5 ms·

> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago. Well for something to be G or I you need them to solve novel

> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago. Well for something to be G or I you need them to solve novel problems. These things have interested most of the Internet and I've yet to see a "reasoning" disentangle memorization from reasoning. Memorization doesn't mean they aren't useful (not sure why this was ever conflated since... Computers are useful...), but it's very different from G or I. And remember that these tools are trained for human preferential output. If humans prefer things to look like reasoning then that's what they optimize. [0] Sure, maybe your cousin Throckmorton is dumb but that's besides the point. That said, I see no reason human level cognition is impossible. We're not magic. We're machines that follow the laws of physics. ML systems may be far from capturing what goes on in these computers, but that doesn't mean magic exists. [0] If it walks like a duck, quacks like a duck, and swims like a duck, and looks like a duck it's probably a duck. But probably doesn't mean it isn't a well made animatronic. We have those too and they'll convince many humans they are ducks. But that doesn't change what's inside. The subtly matters.

stroupwaffle 2y ago
I think it will be an organoid brain bio-machine. We can already grow organs—just need to grow a brain and connect it to a machine.
- Moosdijk 2y ago
  The keyword being “just”.
  - ggm 2y ago
    Just grow, just connect, just sustain, just avoid the many pitfalls. Indeed just is key
  - godelski 2y ago
    just adverb to turn a complex thing into magic with a simple wave of the hands E.g. To turn lead into gold you _just_ need to remove 3 protons
  - stroupwaffle 2y ago
    You “just” need a more vivid imagination if that’s as far as your comment stretches. I mean seriously, people on here. I’m just spitballing ideas not intended to write some kind of dissertation on brain-machine interaction. That’s Elon musks department.
    - Moosdijk 2y ago
      Okay. The keyword should have been “science fiction”
- idle_zealot 2y ago
  Somehow I doubt that organic cells (structures optimized for independent operation and reproduction, then adapted to work semi-cooperatively) resemble optimal compute fabric for cognition. By that same token I doubt that optimal compute fabric for cognition resembles GPUs or CPUs as we understand them today. I would expect whatever this efficient design is to be extremely unlikely to occur naturally, structurally, and involve some very exotic manufactured materials.
- godelski 2y ago
  Maybe that'll be the first way, but there's nothing special about biology. Remember, we don't have a rigorous definition of things like life, intelligence, and consciousness. We are narrowing it down and making progress, but we aren't there (some people confuse this with a "moving goalpost" but of course "it moves", because when we get closer we have better resolution as to what we're trying to figure out. It'd be a "moving goalpost" in the classic sense if we had a well defined definition and then updated in response to make something not work, specifically in a way that is inconsistent with the previous goalpost. As opposed to being more refined)
  - stroupwaffle 2y ago
    The something special about biology is it uses much less energy than a network of power-hungry graphics cards!
    - godelski 2y ago
      No one denies that. But there's no magic. The real baffling thing is that people refuse to pick up a neuroscience textbook
- Dylan16807 2y ago
  If a brain connected to a machine is "AGI" then we already have a billion AGIs at any given moment.
  - stroupwaffle 2y ago
    Well, I mean to say, not exactly human brains. Consider an extremely large brain modified to add/remove sections to increase its capabilities. They already model neural networks on the human brain, even though they currently use orders of magnitude more energy.
    - Dylan16807 2y ago
      But modifying a brain to be bigger and better doesn't require much in the way of computers, it's basically a separate topic.
danaris 2y ago
I have seen far, far too many people say things along the lines of "Sure, LLMs currently don't seem to be good at [thing LLMs are, at least as of now, fundamentally incapable of], but hey, some people are pretty bad at that sometimes too!" It demonstrates such a complete misunderstanding of the basic nature of the problem that I am left baffled that some of these people claim to actually be in the machine-learning field themselves. How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? I do not know if AGI is possible. Honestly, I'd love to believe that it is. However, it has not remotely been demonstrated that it is possible, and as such, it follows that it cannot have been demonstrated that it is inevitable. If you want to believe that it is inevitable, then I have no quarrel with you; if you want to preach that it is inevitable, and draw specious inferences to "prove" it, then I have a big quarrel with you.
- vundercind 2y ago
