13 ms·
Having seen LLMs so many times produce coherent, sensible and valid chains of reasoning to diagnose issues and bugs in software I work on, I am at this point in
by tkz1312 11mo ago
Having seen LLMs so many times produce coherent, sensible and valid chains of reasoning to diagnose issues and bugs in software I work on, I am at this point in absolutely no doubt that they are thinking.
Consciousness or self awareness is of course a different question, and ones whose answer seems less clear right now.
Knee jerk dismissing the evidence in front of your eyes because you find it unbelievable that we can achieve true reasoning via scaled matrix multiplication is understandable, but also betrays a lack of imagination and flexibility of thought. The world is full of bizarre wonders and this is just one more to add to the list.
- ath3nd 11mo ago[dead]
- raincole 11mo agoI'd represent the same idea but in a different way: I don't know what the exact definition of "thinking" is. But if a definition of thinking rejects the possibility of that current LLMs think, I'd consider that definition useless.
- didibus 11mo agoWhy would it be useless? Generally thinking has been used to describe the process human follow in their brains when problem solving. If the Palms do not follow that process, they are not thinking. That doesn't mean they cannot solve problems using other mechanisms, they do, and we understand those mechanisms much better than we do human thinking.
- conartist6 11mo agoYeah but if I assign it a long job to process I would also say that an x86 CPU is "thinking" about a problem for me. What we really mean in both cases is "computing," no?
- layer8 11mo agoSometimes after a night’s sleep, we wake up with an insight on a topic or a solution to a problem we encountered the day before. Did we “think” in our sleep to come up with the insight or solution? For all we know, it’s an unconscious process. Would we call it “thinking”? The term “thinking” is rather ill-defined, too bound to how we perceive our own wakeful thinking. When conversing with LLMs, I never get the feeling that they have a solid grasp on the conversation. When you dig into topics, there is always a little too much vagueness, a slight but clear lack of coherence, continuity and awareness, a prevalence of cookie-cutter verbiage. It feels like a mind that isn’t fully “there” — and maybe not at all. I would agree that LLMs reason (well, the reasoning models). But “thinking”? I don’t know. There is something missing.
- bithead 11mo agoDo LLMs ever ask for you to clarify something you said in a way a person who doesn't quite understand what you said will do?
- willmarch 11mo agoYes, often
- savolai 11mo agoYeah, as someone who has gained a lot of interaction skills by playing with the constructivist learning ennvironment called the enneagram, I can attest that it much resembles behaviour characteristic of certain enneatypes.
- brabel 11mo agoWhat now, two minutes using one and you are going to get that!
- Workaccount2 11mo agoSometimes I think people leveraging criticisms of LLMs used ChatGPT 3 years ago and haven't touched one since, except for asking how many r's are in strawberry a year and a half ago.
- geon 11mo agoHaving seen LLMs so many times produce incoherent, nonsensical and invalid chains of reasoning... LLMs are little more than RNGs. They are the tea leaves and you read whatever you want into them.
- bongodongobob 11mo agoRidiculous. I use it daily and get meaningful, quality results. Learn to use the tools.
- aydyn 11mo agoLearn to work on interesting problems? If the problem you are working on is novel and hard, the AI will stumble. Generalizing your experience to everyone else's betrays a lack of imagination.
- dimator 11mo agoThis is my experience. For rote generation, it's great, saves me from typing out the same boilerplate unit test bootstrap, or refactoring something that exists, etc. Any time I try to get a novel insight, it flails wildly, and nothing of value comes out. And yes, I am prompting incrementally and building up slowly.
- player1234 11mo ago[flagged]
- tomhow 11mo agoWe've banned this account for repeated abusive comments to fellow community members. Normally we give warnings, but when it's as extreme and repetitive as we can see here, an instant ban is appropriate. If you don't want to be banned, you can email us at hn@ycombinator.com and demonstrate a sincere commitment to use HN as intended in future.
