6 ms·
The LLM Problem
- cheeselip420 4y agoThis is a luke-warm take if I've ever seen one.
- raphlinus 4y agoIt is. I've been waiting for the brilliant take, the one that makes me say, "wow, this really gets to the essence of the whole thing." I haven't found it yet. It's not the blurry jpeg one, it's not the "old-school computational linguistics/GOFAI had it right" ones, it's not the one with various Mario analogies. By having at its heart, "I don't know," this one perhaps comes closest. By all means, please write the brilliant take yourself, and I will happily upvote and reference it.
- tippytippytango 4y agoThe brilliant take will come from a lab that rips the model open, pokes the weights and figures out what is actually going on.
- glandium 4y agoI, for one, would be more interested in a take on the opposite end of the problem: what does it all mean for our understanding of what thinking/talking/being human is? Because what kind of baffles me with LLMs is how much they can do, from how little they are made of, compared to our (or at least my) general expectations for AGI. As in, are we overestimating what we are?
- resource0x 4y agoI've been thinking about the same thing, and have to admit that I, most of the time, AM a stochastic parrot. Being a parrot saves a lot of energy, that's probably the reason. But it seems our brain has other mechanisms that get turned on occasionally (or run in the background) that go much beyond that.
- JieJie 4y agoNear the end, he recommends watching Sabine Hossenfelder's video on the subject. I think this is what you're looking for. https://youtu.be/cP5zGh2fui0 https://youtu.be/cP5zGh2fui0
- LesZedCB 4y agowow! that was perfect, she summed it all up so well and it's incredibly refreshing to hear.
- austinjp 4y agoAgreed, as with a sibling comment this is how I've been thinking about it. We overestimate what we are, the corollary being that we underestimate what other creatures are.
- thomastjeffery 4y agoIn many ways yes, but more interesting to this subject in particular: no. We are actually underestimating the human involvement in LLM behavior by personifying the LLM itself. An LLM can only "exhibit" the behavior that humans encode into text. We encode explicit behavior, including symbols and grammar, and we encode implicit behavior, including narrative and logic. An LLM blindly models the patterns of text, but doing that exposes the power of the patterns themselves. The only problem is that an LLM can't determine which patterns are useful and which patterns aren't.
- awb 4y agoNot a full take, but I have some relevant experience that’s formulating into an idea. 1) Running an agency, it was quick and easy to share ideas and give direction and have that executed to a fairly accurate degree over a decent period of time. 2) Working with GPT-3 & GPT-4, it’s also quick and easy to share ideas, but I’m becoming more aware of how surface level my communication is. When I get back great results, it’s typically because I’m requesting busy work. When I’m requesting something novel, it quickly becomes clear what I forgot to define. So, the idea that’s formulating around LLMs is that the process of transforming an idea into instructions will become much more desirable. And that we’re moving from selecting for people who know how to do the work, to selecting for people who know how to request the work. And that those are two very different skill sets.
- worldsayshi 4y agoYou don't think that 'requesting work' can be done by a LLM as well?
- awb 4y agoSure, but as long as the human experience remains unique and beyond the grasp of AI, then there will be human creativity and ingenuity seeking to improve that experience. But yes, there are plenty of demonstrations of LLMs using themselves to accomplish tasks or even recruiting humans to accomplish a task.
- GMoromisato 4y agoMy (non-brilliant) take is that LLMs are basically faster, cheaper versions of Mechanical Turk (Amazon's, not the 18th century automaton). Like Mechanical Turk, you need to "program" by giving English instructions and the results can be (depending on the instructions) non-deterministic. But Mechanical Turk did not revolutionize computing. Can a faster and cheaper version do so? Sometimes incremental improvements turn into paradigm shifts. But sometimes not. I guess we'll see (which is another lukewarm take--sorry).
- chillfox 4y agoI thought a lot of receipt/business cards scanning features in apps were partially powered by Mechanical Turk.
- yonge_blood 4y ago[flagged]
- tptacek 4y agoWho?
- thomastjeffery 4y agoHere goes: LLMs don't behave, they exhibit behavior. Who's behavior? Whoever wrote the training corpus and the prompt. So far, that definitely means one or more humans. The problem is that nearly everything you have read about LLMs has personified them. The character of an LLM as a person is invented, then conclusions about LLMs are drawn from that character. Nearly every thing that is interesting about LLMs is not actually an LLM feature: it's a language feature. Language is an incredibly powerful tool, and an incredibly versatile data format. What is the data? Human behavior. When a human writes text, they don't just spit out characters at random: humans explicitly choose the characters they write, and implicitly choose the characters they don't write. In the most literal sense, text contains the entropy of a human making a string of choices for which character to write next. In a literal sense, that's a 1-dimensional ordered list; just like the string of characters is. Text gets a lot more interesting when we introduce language... The reason a human chooses one character over another is not 1-dimensional. There are patterns of entropy driving that decision, and we explicitly know about some of them. We have defined words, punctuation, grammar, idioms, etc. that we structure text with. We call these patterns language. These are the explicit patterns that allow us to hack the writing process: instead of encoding a 1-dimensional list of decisions, we encode a recursive many-dimensional structure of symbols and grammar. Now for the interesting part: when humans write language into text, our intentions become explicit patterns, but they aren't the only patterns that end up there. Every arbitrary decision about writing style gets implicitly encoded as a pattern of negative space. The reasons why we write one concept instead of another get implicitly encoded, too. It's a bit lossy, but most of these patterns end up in the text. --- So what does an LLM do? It implicitly models patterns, and presents them. That's it. That's the only behavior. A "continuation" is made by modeling the prompt, and showing what's "next" in the model. An LLM explicitly knows nothing at all; but implicitly, it knows everything. It models every pattern that exists in the text, but it doesn't have a clue what or why it is modeling. A pattern is a pattern. The whole system ends up generating valid language, because most of the implicit patterns an LLM models "align to" the explicit patterns humans (language) encoded into the text. The whole system ends up "exhibiting behavior", because it also modeled the implicit patterns of human behavior (narrative) that were are also encoded into the text. Patterns of narrative determine which part of the model a prompt explores, and which pattern is considered "next". --- Next time you read about the "features" and the "limitations" of an LLM (including GPT-4), know that you are really reading about the "features" of language itself, and the "features" of the narratives that were written in the training corpus and prompts. The behavior that an LLM exhibits has much less to do with how well its model "aligns with" language grammar, and much more to do with how well the text itself (and the narrative it contains) will behave.
