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> something fundamental has changed that enables a computer to pretty effectively understand natural language. You understand how the tech works right? It's st
by gishh 10mo ago
> something fundamental has changed that enables a computer to pretty effectively understand natural language.
You understand how the tech works right? It's statistics and tokens. The computer understands nothing. Creating "understanding" would be a breakthrough.
Edit: I wasn't trying to be a jerk. I sincerely wasn't. I don't "understand" how LLMs "understand" anything. I'd be super pumped to learn that bit. I don't have an agenda.
- sukhdeepprashit 10mo ago[dead]
- danielvaughn 10mo agoI think it’s a disingenuous read to assume original commenter means “understanding” in the literal sense. When we talk about LLM “understanding”, we usually mean it from a practical sense. If you give an input to the computer, and it gives you an expected output, then colloquially the computer “understood” your input.
- pawelduda 10mo agoThe end effect certainly gives off "understanding" vibe. Even if method of achieving it is different. The commenter obviously didn't mean the way human brain understands
- frotaur 10mo agoIt astonishes me how people can make categorical judgements on things as hard to define as 'understanding'. I would say that, except for the observable and testable performance, what else can you say about understanding? It is a fact that LLMs are getting better at many tasks. From their performance, they seem to have an understanding of say python. The mechanistic way this understanding arises is different than humans. How can you say then it is 'not real', without invoking the hard problem of consciousness, at which point, we've hit a completely open question.
- deleted 10mo ago[deleted]
- phantasmish 10mo agoTo be fair, it can be hard to define “chair” to the satisfaction of an unsympathetic judge. “Do chairs exist?”: https://m.youtube.com/watch?v=fXW-QjBsruE https://m.youtube.com/watch?v=fXW-QjBsruE
- matthewkayin 10mo agoI think it is fair to say that AIs do not yet "understand" what they say or what we ask them. When I ask it to use a specific MCP to complete a certain task, and it proceeds to not use that MCP, this indicates a clear lack of understanding. You might say that the fault was mine, that I didn't setup or initialize the MCP tool properly, but wouldn't an understanding AI recognize that it didn't have access to the MCP and tell me that it cannot satisfy my request, rather than blindly carrying on without it? LLMs consistently prove that they lack the ability to evaluate statements for truth. They lack, as well, an awareness of their unknowing, because they are not trying to understand; their job is to generate (to hallucinate). It astonishes me that people can be so blind to this weakness of the tool. And when we raise concerns, people always say "How can you define what 'thinking' is?" "How can you define 'understanding'?" These philosophical questions are missing the point. When we say it doesn't "understand", we mean that it doesn't do what we ask. It isn't reliable. It isn't as useful to us as perhaps it has been to you.
- deleted 10mo ago[deleted]
- kunley 10mo agoHow do you know what kind of "understanding" a python has? Why python and not a lizard? Or a bird? What method do you use for evaluating this? Does a typical python do what you tell your ai agent to do?... C'mon, this comparison seems to be very, very unscientific. No offense...
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- ilikeatari 10mo agoWe could use a little more kindness in discussion. I think the commenter has a very solid understanding on how computer works. The “understanding” is somewhat complex but I do agree with you that we are not there yet. I do think that the paradigm shift though is more about the fact that now we can interact with the computer in a new way.
- neom 10mo agoBirds and planes operate using somewhat different mechanics, but they do both achieve flight.
- HPsquared 10mo agoBirds and planes are very similar other than the propulsion and landing gear, and construction materials. Maybe bird vs helicopter, or bird vs rocket.
- mejutoco 10mo ago> other than the propulsion and landing gear, and construction materials "Apart from the sanitation, the medicine, education, wine, public order, irrigation, roads, the fresh water system and public health, what have the Romans ever done for us?" Monty Python's Life of Brian. P.S. It is relative, but quite a lot of differences IMHO.
- HPsquared 10mo agoYes indeed, but they still use wings, fly in the air and so on. Artificial neural networks have very little in common with real brains and have no structural or functional similarities besides "they process information, and they have things called neurons". They can perform some of the same tasks though, like how a quadcopter can perform some of the duties as a homing pigeon.
