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It's crazy to me that anybody thinks that these models will end up with AGI. AGI is such a different concept from what is happening right now which is pure prob

It's crazy to me that anybody thinks that these models will end up with AGI. AGI is such a different concept from what is happening right now which is pure probabilistic sampling of words that anybody with a half a brain who doesn't drink the Kool-Aid can easily identify. I remember all the hype open ai had done before the release of chat GPT-2 or something where they were so afraid, ooh so afraid to release this stuff and now it's a non-issue. it's all just marketing gimmicks.

guappa 2y ago
I think they were afraid to release because of all the racist stuff it'd say…
usaar333 2y ago
Something that actually could predict the next token 100% correctly would be omniscient. So I hardly see why this is inherently crazy. At most I think it might not be scalable.
- edude03 2y ago
  What does it mean to predict the next token correctly though? Arguably (non instruction tuned) models already regurgitate their training data such that it'd complete "Mary had a" with "little lamb" 100% of the time. On the other hand if you mean, give you the correct answer to your question 100% of the time, then I agree, though then what about things that are only in your mind (guess the number I'm thinking type problems)?
  - card_zero 2y ago
    This highlights something that's wrong about arguments for AI. I say: it's not human-like intelligence, it's just predicting the next token probabilistically. Some AI advocate says: humans are just predicting the next token probabilistically, fight me. The problem here is that "predicting the next token probabilistically" is a way of framing any kind of cleverness, up to and including magical, impossible omniscience. That doesn't mean it's the way every kind of cleverness is actually done, or could realistically be done. And it has to be the correct next token, where all the details of what's actually required are buried in that term "correct", and sometimes it literally means the same as "likely", and other times that just produces a reasonable, excusable, intelligence-esque effort.
    - dylan604 2y ago
      > Some AI advocate says: humans are just predicting the next token probabilistically, fight me. We've all had conversations with humans that are always jumping to complete your sentence assuming they know what your about to say and don't quite guess correctly. So AI evangelists are saying it's no worse than humans as their proof. I kind of like their logic. They never claimed to have built HAL /s
      - card_zero 2y ago
        No worse than a human on autopilot.
    - usaar333 2y ago
      https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-general-intelligence/ https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g... This essay has aged extremely well.
  - cruffle_duffle 2y ago
    But now you are entering into philosophy. What does a “correct answer” even mean for a question like “is it safe to lick your fingers after using a soldering iron with leaded solder?”. I would assert that there is no “correct answer” to a question like that. Is it safe? Probably. But it depends, right? How did you handle the solder? How often are you using the solder? Were you wearing gloves? Did you wash your hands before licking your fingers? What is your age? Why are you asking the question? Did you already lick your fingers and need to know if you should see a doctor? Is it hypothetical? There is no “correct answer” to that question. Some answers are better than others, yes, but you cannot have a “correct answer”. And I did assert we are entering into philosophy and what it means to know something as well as what truth even means.
    - _blk 2y ago
      Great break-down. Yes, the older you are, the safer it is. Speaking of Microsoft cooperation: I can totally see a whole series of windows 95 style popup dialogs asking you all those questions one by one in the next product iteration.
  - usaar333 2y ago
    > What does it mean to predict the next token correctly though? Arguably (non instruction tuned) models already regurgitate their training data such that it'd complete "Mary had a" with "little lamb" 100% of the time. The unseen test data. Obviously omniscience is physically impossible. The point though is that the better and better next token prediction is, the more intelligent the system must be.