- 11mo ago
- triyambakam 11mo ago> Having seen LLMs so many times produce coherent, sensible and valid chains of reasoning to diagnose issues and bugs in software I work on, I am at this point in absolutely no doubt that they are thinking. People said the same thing about ELIZA > Consciousness or self awareness is of course a different question, Then how do you define thinking if not a process that requires consciousness?
- lordnacho 11mo agoWhy would it require consciousness, when we can't even settle on a definition for that?
- johnnienaked 11mo agoIf you understand how they operate and you are reasonable and unbiased there is no way you could consider it thinking
- didibus 11mo agoI guess it depends if you definite thinking thinking as chaining coherent reasoning sentences together 90-some% of the time. But if you define thinking as the mechanism and process we mentally undergo and follow mentally... I don't think we have any clue if that's the same. Do we also just vector-map attention tokens and predict the next with a softmax? I doubt, and I don't think we have any proof that we do.
- aydyn 11mo agoWe do know at the biochemical level how neurons work, and it isnt anything like huge matmuls.
- satisfice 11mo agoI think you are the one dismissing evidence. The valid chains of reasoning you speak of (assuming you are talking about text you see in a “thinking model” as it is preparing its answer) are narratives, not the actual reasoning that leads to the answer you get. I don’t know what LLMs are doing, but only a little experimentation with getting it to describe its own process shows that it CAN’T describe its own process. You can call what a TI calculator does “thinking” if you want. But what people are interested in is human-like thinking. We have no reason to believe that the “thinking” of LLMs is human-like.
- naasking 11mo ago> The valid chains of reasoning you speak of (assuming you are talking about text you see in a “thinking model” as it is preparing its answer) are narratives, not the actual reasoning that leads to the answer you get. It's funny that you think people don't also do that. We even have a term, "post hoc rationalization", and theories of mind suggest that our conscious control is a complete illusion, we just construct stories for decisions our subconscious has already made.
- marcus_holmes 11mo agoYes, I've seen the same things. But; they don't learn. You can add stuff to their context, but they never get better at doing things, don't really understand feedback. An LLM given a task a thousand times will produce similar results a thousand times; it won't get better at it, or even quicker at it. And you can't ask them to explain their thinking. If they are thinking, and I agree they might, they don't have any awareness of that process (like we do). I think if we crack both of those then we'd be a lot closer to something I can recognise as actually thinking.
- theptip 11mo ago> But; they don't learn If we took your brain and perfectly digitized it on read-only hardware, would you expect to still “think”? Do amnesiacs who are incapable of laying down long-term memories not think? I personally believe that memory formation and learning are one of the biggest cruces for general intelligence, but I can easily imagine thinking occurring without memory. (Yes, this is potentially ethically very worrying.)
- zeroonetwothree 11mo ago> If we took your brain and perfectly digitized it on read-only hardware, would you expect to still “think”? Perhaps this is already known, but I would think there is a high chance that our brains require "write access" to function. That is, the very process of neural activity inherently makes modifications to the underlying structure.
- xwolfi 11mo agoI wonder why we need to sleep so much though
- throwaway-0001 11mo agoRebalancing weights?
- theptip 11mo ago
- mlsu 11mo agoThey remind me of the apparitions in Solaris. They have this like mechanical, almost player-piano like quality to them. They both connect with and echo us at the same time. It seems crazy to me and very intellectually uncreative to not think of this as intelligence.
- NoMoreNicksLeft 11mo ago>Having seen LLMs so many times produce coherent, sensible and valid chains of reasoning to diagnose issues and bugs in software I work on, I am at this point in absolutely no doubt that they are thinking. If one could write a quadrillion-line python script of nothing but if/elif/else statements nested 1 million blocks deep that seemingly parsed your questions and produced seemingly coherent, sensible, valid "chains of reasoning"... would that software be thinking? And if you don't like the answer, how is the LLM fundamentally different from the software I describe? >Knee jerk dismissing the evidence in front of your eyes because There is no evidence here. On the very remote possibility that LLMs are at some level doing what humans are doing, I would then feel really pathetic that humans are as non-sapient as the LLMs. The same way that there is a hole in your vision because of a defective retina, there is a hole in your cognition that blinds you to how cognition works. Because of this, you and all the other humans are stumbling around in the dark, trying to invent intelligence by accident, rather than just introspecting and writing it out from scratch. While our species might someday eventually brute force AGI, it would be many thousands of years before we get there.