  I think the fact that this particular fuzzy statistical analysis tool takes human language as input, and outputs more human language, is really dazzling some folks I’d not have expected to be dazzled by it. That is quickly becoming the most surprising part of this entire development, to me.
  - jofla_net 2y ago
    At the very least, the last few years have laid bare some of the notions of what it takes, technically, to reconstruct certain chains of dialog, and how those chains are regarded completely differently as evidence for or against any and all intelligence it does or may take to conjure them.
  - godelski 2y ago
    I'm astounded by them, still! But what is more astounding to me is all the reactions (even many in the "don't reason" camp, which I am part of). I'm an ML researcher and everyone was shocked when GPT3 came out. It is still impressive, and anyone saying it isn't is not being honest (likely to themselves). But it is amazing to me that "we compressed the entire internet and built a human language interface to access that information" is anything short of mindbogglingly impressive (and RAGs demonstrate how to decrease the lossyness of this compression). It would be complete Sci-Fi not even 10 years ago. I thought it was bad that we make them out to me much more than they are because when you bootstrap like that, you have to make that thing, and fast (e.g. iPhone). But "reasoning" is too big of a promise and we're too far from success. So I'm concerned as a researcher myself, because I like living in the summer. Because I want to work towards AGI. But if a promise is too big and the public realizes it, usually you don't just end up where you were. So it is the duty of any scientist and researcher to prevent their fields from being captured by people who overpromise. Not to "ruin the fun" but to instead make sure the party keeps going (sure, inviting a gorilla to the party may make it more exciting and "epic", but there's a good chance it also goes on a rampage and the party ends a lot sooner).
User23 2y ago
We don't really have the proper vocabulary to talk about this. Well, we do, but C.S. Peirce's writings are still fairly unknown. In short, there are two fundamentally distinct forms of reasoning. One is corollarial reasoning. This is the kind of reasoning that follows deductions that directly follow from the premises. This of course includes subsequent deductions that can be made from those deductions. Obviously computers are very good at this sort of thing. The other is theorematic reasoning. It deals with complexity and creativity. It involves introducing new hypotheses that are not present in the original premises or their corollaries. Computers are not so very good at this sort of thing. When people say AGI, what they are really talking about is an AI that is capable of theorematic reasoning. The most romanticized example of that of course being the AI that is capable of designing (not aiding humans in designing, that's corollarial!) new more capable AIs. All of the above is old hat to the AI winter era guys. But amusingly their reputations have been destroyed much the same as Peirce's was, by dissatisfied government bureaucrats. On the other hand, we did get SQL, which is a direct lineal descendent (as in teacher to teacher) from Peirce's work, so there's that.
- godelski 2y ago
  We don't have proper language, but certainly we've improved. Even since Peirce. You're right that many people are not well versed in the philosophical and logician discussions as to what reasoning is (and sadly this lack of literature review isn't always common in the ML community), but I'm not convinced Peirce solved it. I do like that there are many different categories of reasoning and subcategories. > All of the above is old hat to the AI winter era guys. But amusingly their reputations have been destroyed much the same as Peirce's was, by dissatisfied government bureaucrats. Yeah, this has been odd. Since a lot of their work has shown to be fruitful once scaled. I do think you need a combination of theory people + those more engineering oriented, but having too much of one is not a good thing. It seems like now we're overcorrecting and the community is trying to kick out the theorists. By saying things like "It's just linear algebra"[0] or "you don't need math"[1] or "they're black boxes". These are unfortunate because they encourage one to not look inside and try to remove the opaqueness. Or to dismiss those that do work on this and are bettering our understanding (sometimes even post hoc saying it was obvious). It is quite the confusing time. But I'd like to stop all the bullshit and try to actually make AGI. That does require a competition of ideas and not everyone just boarding the hype train or have no careers.... [0] You can assume anyone that says this doesn't know linear algebra [1] You don't need math to produce good models, but it sure does help you know why your models are wrong (and understanding the meta should make one understand my reference. If you don't, I'm not sure you're qualified for ML research. But that's not a definitive statement either).
eli_gottlieb 2y ago
If it walks like a duck, quacks like a duck, swims like a duck, and looks like a duck it's probably worth dissecting its internal organs to see if it might be related to a duck.

