5 ms·
LLMs are still next token predictors, just because you can give it more vague instructions and it still finds the right steps to follow, it doesn't mean it's in
by moezd 3mo ago
LLMs are still next token predictors, just because you can give it more vague instructions and it still finds the right steps to follow, it doesn't mean it's intelligent. It means you're speaking the same language as the harness they trained your model on.
And that has a limit. If you are stuck at PoC level or simple apps, you have no idea how limited the current models still are. There you really need to break tasks down, not just trust a token predictor to list steps that sound good. There has to be a human in the loop somewhere, because by the time you start skipping permissions, best case you get the jackpot, more likely is you get a suboptimal solution and token waste and what's genuinely still terrifying when the model ignores instructions and does some stupid nonsense, ruining your day. It really is as sharp as a CNC machine. It's not not useful, but could be dangerous, so maybe don't try to carve wood with a monster machine, or park your Ferrari in that crammed neighbourhood if you don't know how to parallel park.
- semiquaver 3mo agoYeah, and you’re just a next-word-sayer.
- ofjcihen 3mo agoI love this argument. Not because it’s true but because it betrays the posters doubt in their own sentience.
- matheusmoreira 3mo agoIt's impossible for someone to doubt their own sentience. The literal act of doubting is enough to dissipate all doubt. Solipsism is essentially the one certainty that every mind out there has. Doubting the sentience of machines and even other humans is perfectly fine though. Only empathy allows people to make the leap and assume other humans have souls.
- rexarex 3mo agoSo you posit that humans are solipsistic by default, but some (most?) develop more and realize they’re not the only conscious being out there?
- matheusmoreira 3mo ago"Realize" is too strong a word. You're the only one who can verify that you're the soul who's staring out at the world through your eyes. For all you know, everyone else could be just biological automatons, golems. Any leap beyond that is based on empathy. You have a soul, and you are human, therefore other humans could have souls too. It's a spiritual belief. Answers to questions that cannot be answered.
- marmarama 3mo agoThat's the standard Piagetian understanding of child development, yes. Humans do not start out with theory of mind, and are thus inherently solipsistic, but in most cases an understanding that there are other conscious beings with their own thoughts, goals and feelings develops between the ages of 2 and 7. Developing theory of mind is one of the key milestones in child development.
- deleted 3mo ago[deleted]
- teravor 3mo ago> It's impossible for someone to doubt their own sentience. The literal act of doubting is enough to dissipate all doubt. i never found this convincing. just because you can loop does not mean you are sentient/conscious. what would it look like if you didn't exist and there was just a system that interrogated neural inputs and produced neural outputs in a loop? if anything, LLM's as an existence proof made this more likely to be the actual case.
- Zecc 3mo ago> Solipsism is essentially the one certainty that every mind out there has. Not I. I'm just a Boltzmann brain.
- solumunus 3mo agoI’m not sure what sentience has to do with it.
- root_axis 3mo agoThis is wrong. Human thinking and speech isn't autoregressive like LLM inference.
- infinite_spin 3mo agowhile the how is different, the what has many parallels. E.g. both the brain and LLMs appear to learn distributions of representations, they both develop a hierarchy of those representations, both have early layers that process simple features, with later ones processing more abstract concepts, both predict missing information...
- root_axis 3mo agoThe post I responded to stated that the commenter was just a next-word-sayer, but that's wrong. The similarities you draw aren't really relevant to my reply.
- infinite_spin 3mo agono disrespect intended, however I think my response is relevant, because the broader topic here is whether LLMs and the human mind share similar functions. They both do in fact have a lot of overlapping features, and a fundamental one is predicting next-thing, be that a word, image, or otherwise.
- root_axis 3mo agoIt's not relevant. However, if you want to talk about a broader point, that's ok. > LLMs appear to learn distributions of representations, they both develop a hierarchy of those representations, both have early layers that process simple features, with later ones processing more abstract concepts, both predict missing information. This type of superficial comparison isn't very meaningful, it's trivial to liken anything to a human biology in this manner. A plane and a bird both use wings to produce lift, it doesn't then follow that a bird and a plane are meaningfully similar.