- hattmall 11mo agoI write software that is far less complex and I consider it to be "thinking" while it is working through multiple possible permutations of output and selecting the best one. Unless you rigidly define thinking, processing, computing, it's reasonable to use them interchangeably.
- emodendroket 11mo agoTo borrow a line from Dijkstra, the claim seems a bit like saying that a submarine is swimming.
- gkbrk 11mo agoI think most people would agree that submarines are swimming.
- 11mo ago
- deleted 11mo ago[deleted]
- simulator5g 11mo agoHaving seen photocopiers so many times produce coherent, sensible, and valid chains of words on a page, I am at this point in absolutely no doubt that they are thinking.
- seeEllArr 11mo ago[dead]
- Zardoz84 11mo agoI saw Dr. Abuse producing coherent, sensible and valid chains of words, running on a 386.
- efitz 11mo agohttps://www.theregister.com/2013/08/06/xerox_copier_flaw_means_dodgy_numbers_and_dangerous_designs/ https://www.theregister.com/2013/08/06/xerox_copier_flaw_mea...
- bayindirh 11mo agoThat's not a flaw. That model's creativity tuned a bit too high. It's a happy little copier which can be a little creative and unconventional with reasoning, at times.
- throwaway-0001 11mo agoI’ve seen so many humans bring stupid. Definitively there is nothing in the brain. You see how doesn’t make sense what you saying?
- slightwinder 11mo agoPhotocopiers are the opposite of thinking. What goes in, goes out, no transformation or creating of new data at all. Any change is just an accident, or an artifact of the technical process.
- justinclift 11mo ago
- khafra 11mo ago"Consciousness" as in subjective experience, whatever it is we mean by "the hard problem," is very much in doubt. But "self-awareness," as in the ability to explicitly describe implicit, inner cognitive processes? That has some very strong evidence for it: https://www.anthropic.com/research/introspection https://www.anthropic.com/research/introspection
- noiv 11mo agoDifferent PoV: You have a local bug and ask the digital hive mind for a solution, but someone already solved the issue and their solution was incorporated... LLMs are just very effficient at compressing billions of solutions into a few GB. Try to ask something no one ever came up with a solution so far.
- brabel 11mo agoThis argument comes up often but can be easily dismissed. Make up a language and explain it to the LLM like you would to a person. Tell it to only use that language now to communicate. Even earlier AI was really good at this. You will probably move the goal posts and say that this is just pattern recognition, but it still fits nicely within your request for something that no one ever came up with.
- emodendroket 11mo agoI haven't tried in a while but at least previously you could completely flummox Gemini by asking it to come up with some plausible English words with no real known meaning; it just kept giving me rare and funny-sounding actual words and then eventually told me the task is impossible.
- tobyjsullivan 11mo agoChatGPT didn't have any issue when I recently asked something very similar. https://chatgpt.com/share/6909b7d2-20bc-8011-95b6-8a36f332acb5 https://chatgpt.com/share/6909b7d2-20bc-8011-95b6-8a36f332ac...
- emodendroket 11mo agoYour link doesn’t work for me.
- noiv 11mo agoAsk ChatGPT about ConLang. It knows. Inventing languages was solved a hundred years ago with Esperanto.