stroupwaffle 2y ago

I think it will be an organoid brain bio-machine. We can already grow organs—just need to grow a brain and connect it to a machine.

Moosdijk 2y ago
The keyword being “just”.
- ggm 2y ago
  Just grow, just connect, just sustain, just avoid the many pitfalls. Indeed just is key
- godelski 2y ago
  just adverb to turn a complex thing into magic with a simple wave of the hands E.g. To turn lead into gold you _just_ need to remove 3 protons
- stroupwaffle 2y ago
  You “just” need a more vivid imagination if that’s as far as your comment stretches. I mean seriously, people on here. I’m just spitballing ideas not intended to write some kind of dissertation on brain-machine interaction. That’s Elon musks department.
  - Moosdijk 2y ago
    Okay. The keyword should have been “science fiction”
idle_zealot 2y ago
Somehow I doubt that organic cells (structures optimized for independent operation and reproduction, then adapted to work semi-cooperatively) resemble optimal compute fabric for cognition. By that same token I doubt that optimal compute fabric for cognition resembles GPUs or CPUs as we understand them today. I would expect whatever this efficient design is to be extremely unlikely to occur naturally, structurally, and involve some very exotic manufactured materials.
godelski 2y ago
Maybe that'll be the first way, but there's nothing special about biology. Remember, we don't have a rigorous definition of things like life, intelligence, and consciousness. We are narrowing it down and making progress, but we aren't there (some people confuse this with a "moving goalpost" but of course "it moves", because when we get closer we have better resolution as to what we're trying to figure out. It'd be a "moving goalpost" in the classic sense if we had a well defined definition and then updated in response to make something not work, specifically in a way that is inconsistent with the previous goalpost. As opposed to being more refined)
- stroupwaffle 2y ago
  The something special about biology is it uses much less energy than a network of power-hungry graphics cards!
  - godelski 2y ago
    No one denies that. But there's no magic. The real baffling thing is that people refuse to pick up a neuroscience textbook
Dylan16807 2y ago
If a brain connected to a machine is "AGI" then we already have a billion AGIs at any given moment.
- stroupwaffle 2y ago
  Well, I mean to say, not exactly human brains. Consider an extremely large brain modified to add/remove sections to increase its capabilities. They already model neural networks on the human brain, even though they currently use orders of magnitude more energy.
  - Dylan16807 2y ago
    But modifying a brain to be bigger and better doesn't require much in the way of computers, it's basically a separate topic.

danaris 2y ago

I have seen far, far too many people say things along the lines of "Sure, LLMs currently don't seem to be good at [thing LLMs are, at least as of now, fundamentally incapable of], but hey, some people are pretty bad at that sometimes too!" It demonstrates such a complete misunderstanding of the basic nature of the problem that I am left baffled that some of these people claim to actually be in the machine-learning field themselves. How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? I do not know if AGI is possible. Honestly, I'd love to believe that it is. However, it has not remotely been demonstrated that it is possible, and as such, it follows that it cannot have been demonstrated that it is inevitable. If you want to believe that it is inevitable, then I have no quarrel with you; if you want to preach that it is inevitable, and draw specious inferences to "prove" it, then I have a big quarrel with you.

