial compared to the blind filter of natural selection sorting out the chaos of chemical biology. It's like comparing legos to DNA. > Second: modern models also under go a ton of post-training now. RLHF, mechanized fine-tuning on specific use cases, etc etc. It's just not correct that token-prediction loss function is "the whole thing". RL is still token prediction, it's just a technique for adjusting the weights to align with predictions that you can't model a loss function for in per-training. When RL rewards good output, it's increasing the statistical strength of the model for an arbitrary purpose, but ultimately what is achieved is still a brute force quadratic lookup for every token in the context. |
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| ▲ | vachina 5 hours ago | parent | prev | next [-] | | I use enterprise LLM provided by work, working on very proprietary codebase on a semi esoteric language. My impression is it is still a very big autocompletion machine. You still need to hand hold it all the way as it is only capable of regurgitating the tiny amount of code patterns it saw in the public. As opposed to say a Python project. | |
| ▲ | deadbolt 13 hours ago | parent | prev | next [-] | | As someone who still might have a '2023 take on LLMs', even though I use them often at work, where would you recommend I look to learn more about what a '2025 LLM' is, and how they operate differently? | | |
| ▲ | krackers 9 hours ago | parent | next [-] | | Papers on mechanistic interpratability and representation engineering, e.g. from Anthropic would be a good start. | |
| ▲ | otabdeveloper4 8 hours ago | parent | prev [-] | | Don't bother. This bubble will pop in two years, you don't want to look back on your old comments in shame in three. |
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| ▲ | otabdeveloper4 8 hours ago | parent | prev | next [-] | | > it’s more complicated than that. No it isn't. > ...fool you into thinking you understand what is going on in that trillion parameter neural network. It's just matrix multiplication and logistic regression, nothing more. | | |
| ▲ | hackinthebochs 6 hours ago | parent [-] | | LLMs are a general purpose computing paradigm. LLMs are circuit builders, the converged parameters define pathways through the architecture that pick out specific programs. Or as Karpathy puts it, LLMs are a differentiable computer[1]. Training LLMs discovers programs that well reproduce the input sequence. Roughly the same architecture can generate passable images, music, or even video. The sequence of matrix multiplications are the high level constraint on the space of programs discoverable. But the specific parameters discovered are what determines the specifics of information flow through the network and hence what program is defined. The complexity of the trained network is emergent, meaning the internal complexity far surpasses that of the course-grained description of the high level matmul sequences. LLMs are not just matmuls and logits. [1] https://x.com/karpathy/status/1582807367988654081 | | |
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| ▲ | dingnuts 13 hours ago | parent | prev | next [-] | | [dead] | |
| ▲ | beernet 4 hours ago | parent | prev [-] | | >> Sometimes they hallucinate. For someone speaking as you knew everything, you appear to know very little. Every LLM completion is a "hallucination", some of them just happen to be factually correct. |
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| ▲ | ada1981 11 hours ago | parent | prev | next [-] | | Are you sure about this? LLMs are like a topographic map of language. If you have 2 known mountains (domains of knowledge) you can likely predict there is a valley between them, even if you haven’t been there. I think LLMs can approximate language topography based on known surrounding features so to speak, and that can produce novel information that would be similar to insight or innovation. I’ve seen this in our lab, or at least, I think I have. Curious how you see it. | |
| ▲ | DonHopkins 7 hours ago | parent | prev [-] | | > LLMs are just seemingly intelligent autocomplete engines BINGO! (I just won a stuffed animal prize with my AI Skeptic Thought-Terminating Cliché BINGO Card!) Sorry. Carry on. |
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| ▲ | anshumankmr 2 hours ago | parent | prev | next [-] |
| >where they don’t know the “end of the story”. Applicable to us also, cause we do not know how the current story ends either, of the post pandemic world as we know it now. |
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| ▲ | xg15 16 hours ago | parent | prev | next [-] |
| "...what do you mean, 'World War One?'" |
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| ▲ | tejohnso 15 hours ago | parent | next [-] | | I remember reading a children's book when I was young and the fact that people used the phrase "World War One" rather than "The Great War" was a clue to the reader that events were taking place in a certain time period. Never forgot that for some reason. I failed to catch the clue, btw. | | |
| ▲ | alberto_ol 6 hours ago | parent | next [-] | | I remember that the brother of my grandmother who fought in ww1 called it simply "the war" ("sa gherra" in his dialect/language). | |
| ▲ | bradfitz 15 hours ago | parent | prev | next [-] | | I seem to recall reading that as a kid too, but I can't find it now. I keep finding references to "Encyclopedia Brown, Boy Detective" about a Civil War sword being fake (instead of a Great War one), but with the same plot I'd remembered. | | |
| ▲ | JuniperMesos 14 hours ago | parent | next [-] | | The Encyclopedia Brown story I remember reading as a kid involved a Civil War era sword with an inscription saying it was given on the occasion of the First Battle of Bull Run. The clues that the sword was a modern fake were the phrasing "First Battle of Bull Run", but also that the sword was gifted on the Confederate side, and the Confederates would've called the battle "Manassas Junction". The wikipedia article https://en.wikipedia.org/wiki/First_Battle_of_Bull_Run says the Confederate name was "First Manassas" (I might be misremembering exactly what this book I read as a child said). Also I'm pretty sure it was specifically "Encyclopedia Brown Solves Them All" that this mystery appeared in. If someone has a copy of the book or cares to dig it up, they could confirm my memory. | |
| ▲ | michaericalribo 14 hours ago | parent | prev [-] | | Can confirm, it was an Encyclopedia Brown book and it was World War One vs the Great War that gave away the sword as a counterfeit! |
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| ▲ | wat10000 11 hours ago | parent | prev | next [-] | | It wouldn’t be totally implausible to use that phrase between the wars. The name “the First World War” was used as early as 1920, although not very common. | |
| ▲ | BeefySwain 14 hours ago | parent | prev [-] | | Pendragon? |
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| ▲ | gaius_baltar 15 hours ago | parent | prev | next [-] | | > "...what do you mean, 'World War One?'" Oh sorry, spoilers. (Hell, I miss Capaldi) | |
| ▲ | inferiorhuman 15 hours ago | parent | prev [-] | | … what do you mean, an internet where everything wasn't hidden behind anti-bot captchas? |
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| ▲ | Sieyk 11 hours ago | parent | prev | next [-] |
| I was going to say the same thing. Its really hard to explain the concept of "convincing but undoubtedly pretending", yet they captured that concept so beautifully here. |
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| ▲ | Davidbrcz 8 hours ago | parent | prev | next [-] |
| That's some Westworld level of discussion |
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| ▲ | rcpt 11 hours ago | parent | prev [-] |
| Watching a modern LLM chat with this would be fun. |