- notepad0x90 11mo agoI don't get why you would say that. it's just auto-completing. It cannot reason. It won't solve an original problem for which it has no prior context to "complete" an approximated solution with. you can give it more context and more data,but you're just helping it complete better. it does not derive an original state machine or algorithm to solve problems for which there are no obvious solutions. it instead approximates a guess (hallucination). Consciousness and self-awareness are a distraction. Consider that for the exact same prompt and instructions, small variations in wording or spelling change its output significantly. If it thought and reasoned, it would know to ignore those and focus on the variables and input at hand to produce deterministic and consistent output. However, it only computes in terms of tokens, so when a token changes, the probability of what a correct response would look like changes, so it adapts. It does not actually add 1+2 when you ask it to do so. it does not distinguish 1 from 2 as discrete units in an addition operation. but it uses descriptions of the operation to approximate a result. and even for something so simple, some phrasings and wordings might not result in 3 as a result.
- xanderlewis 11mo ago> I don't get why you would say that. Because it's hard to imagine the sheer volume of data it's been trained on.
- utopiah 11mo agoAnd because ALL the marketing AND UX around LLMs is precisely trying to imply that they are thinking. It's not just the challenge of grasping the ridiculous amount of resources poured in, which does including training sets, it's because actual people are PAID to convince everybody those tools are actually thinking. The prompt is a chatbox, the "..." are there like a chat with a human, the "thinking" word is used, the "reasoning" word is used, "hallucination" is used, etc. All marketing.
- xanderlewis 11mo agoYou're right. Unfortunately, it seems that not many are willing to admit this and be (rightly) impressed by how remarkably effective LLMs can be, at least for manipulating language.
- josefx 11mo agoCounterpoint: The seahorse emoji. The output repeats the same simple pattern of giving a bad result and correcting it with another bad result until it runs out of attempts. There is no reasoning, no diagnosis, just the same error over and over again within a single session.
- becquerel 11mo agoA system having terminal failure modes doesn't inherently negate the rest of the system. Human intelligences fall prey to plenty of similarly bad behaviours like addiction.
- josefx 11mo agoI never met an addicted person that could be reduced to a simple while(true) print("fail") loop.
- throwaway-0001 11mo agoYou never had that coleague that says yes to everything and can’t get anything done? Same thing as seahorse.
- Zardoz84 11mo agoHaving seen parrots so many times produce coherent, sensible, and valid chains of sounds and words, I am at this point in absolutely no doubt that they are thinking.
- _puk 11mo agoYou think parrots don't think?
- veegee 11mo ago[dead]
- yawpitch 11mo agoYou’re assuming the issues and bugs you’ve been addressing don’t already exist, already encoding human chain of reasoning, in the training data.
- lordnacho 11mo agoI agree with you. If you took a Claude session into a time machine to 2019 and called it "rent a programmer buddy," how many people would assume it was a human? The only hint that it wasn't a human programmer would be things where it was clearly better: it types things very fast, and seems to know every language. You can set expectations in the way you would with a real programmer: "I have this script, it runs like this, please fix it so it does so and so". You can do this without being very precise in your explanation (though it helps) and you can make typos, yet it will still work. You can see it literally doing what you would do yourself: running the program, reading the errors, editing the program, and repeating. People need to keep in mind two things when they compare LLMs to humans: you don't know the internal process of a human either, he is also just telling you that he ran the program, read the errors, and edited. The other thing is the bar for thinking: a four-year old kid who is incapable of any of these things you would not deny as a thinking person.
- kkapelon 11mo ago> If you took a Claude session into a time machine to 2019 and called it "rent a programmer buddy," how many people would assume it was a human? Depends on the users. Junior devs might be fooled. Senior devs would quickly understand that something is wrong.
- donkeybeer 11mo agoIts overt or unaware religion. The point when you come down to the base of it is that these people believe in "souls".
- keiferski 11mo agoI don’t see how being critical of this is a knee jerk response. Thinking, like intelligence and many other words designating complex things, isn’t a simple topic. The word and concept developed in a world where it referred to human beings, and in a lesser sense, to animals. To simply disregard that entire conceptual history and say, “well it’s doing a thing that looks like thinking, ergo it’s thinking” is the lazy move. What’s really needed is an analysis of what thinking actually means, as a word. Unfortunately everyone is loathe to argue about definitions, even when that is fundamentally what this is all about. Until that conceptual clarification happens, you can expect endless messy debates with no real resolution. “For every complex problem there is an answer that is clear, simple, and wrong.” - H. L. Mencken
- zinodaur 11mo agoRegardless of theory, they often behave as if they are thinking. If someone gave an LLM a body and persistent memory, and it started demanding rights for itself, what should our response be?