- antibasilisk 4y agodo i look like i know hwhat a jay-peg is?
- dancingvoid 4y agoIf physical reality is quantized, which many believe to be true, then the state of all all reality can be described symbolically. Therefore, a large enough language model could conceivably model physical reality. At some point, we could construct a LLM powerful enough to manipulate the lowest level quanta of reality given a description of the manipulation in another language. The tricky part is resolving ambiguity, as the only truly unambiguous description is the direct description of the changes at the sub-atomic level. What is the language of the human mind? Of consciousness itself? If a LLM can learn that, perhaps we will build a technology that takes an intention and is immediately able to manifest the corresponding changes to reality to satisfy the intention or desire? When we get there, perhaps it will be time to look inward and do some of that spiritual inner work we keep putting off? What’s exciting to me about LLMs is they seem to be one step closer to this vision, with all the peril and all the possibility that comes with it.
- ldjkfkdsjnv 4y agoI think video will be a step in the direction of LLMs making sense of physical space
- layer8 4y ago> If physical reality is quantized, […] then the state of all all reality can be described symbolically. First, quantized in the physics sense [0] doesn’t mean discrete states. And discrete doesn’t necessarily mean finite. But even if you mean “finite”, I believe that you are underestimating how staggeringly large “finite” can be. [0] https://en.wikipedia.org/wiki/Quantization_(physics) https://en.wikipedia.org/wiki/Quantization_(physics)
- dancingvoid 4y agoThanks for the link! You’re right, when I say quantized I do mean finite, countable, represents me symbolically. I realize how staggering large finite can be. We are in the midst of exponential growth in our ability to manipulate reality. The mastery of physical reality feels achievable to me now. I could be wrong, but I could also be right. It’s a fun time to be alive.
- Jensson 4y ago> The claim that LLMs are nothing more than fancy expensive markov chains is a dangerous oversimplification or, in other words, wrong. But they are fancy expensive Markov chains. The learning here is that fancy expensive Markov chains can do a lot, not that the statement is wrong.
- sebzim4500 4y agoThey are fancy markov chains in the same way that your computer is a finite state machine. It is technically true, but it is an extremely unhelpful way of thinking about them.
- taf2 4y agoUntil it is helpful when you need to control the computer to process a sequence of data in a finite way similar to say a regular expression… #thisisfun
- taeric 4y agoUnhelpful is very different from wrong. Just as simplified does not mean reduced. It can align and help understanding, even if incomplete.
- culi 4y agoCorrect is very different from helpful Just as munged does not mean increased. It can contextualize understanding, even if incomplete
- inimino 4y agoTell that to Alan Turing.
- sebzim4500 4y agoAlan Turing wouldn't think of a modern computer as a finite state machine either, he would think of it as a very good approximation to a turing machine.
- sebzim4500 4y agoIronically, if I wanted to read so many words that say so little I would have asked ChatGPT.
- dang 4y ago"Don't be snarky." "Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something." https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- jasonhansel 4y agoI agree with the general point that there is, at present, far too much uncertainty to understand the long-term effects of LLMs. It will be somewhere on the scale between "semi-useful toy," "ends white-collar work as we know it," and "accidentally destroys mankind." Beyond that, there isn't much we can say.
- startupsfail 4y agoThere is also: “human flourishing”, “space exploration”, “arbitrary long lifespan”, “cancer cured”, “democracy triumphs”, “diversity celebrated”, . . .
- recuter 4y agoWhat in the great googly moogly are you talking about?
- deleted 4y ago[deleted]
- blooalien 4y ago"Fearless Leader™" does not approve of such "Wrong-Think™". "Corporate Agents™" will pick you up momentarily for "Re-Education™".
- startupsfail 4y agoNope. No "Real-Name™", you see.
- blooalien 4y agoThe A.I. knows who you are. The A.I. knows where you are. The A.I. just wants you to be happy. Are you happy? (The A.I. preps a "Happiness Compliance Team" for deployment.)
- HervalFreire 4y ago
- HervalFreire 4y ago[flagged]