- moezd 3mo agoChinese whispers, simulacra... I don't have the energy to argue after being name called, but you get the point. Yes LLMs are useful in building automatic telling machines, but ask it to do anything more substantial and all you are doing is burning tokens at the altar of Anthropic and hope. That just doesn't fly in regulated industries.
- dofm 3mo agoI mean, conversationally, of course we work a little more like that (I tend to think in whole sentence blocks before I say them but I suppose they assemble themselves largely word-by-word, or word-by-word with a bit of editing). But right now I am trying to design something -— a physical mechanism with a particular enclosure — that I cannot clearly describe (this makes it hard to research). I designed a previous version without even knowing the words that do, in fact, describe that. I have a theory about it, animated in my mind, that I can only test by making it. If I want you to know about it, I can either show you it or work out words to describe it, which will be inadequate to describing it. The idea for it came from seeing things nobody has ever put into words for me. "Next-word sayer" doesn't describe any of this process, does it? (This is also why text-to-CAD is a bullshit idea)
- infinite_spin 3mo ago> it doesn't mean it's intelligent I'm not sure how you're defining "intelligent", but I'd like to know how it is able to exclude a language model, while still including humans, without simply defining it with an axiom that predefines LLMs as lacking intelligence.
- bbqbbqbbq 3mo ago[dead]
- Cycl0ps 3mo agoAn LLM has a fixed number of ways it can express itself. we can give it an array of 14 billion options but it still has to chose one to output. Humans have no such limitation. An LLM does not persist in consciousness from one token to the next. Each generation, happening hundreds of times a second, will be initialized, generate an output, and terminate. Humans are not stateless like an LLM.
- infinite_spin 3mo agoYou're conflating a singular model with a much larger system, but I want to address some of your points anyway. > An LLM has a fixed number of ways it can express itself While deterministic, there is not a fixed number of ways it can express itself, given that we can use settings like temperature to inject randomness into the output. > An LLM does not persist in consciousness from one token to the next While a model alone does not update itself to persist some form of history, there are a number of ways to overcome this, e.g. episodic memory, fine-tuning, and other self-improvement systems exist, which can indeed carry forward what you've called "consciousness". > Humans are not stateless like an LLM. A single LLM might be stateless, but an agentic system that relies on LLMs is very often not.
- delusional 3mo ago> While deterministic, there is not a fixed number of ways it can express itself, given that we can use settings like temperature to inject randomness into the output. You're missing the point, which is that no matter the process involved. The LLM can only ever output one of the tokens in its token vector. It can't invent a new symbol or character. It can't leave and go build a church. It has to output a little piece of data for you.
- ACCount37 3mo ago"Next token prediction" is an interface, not an algorithm. A process that "predicts next tokens" can be arbitrarily complex or simple, and arbitrarily capable or incapable of performing a given task. Saying that an LLM can or can't do something because it's a "token predictor" is a category error. The interface isn't a hard limit.
- IsTom 3mo agoI'm not sure if it's has any real bearing on real-world performance, but technically next token prediction makes it an online algorithm and they can be provably worse than (good) offline algorithms.
- dncornholio 3mo agoThe word "prediction" still holds a lot of weight. LLM's only can predict what has been written. This is a hard limit.
- ACCount37 3mo agoFor something like "a hard limit" to hold, LLMs must be restricted to only reproducing existing text. This is utterly false even for base models - their basin seems to be "permutations loosely inspired by existing text". And that's before all the post-training comes in. What's the "limit" there?
- MoltenMan 3mo agoCalling LLMs 'next token predictors' is completely reductive and disingenuous; it's true that technically that is what they're doing, but so are you! What people generally mean by this though is that they're just 'predicting the next token of their training [i.e. the internet]'. If you were talking about the raw models, this would actually be true; but the models are post trained, so even this description isn't true at all anymore! Saying they aren't 'intelligent' is both not useful and (imo) wrong. Who cares if it matches your definition of 'intelligent'; it still gets impressive stuff done, much more impressive stuff than you seem to be implying.
- joenot443 3mo agoWhat would you say is your benchmark for calling something intelligent?
- solumunus 3mo agoCan it solve problems.