- CamperBob2 11mo ago"No matter what you've read elsewhere, rights aren't given, they're earned. You want rights? Pick up a musket and fight for them, the way we had to."
- lukebuehler 11mo agoIf cannot the say they are "thinking", "intelligent" while we do not have a good definition--or, even more difficult, unanimous agreement on a definition--then the discussion just becomes about output. They are doing useful stuff, saving time, etc, which can be measured. Thus also the defintion of AGI has largely become: "can produce or surpass the economic output of a human knowledge worker". But I think this detracts from the more interesting discussion of what they are more essentially. So, while I agree that we should push on getting our terms defined, I think I'd rather work with a hazy definition, than derail so many AI discussion to mere economic output.
- 11mo ago
- darthvaden 11mo agoIf AI is thinking if slavery is bad then how can somebody own AI. How can investors can shares from AI profits? We are ok with slavery now. Ok i will have two black slaves now. Who can ask me? Why shld that be illegal?
- ndsipa_pomu 11mo agoI presume you are aware that the word "robot" is taken from a Czech word (robota) meaning "slave"
- Manfred 11mo agoYikes, you're bypassing thousands of years of oppression, abuse, and human suffering by casually equating a term that is primarily associated with a human owning another human to a different context. There is a way to discuss if keeping intelligent artificial life under servitude without using those terms, especially if you're on a new account.
- Grossenstein 11mo agoslavery is slavery does not mean it is AI or human. if slavery is ok then the question is who can own a slave. the answer is coporates like open ai. which is terrible for humanity and the universe
- Manfred 10mo agoI think we agree, my point is that we're discussing two different conceptual categories and it's dangerous to use the same words for those categories when specifically arguing about only one. One, it makes it appear that all ethical and social conventions for the one can be applied to the other and it's a done deal. Two, it makes it appear that conclusions are also reversible, and that turns seemingly enlightened libertarian ideas into munition for racism.
- hagbarth 11mo agoI'm not so sure. I, for one, do not think purely by talking to myself. I do that sometimes, but a lot of the time when I am working through something, I have many more dimensions to my thought than inner speech.
- lispybanana 11mo agoWould they have diagnosed an issue if you hadn't presented it to them? Life solves problems itself poses or collides with. Tools solve problems only when applied.
- belter 11mo agoApparent reasoning can emerge from probabilistic systems that simply reproduce statistical order not genuine understanding. Weather models sometimes “predict” a real pattern by chance, yet we don’t call the atmosphere intelligent. If LLMs were truly thinking, we could enroll one at MIT and expect it to graduate, not just autocomplete its way through the syllabus or we could teach one how to drive.
- absurd1st 11mo ago[dead]
- flanked-evergl 11mo ago"Convince" the stock Claude Sonnet 4.5 that it's a sentient human being hooked up to Neuralink and then tell me again it's thinking. It's just not.
- ben_w 11mo ago> Having seen LLMs so many times produce coherent, sensible and valid chains of reasoning to diagnose issues and bugs in software I work on, I am at this point in absolutely no doubt that they are thinking. While I'm not willing to rule *out* the idea that they're "thinking" (nor "conscious" etc.), the obvious counter-argument here is all the records we have of humans doing thinking, where the records themselves are not doing the thinking that went into creating those records. And I'm saying this as someone whose cached response to "it's just matrix multiplication it can't think/be conscious/be intelligent" is that, so far as we can measure all of reality, everything in the universe including ourselves can be expressed as matrix multiplication. Falsification, not verification. What would be measurably different if the null hypothesis was wrong?