- Uehreka 10mo ago“You understand how the brain works right? It’s neurons and electrical charges. The brain understands nothing.” I’m always struck by how confidently people assert stuff like this, as if the fact that we can easily comprehend the low-level structure somehow invalidates the reality of the higher-level structures. As if we know concretely that the human mind is something other than emergent complexity arising from simpler mechanics. I’m not necessarily saying these machines are “thinking”. I wish I could say for sure that they’re not, but that would be dishonest: I feel like they aren’t thinking, but I have no evidence to back that up, and I haven’t seen non-self-referential evidence from anyone else.
- claytongulick 10mo agoYou understand how reality works right? It's all just atoms clinging to each other. Simple. Heh.
- Lambdanaut 10mo agoYou understand how the brain works right? It's probability distributions mapped to sodium ion channels. The human understands nothing.
- 0xdeadbeefbabe 10mo agoI've heard that this human brain is rigged to find what it wants to find.
- aydyn 10mo agoThats how the brain works, not how the mind works. We understand the hardware, not the software.
- kipchak 10mo agoAre we even sure we understand the hardware? My understanding is even that is contested, for example orchestrated objective reduction, holonomic brain theory or GVF theory.
- claytongulick 10mo agoYou understand how the brain works? You're the one then. All those laggardly neurobiologists are still struggling.
- Eddy_Viscosity2 10mo agoIt could very well be that statistics and tokens is how our brains work at the computational level too. Just that our algorithms have slightly better heuristics due to all those millennia of A/B testing of our ancestors.
- emp17344 10mo agoExcept we know for a fact that the brain doesn’t work that way. You’re ignoring the entire history of neuroscience.
- Eddy_Viscosity2 10mo agoI didn't know that neuroscience even claimed to a full enough understanding of how people think to conclusively disprove this.
- emp17344 10mo agoCertainly not a full understanding, but there’s enough understanding to refute vague claims that we are somehow analogous to a text model.
- LatencyKills 10mo agoAs someone who was an engineer on the original Copilot team, yes I understand how tech works. You don’t know how your own mind “understands” something. No one on the planet can even describe how human understanding works. Yes, LLMs are vast statistical engines but that doesn’t mean something interesting isn’t going on. At this point I’d argue that humans “hallucinate” and/or provide wrong answers far more often than SOTA LLMs. I expect to see responses like yours on Reddit, not HN.
- gishh 10mo ago> I expect to see responses like yours on Reddit, not HN. I suppose that says something about both of us.
- szundi 10mo ago[dead]
- szundi 10mo ago[dead]
- 6510 10mo agoBefore one may begin to understand something one must first be able to estimate the level of certainty. Our robot friends, while really helpful and polite, seem to be lacking in that department. They actually think the things we've written on the internet, in books, academic papers, court documents, newspapers, etc are actually true. Where the humans aren't omniscient it fills the blanks with nonsense.
- LatencyKills 10mo ago> Where the humans aren't omniscient it fills the blanks with nonsense As do most humans. People lie. People make things up to look smart. People fervently believe things that are easily disproved. Some people are willfully ignorant, anti-science, anti-education, etc. The problem isn't the transformer architecture... it is the humans who advertise capabilities that are not there yet.
- goncharom 10mo agoEvery time I see comments like these I think about this research from anthropic: https://www.anthropic.com/research/mapping-mind-language-model https://www.anthropic.com/research/mapping-mind-language-mod... LLMs activate similar neurons for similar concepts not only across languages, but also across input types. I’d like to know if you’d consider that as a good representation of “understanding” and if not, how would you define it?
- gishh 10mo agoIf i could understand what the brain scans actually meant, I would consider it a good representation. I don't think we know yet what they mean. I saw some headline the other day about a person with "low brain activity" and said person was in complete denial about it, I would be too.
- goncharom 10mo agoAs I said then, and probably echoing what other commenters are saying - what do you mean by understanding when you say computers understand nothing? do humans understand anything? if so, how?