vundercind 2y ago
I think the fact that this particular fuzzy statistical analysis tool takes human language as input, and outputs more human language, is really dazzling some folks I’d not have expected to be dazzled by it. That is quickly becoming the most surprising part of this entire development, to me.
- jofla_net 2y ago
  At the very least, the last few years have laid bare some of the notions of what it takes, technically, to reconstruct certain chains of dialog, and how those chains are regarded completely differently as evidence for or against any and all intelligence it does or may take to conjure them.
- godelski 2y ago
  I'm astounded by them, still! But what is more astounding to me is all the reactions (even many in the "don't reason" camp, which I am part of). I'm an ML researcher and everyone was shocked when GPT3 came out. It is still impressive, and anyone saying it isn't is not being honest (likely to themselves). But it is amazing to me that "we compressed the entire internet and built a human language interface to access that information" is anything short of mindbogglingly impressive (and RAGs demonstrate how to decrease the lossyness of this compression). It would be complete Sci-Fi not even 10 years ago. I thought it was bad that we make them out to me much more than they are because when you bootstrap like that, you have to make that thing, and fast (e.g. iPhone). But "reasoning" is too big of a promise and we're too far from success. So I'm concerned as a researcher myself, because I like living in the summer. Because I want to work towards AGI. But if a promise is too big and the public realizes it, usually you don't just end up where you were. So it is the duty of any scientist and researcher to prevent their fields from being captured by people who overpromise. Not to "ruin the fun" but to instead make sure the party keeps going (sure, inviting a gorilla to the party may make it more exciting and "epic", but there's a good chance it also goes on a rampage and the party ends a lot sooner).

User23 2y ago

We don't really have the proper vocabulary to talk about this. Well, we do, but C.S. Peirce's writings are still fairly unknown. In short, there are two fundamentally distinct forms of reasoning. One is corollarial reasoning. This is the kind of reasoning that follows deductions that directly follow from the premises. This of course includes subsequent deductions that can be made from those deductions. Obviously computers are very good at this sort of thing. The other is theorematic reasoning. It deals with complexity and creativity. It involves introducing new hypotheses that are not present in the original premises or their corollaries. Computers are not so very good at this sort of thing. When people say AGI, what they are really talking about is an AI that is capable of theorematic reasoning. The most romanticized example of that of course being the AI that is capable of designing (not aiding humans in designing, that's corollarial!) new more capable AIs. All of the above is old hat to the AI winter era guys. But amusingly their reputations have been destroyed much the same as Peirce's was, by dissatisfied government bureaucrats. On the other hand, we did get SQL, which is a direct lineal descendent (as in teacher to teacher) from Peirce's work, so there's that.

godelski 2y ago
We don't have proper language, but certainly we've improved. Even since Peirce. You're right that many people are not well versed in the philosophical and logician discussions as to what reasoning is (and sadly this lack of literature review isn't always common in the ML community), but I'm not convinced Peirce solved it. I do like that there are many different categories of reasoning and subcategories. > All of the above is old hat to the AI winter era guys. But amusingly their reputations have been destroyed much the same as Peirce's was, by dissatisfied government bureaucrats. Yeah, this has been odd. Since a lot of their work has shown to be fruitful once scaled. I do think you need a combination of theory people + those more engineering oriented, but having too much of one is not a good thing. It seems like now we're overcorrecting and the community is trying to kick out the theorists. By saying things like "It's just linear algebra"[0] or "you don't need math"[1] or "they're black boxes". These are unfortunate because they encourage one to not look inside and try to remove the opaqueness. Or to dismiss those that do work on this and are bettering our understanding (sometimes even post hoc saying it was obvious). It is quite the confusing time. But I'd like to stop all the bullshit and try to actually make AGI. That does require a competition of ideas and not everyone just boarding the hype train or have no careers.... [0] You can assume anyone that says this doesn't know linear algebra [1] You don't need math to produce good models, but it sure does help you know why your models are wrong (and understanding the meta should make one understand my reference. If you don't, I'm not sure you're qualified for ML research. But that's not a definitive statement either).

eli_gottlieb 2y ago

If it walks like a duck, quacks like a duck, swims like a duck, and looks like a duck it's probably worth dissecting its internal organs to see if it might be related to a duck.