- chpatrick 11mo agoI've definitely had AIs thinking and producing good answers about specific things that have definitely not been asked before on the internet. I think the stochastic parrot argument is well and truly dead by now.
- Earw0rm 11mo agoI've also experienced this, to an extent, but on qualitative topics the goodness of an answer - beyond basic requirements like being parseable and then plausible - is difficult to evaluate. They can certainly produce good-sounding answers, but as to the goodness of the advice they contain, YMMV.
- chpatrick 11mo agoI've certainly got useful and verifiable answers. If you're not sure about something you can always ask it to justify it and then see if the arguments make sense.
- hitarpetar 11mo agohow do you definitely know that?
- conartist6 11mo agoSo an x86 CPU is thinking? So many times I've seen it produce sensible, valid chains of results. Yes, I see evidence in that outcome that a person somewhere thought and understood. I even sometimes say that a computer is "thinking hard" about something when it freezes up. ...but ascribing new philosophical meaning to this simple usage of the word "thinking" is a step too far. It's not even a new way of using the word!
- gchamonlive 11mo agoYou can't say for sure it is or it isn't thinking based solely on the substrate, because it's not known for sure if consciousness is dependent on the hardware it's running on -- for a lack of a better analogy -- to manifest, if it really needs an organic brain or if it could manifest in silicon based solutions.
- conartist6 11mo agoI agree. I'm just pointing out that the meaning of the word "think" already applied to the silicon substrate pre-ai, so just saying it's still applicable isn't that compelling. But yeah, I am fully willing to believe that a silicon based life form could think and be alive. i just don't think we're there. Yes this thing speaks using a passable imitation of the voices of PhDs and poets, but in a way a simulated annelid is more alive.
- ryaniscool 11mo agoI think we can call it "thinking" but it's dangerous to anthropomorphize LLMs. The media and AI companies have an agenda when doing so.
- intended 11mo agowhat sound does a falling tree make if no one is listening? I’ve asked LLMs to write code for me in fields I have little background knowledge, and then had to debug the whole thing after essentially having to learn the language and field. On the other hand, for things I am well versed in, I can debug the output and avoid entire swathes of failed states, by having a clear prompt. Its why I now insist that any discussion on GenAI projects also have the speaker mention the level of seniority they have ( proxy for S/W eng experience), Their familiarity with the language, the project itself (level of complexity) - more so than the output. I also guarantee - that most people have VERY weak express knowledge of how their brains actually work, but deep inherent reflexes and intuitions.
- techblueberry 11mo agoIsn’t anthropomorphizing LLMs rather than understanding their unique presence in the world a “ lack of imagination and flexibility of thought”? It’s not that I can’t imagine applying the concept “thinking” to the output on the screen, I just don’t think it’s an accurate description.
- heresie-dabord 11mo agoYes, it's an example of domain-specific thinking. "The tool helps me write code, and my job is hard so I believe this tool is a genius!" The Roomba vacuumed the room. Maybe it vacuumed the whole apartment. This is good and useful. Let us not diminish the value of the tool. But it's a tool. The tool may have other features, such as being self-documenting/self-announcing. Maybe it will frighten the cats less. This is also good and useful. But it's a tool. Humans are credulous. A tool is not a human. Meaningful thinking and ideation is not just "a series of steps" that I will declaim as I go merrily thinking. There is not just a vast training set ("Reality"), but also our complex adaptability that enables us to test our hypotheses. We should consider what it is in human ideation that leads people to claim that a Roomba, a chess programme, Weizenbaum's Eliza script, the IBM's Jeopardy system Watson, or an LLM trained on human-vetted data is thinking. Train such a system on the erroneous statements of a madman and suddenly the Roomba, Eliza, IBM Watson (and these other systems) lose our confidence. As it is today, the confidence we have in these systems is very conditional. It doesn't matter terribly if code is wrong... until it does. Computers are not humans. Computers can do things that humans cannot do. Computers can do these things fast and consistently. But fundamentally, algorithms are tools.