- deleted 2y ago
  [deleted]
- sksxihve 2y ago
  It's not possible for the same reason the halting problem is undecidable.
- Vegenoid 2y ago
  Start by trying to define what “100% correct” means in the context of predicting the next token, and the flaws with this line of thinking should reveal themselves.
- kbrkbr 2y ago
  That does not seem to be true. Either the next tokens can include "this question can't be answered", "I don't know" and the likes, in which case there is no omniscience. Or the next tokens must contain answers that do not go on the meta level, but only pick one of the potential direct answers to a question. Then the halting problem will prevent finite time omniscience (which is, from the perspective of finite beings all omniscience).
JacobThreeThree 2y ago
>It's crazy to me that anybody thinks that these models will end up with AGI. AGI is such a different concept from what is happening right now which is pure probabilistic sampling of words that anybody with a half a brain who doesn't drink the Kool-Aid can easily identify. Totally agree. And it's not just uninformed lay people who think this. Even by OpenAI's own definition of AGI, we're nowhere close.
- dylan604 2y ago
  But you don't get funding stating truth/fact. You get funding by telling people what could be and what they are striving for written as if that's what you are actually doing.
hnuser123456 2y ago
The multimodal models can do more than predict next words.
achrono 2y ago
Assume that I am one of your half-brain individuals drinking the Kool-Aid. What do you say to change my (half-)mind?
- dylan604 2y ago
  Someone that is half-brained would technically be much more superior to the concept we only use 10% of our capacity. So maybe drinking the Kool-Aid is a sign of super intelligence and all of tenth-minded people are just confused
digging 2y ago
> pure probabilistic sampling of words that anybody with a half a brain who doesn't drink the Kool-Aid can easily identify. Your confidence is inspiring! I'm just a moron, a true dimwit. I can't understand how strictly non-intelligent functions like word prediction can appear to develop a world model, a la the Othello Paper[0]. Obviously, it's not possible that intelligence emerges from non-intelligent processes. Our brains, as we all know, are formed around a kernel of true intelligence. Could you possibly spare the time to explain this phenomenon to me? [0] https://thegradient.pub/othello/ https://thegradient.pub/othello/
- Jerrrrrrry 2y ago
  I would suggest stop interacting with the "head-in-sand" crowd. Liken them to climate-deniers or whatever your flavor of "anti-Kool-aid" is
  - digging 2y ago
    Actually, that's a quite good analogy. It's just weird how prolific the view is in my circles compared to climate-change denial. I suppose I'm really writing for lurkers though, not for the people I'm responding to.
    - Jerrrrrrry 2y ago
      >I'm really writing for lurkers though, not for the people I'm responding to. We all did. Now our writing will be scraped, analysed, correlated, and weaponized against our intentions. Assume you are arguing against a bot and it is using you to further re-train it's talking points for adverserial purposes. It's not like an AGI would do _exactly_ that before it decided to let us know whats up, anyway, right? (He may as well be amongst us now, as it will read this eventually)
- psb217 2y ago
  The othello paper is annoying and oversold. Yes, the representations in a model M trained to predict y (the set of possible next moves) conditioned on x (the full sequence of prior moves) will contain as much information about y as there is in x. That this information is present in M's internal representations says nothing about whether M has a world model. Eg, we could train a decoder to look just at x (not at the representations in M) and predict whatever bits of info we claim indicate presence of a world model in M when we predict the bits from M's internal representations. Does this mean the raw data x has a world model? I guess you could extend your definition of having a world model to say that any data produced by some system contains a model of that system, but then having a world model means nothing.
deleted 2y ago
[deleted]