- gishh 10mo agoDoes a computer understand how hot or cold it is outside? Does it understand that your offspring might be cranky because they’re hungry? Or not hungry, just tired? Can it divine the difference? Does a computer know if your boss is mad at you or if they had a fight with their spouse last night, or whatever other reason they may be grumpy? Can a computer establish relationships… with anything? How about when a computer goes through puberty? Or menopause? Or a car accident? How do those things affect them? Don’t bother responding, I think you get the point.
- emp17344 10mo agoAnthropic is pretty notorious for peddling hype. This is a marketing article - it has not undergone peer-review and should not be mistaken for scientific research.
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- stanfordkid 10mo agoWhat do you mean by “understand”? Do you mean conscious? Understand just means “parse language” and is highly subjective. If I talk to someone African in Chinese they do not understand me but they are still conscious. If I talk to an LLM in Chinese it will understand me but that doesn’t mean it is conscious. If I talk about physics to a kindergartner they will not understand but that doesn’t mean they don’t understand anything. Do you see where I am going?
- observationist 10mo agoYou don't understand how the tech works, then. LLMs aren't as good as humans at understanding, but it's not just statistics. The stochastic parrot meme is wrong. The networks create symbolic representations in training, with huge multidimensional correlations between patterns in the data, whether its temporal or semantic. The models "understand" concepts like emotions, text, physics, arbitrary social rules and phenomena, and anything else present in the data and context in the same fundamental way that humans do it. We're just better, with representations a few orders of magnitude higher resolution, much wider redundancy, and multi-million node parallelism with asynchronous operation that silicon can't quite match yet. In some cases, AI is superhuman, and uses better constructs than humans are capable of, in other cases, it uses hacks and shortcuts in representations, mimics where it falls short, and in some cases fails entirely, and has a suite of failure modes that aren't anywhere in the human taxonomy of operation. LLMs and AI aren't identical to human cognition, but there's a hell of a lot of overlap, and the stochastic parrot "ItS jUsT sTaTiStIcS!11!!" meme should be regarded as an embarrassing opinion to hold. "Thinking" models that cycle context and systems of problem solving also don't do it the same way humans think, but overlap in some of the important pieces of how we operate. We are many orders of magnitude beyond old ALICE bots and MEgaHAL markov chains - you'd need computers the size of solar systems to run a markov chain equivalent to the effective equivalent 40B LLM, let alone one of the frontier models, and those performance gains are objectively within the domain of "intelligence." We're pushing the theory and practice of AI and ML squarely into the domain of architectures and behaviors that qualify biological intelligence, and the state of the art models clearly demonstrate their capabilities accordingly. For any definition of understanding you care to lay down, there's significant overlap between the way human brains do it and the way LLMs do it. LLMs are specifically designed to model constructs from data, and to model the systems that produce the data they're trained on, and the data they model comes from humans and human processes.
- pwndByDeath 10mo agoYou appear to be a proper alchemist, but you can't support an argument of understanding if there is no definition of understanding that isn't circular. If you want to believe the friendly voice really understands you, we have a word for that, faith. The skeptic sees the interactions with a chatbot as a statistical game that shows how uninteresting (e.g. predictable) humans and our stupid language are. There are useful gimmicks coming out like natural language processing, for low risk applications, but this form of AI pseudoscience isn't going to survive, but it will take some time for research to catch up to understanding how to describe the falsehoods of contemporary AI toys
- deepGem 10mo ago"I don't "understand" how LLMs "understand" anything." Why does the LLM need to understand anything. What today's chatbots have achieved is a software engineering feat. They have taken a stateless token generation machine that has compressed the entire internet's vocabulary to predict the next token and have 'hacked' a whole state management machinery around it. End result is a product that just feels like another human conversing with you and remembering your last birthday. Engineering will surely get better and while purists can argue that a new research perspective is needed, the current growth trajectory of chatbots, agents and code generation tools will carry the torch forward for years to come. If you ask me, this new AI winter will thaw in the atmosphere even before it settles on the ground.