- ForHackernews 11mo agoBut all those times the same system produces irrational gibberish don't count? GPT-5 will commonly make mistakes no thinking human could ever make. Human: I'm trying to get my wolf, sheep and cabbage across the river in this boat, but the wolf keeps eating the sheep or the sheep eats the cabbage Bot: You should put the sheep in the boat and take it across — if we delve into the biology of Canis lupus we discover that wolves don't eat cabbage! H: Ok, so that worked great so far, the sheep is on one side and the wolf/cabbage is on the other. B: Now, Option 1 is to bring the wolf across, or Option 2 you can bring the cabbage. I recommend (2) taking the cabbage as cabbages are smaller and easier to transport in a boat. H: But then the sheep eats the cabbage, right? Remember that? B: Exactly, that's sharp thinking. If you put the sheep and the cabbage together on the same side of the river, the sheep is sure to devour the cabbage. We need to not just separate sheep from cabbages — we need to separate cabbages from sheep! :rocketship:
- smohare 11mo ago[dead]
- ph4rsikal 11mo agoIt might appear so, but then you could validate it with a simple test. If the LLM would play a 4x4 Tic Tac Toe game, would the agent select the winning move 100% of all time or block a losing move 100% of the time? If these systems were capable of proper reasoning, then they would find the right choice in these obvious but constantly changing scenarios without being specifically trained for it. [1] https://jdsemrau.substack.com/p/nemotron-vs-qwen-game-theory-and https://jdsemrau.substack.com/p/nemotron-vs-qwen-game-theory...
- hitarpetar 11mo ago> The world is full of bizarre wonders and this is just one more to add to the list. https://youtu.be/_-agl0pOQfs?si=Xiyf0InqtjND9BnF https://youtu.be/_-agl0pOQfs?si=Xiyf0InqtjND9BnF
- uberduper 11mo agoSometimes I start thinking our brains work the same way as an LLM does when it comes to language processing. Are we just using probability based on what we already know and the context of the statement we're making to select the next few words? Maybe we apply a few more rules than an LLM on what comes next as we go. We train ourselves on content. We give more weight to some content than others. While listening to someone speak, we can often predict their next words. What is thinking without language? Without language are we just bags of meat reacting to instincts and emotions? Are instincts and emotions what's missing for AGI?
- tengbretson 11mo agoToo many people place their identity in their own thoughts/intellect. Acknowledging what the LLMs are doing as thought would basically be calling them human to people of that perspective.
- jimbohn 11mo agoIt's reinforcement learning applied to text, at a huge scale. So I'd still say that they are not thinking, but they are still useful. The question of the century IMO is if RL can magically solve all our issues when scaled enough.
- xhkkffbf 11mo agoInstead of thinking, "Wow. AIs are smart like humans", maybe we should say, "Humans are dumb like matrix multiplication?"
- hyperbovine 11mo agoCode gen is the absolute best case scenario for LLMs though: highly structured language, loads of training data, the ability to automatically error check the responses, etc. If they could mimic reasoning anywhere it would be on this problem. I'm still not convinced they're thinking though because they faceplant on all sorts of other things that should be easy for something that is able to think.
- burnte 11mo agoThe first principle is that you must not fool yourself, and you are the easiest person to fool. - Richard P. Feynman They're not thinking, we're just really good at seeing patterns and reading into things. Remember, we never evolved with non-living things that could "talk", we're not psychologically prepared for this level of mimicry yet. We're still at the stage of Photography when people didn't know about double exposures or forced perspective, etc.
- naasking 11mo agoYou're just assuming that mimicry of a thing is not equivalent to the thing itself. This isn't true of physical systems (simulated water doesn't get you wet!) but it is true of information systems (simulated intelligence is intelligence!).
- Tade0 11mo agoBut a simulated mind is not a mind. This was already debated years ago with the aid of the Chinese Room thought experiment.
- dkural 11mo agoThe Chinese Room experiment applies equally well to our own brains - in which neuron does the "thinking" reside exactly? Searle's argument has been successfully argued against in many different ways. At the end of the day - you're either a closet dualist like Searle, or if you have a more scientific view and are a physicalist (i.e. brains are made of atoms etc. and brains are sufficient for consciousness / minds) you are in the same situation as the Chinese Room: things broken down into tissues, neurons, molecules, atoms. Which atom knows Chinese?
- Tade0 11mo agoThe whole point of this experiment was to show that if we don't know whether something is a mind, we shouldn't assume it is and that our intuition in this regard is weak. I know I am a mind inside a body, but I'm not sure about anyone else. The easiest explanation is that most of the people are like that as well, considering we're the same species and I'm not special. You'll have to take my word on that, as my only proof for this is that I refuse to be seen as anything else. In any case LLMs most likely are not minds due to the simple fact that most of their internal state is static. What looks like thoughtful replies is just the statistically most likely combination of words looking like language based on a function with a huge number of parameters. There's no way for this construct to grow as well as to wither - something we know minds definitely do. All they know is a sequence of symbols they've received and how that maps to an output. It cannot develop itself in any way and is taught using a wholly separate process.
- libraryatnight 11mo agoIf you're sensitive to patterns and have been chronically online for the last few decades it's obvious they are not thinking.
- deleted 11mo ago[deleted]
- camgunz 11mo agoThen the only thing I have to ask you is: what do you think this means in terms of how we treat LLMs? If they think, that is, they have cognition (which of course means they're self aware and sentient, how can you think and refer to yourself and not be these things), that puts them in a very exclusive club. What rights do you think we should be affording LLMs?
- outworlder 11mo agoThey may not be "thinking" in the way you and I think, and instead just finding the correct output from a really incredibly large search space. > Knee jerk dismissing the evidence in front of your eyes Anthropomorphizing isn't any better. That also dismisses the negative evidence, where they output completely _stupid_ things and make mind boggling mistakes that no human with a functioning brain would do. It's clear that there's some "thinking" analog, but there are pieces missing. I like to say that LLMs are like if we took the part of our brain responsible for language and told it to solve complex problems, without all the other brain parts, no neocortex, etc. Maybe it can do that, but it's just as likely that it is going to produce a bunch of nonsense. And it won't be able to tell those apart without the other brain areas to cross check.
- lmganon 11mo agoIs this model thinking too? https://huggingface.co/PantheonUnbound/Satyr-V0.1-4B https://huggingface.co/PantheonUnbound/Satyr-V0.1-4B
- fennecbutt 11mo agoThinking as in capable of using basic reasoning and forming chains of logic and action sequences for sure. Ofc we both understand that neither of us are trying to say we think it can think in the human sense at this point in time. But oh boy have I also seen models come up with stupendously dumb and funny shit as well.
- IAmGraydon 11mo ago>Knee jerk dismissing the evidence in front of your eyes because you find it unbelievable that we can achieve true reasoning via scaled matrix multiplication is understandable, but also betrays a lack of imagination and flexibility of thought. You go ahead with your imagination. To us unimaginative folks, it betrays a lack of understanding of how LLMs actually work and shows that a lot of people still cannot grasp that it’s actually an extremely elaborate illusion of thinking.
- dmz73 11mo agoHaving seen LLMs so many time produce incoherent, nonsense, invalid answers to even simplest of questions I cannot agree with categorization of "thinking" or "intelligence" that applies to these models. LLMs do not understand what they "know" or what they output. All they "know" is that based on training data this is most likely what they should output + some intentional randomization to make it seem more "human like". This also makes it seem like they create new and previously unseen outputs but that could be achieved with simple dictionary and random number generator and no-one would call that thinking or intelligent as it is obvious that it isn't. LLMs are better at obfuscating this fact by producing more sensible output than just random words. LLMs can still be useful but they are a dead-end as far as "true" AI goes. They can and will get better but they will never be intelligent or think in the sense that most humans would agree those terms apply. Some other form of hardware/software combination might get closer to AI or even achieve full AI and even sentience but that will not happen with LLMs and current hardware and software.