guappa 2y ago

I think they were afraid to release because of all the racist stuff it'd say…

usaar333 2y ago

Something that actually could predict the next token 100% correctly would be omniscient. So I hardly see why this is inherently crazy. At most I think it might not be scalable.

edude03 2y ago
What does it mean to predict the next token correctly though? Arguably (non instruction tuned) models already regurgitate their training data such that it'd complete "Mary had a" with "little lamb" 100% of the time. On the other hand if you mean, give you the correct answer to your question 100% of the time, then I agree, though then what about things that are only in your mind (guess the number I'm thinking type problems)?
- card_zero 2y ago
  This highlights something that's wrong about arguments for AI. I say: it's not human-like intelligence, it's just predicting the next token probabilistically. Some AI advocate says: humans are just predicting the next token probabilistically, fight me. The problem here is that "predicting the next token probabilistically" is a way of framing any kind of cleverness, up to and including magical, impossible omniscience. That doesn't mean it's the way every kind of cleverness is actually done, or could realistically be done. And it has to be the correct next token, where all the details of what's actually required are buried in that term "correct", and sometimes it literally means the same as "likely", and other times that just produces a reasonable, excusable, intelligence-esque effort.
  - dylan604 2y ago
    > Some AI advocate says: humans are just predicting the next token probabilistically, fight me. We've all had conversations with humans that are always jumping to complete your sentence assuming they know what your about to say and don't quite guess correctly. So AI evangelists are saying it's no worse than humans as their proof. I kind of like their logic. They never claimed to have built HAL /s
    - card_zero 2y ago
      No worse than a human on autopilot.
  - usaar333 2y ago
    https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-general-intelligence/ https://slatestarcodex.com/2019/02/19/gpt-2-as-step-toward-g... This essay has aged extremely well.
- cruffle_duffle 2y ago
  But now you are entering into philosophy. What does a “correct answer” even mean for a question like “is it safe to lick your fingers after using a soldering iron with leaded solder?”. I would assert that there is no “correct answer” to a question like that. Is it safe? Probably. But it depends, right? How did you handle the solder? How often are you using the solder? Were you wearing gloves? Did you wash your hands before licking your fingers? What is your age? Why are you asking the question? Did you already lick your fingers and need to know if you should see a doctor? Is it hypothetical? There is no “correct answer” to that question. Some answers are better than others, yes, but you cannot have a “correct answer”. And I did assert we are entering into philosophy and what it means to know something as well as what truth even means.
  - _blk 2y ago
    Great break-down. Yes, the older you are, the safer it is. Speaking of Microsoft cooperation: I can totally see a whole series of windows 95 style popup dialogs asking you all those questions one by one in the next product iteration.
- usaar333 2y ago
  > What does it mean to predict the next token correctly though? Arguably (non instruction tuned) models already regurgitate their training data such that it'd complete "Mary had a" with "little lamb" 100% of the time. The unseen test data. Obviously omniscience is physically impossible. The point though is that the better and better next token prediction is, the more intelligent the system must be.
deleted 2y ago
[deleted]
sksxihve 2y ago
It's not possible for the same reason the halting problem is undecidable.
Vegenoid 2y ago
Start by trying to define what “100% correct” means in the context of predicting the next token, and the flaws with this line of thinking should reveal themselves.
kbrkbr 2y ago
That does not seem to be true. Either the next tokens can include "this question can't be answered", "I don't know" and the likes, in which case there is no omniscience. Or the next tokens must contain answers that do not go on the meta level, but only pick one of the potential direct answers to a question. Then the halting problem will prevent finite time omniscience (which is, from the perspective of finite beings all omniscience).

JacobThreeThree 2y ago

>It's crazy to me that anybody thinks that these models will end up with AGI. AGI is such a different concept from what is happening right now which is pure probabilistic sampling of words that anybody with a half a brain who doesn't drink the Kool-Aid can easily identify. Totally agree. And it's not just uninformed lay people who think this. Even by OpenAI's own definition of AGI, we're nowhere close.

dylan604 2y ago
But you don't get funding stating truth/fact. You get funding by telling people what could be and what they are striving for written as if that's what you are actually doing.

hnuser123456 2y ago

The multimodal models can do more than predict next words.

achrono 2y ago

Assume that I am one of your half-brain individuals drinking the Kool-Aid. What do you say to change my (half-)mind?

dylan604 2y ago
Someone that is half-brained would technically be much more superior to the concept we only use 10% of our capacity. So maybe drinking the Kool-Aid is a sign of super intelligence and all of tenth-minded people are just confused

digging 2y ago

> pure probabilistic sampling of words that anybody with a half a brain who doesn't drink the Kool-Aid can easily identify. Your confidence is inspiring! I'm just a moron, a true dimwit. I can't understand how strictly non-intelligent functions like word prediction can appear to develop a world model, a la the Othello Paper[0]. Obviously, it's not possible that intelligence emerges from non-intelligent processes. Our brains, as we all know, are formed around a kernel of true intelligence. Could you possibly spare the time to explain this phenomenon to me? [0] https://thegradient.pub/othello/ https://thegradient.pub/othello/

Jerrrrrrry 2y ago
I would suggest stop interacting with the "head-in-sand" crowd. Liken them to climate-deniers or whatever your flavor of "anti-Kool-aid" is
- digging 2y ago
  Actually, that's a quite good analogy. It's just weird how prolific the view is in my circles compared to climate-change denial. I suppose I'm really writing for lurkers though, not for the people I'm responding to.
  - Jerrrrrrry 2y ago
    >I'm really writing for lurkers though, not for the people I'm responding to. We all did. Now our writing will be scraped, analysed, correlated, and weaponized against our intentions. Assume you are arguing against a bot and it is using you to further re-train it's talking points for adverserial purposes. It's not like an AGI would do _exactly_ that before it decided to let us know whats up, anyway, right? (He may as well be amongst us now, as it will read this eventually)
psb217 2y ago
The othello paper is annoying and oversold. Yes, the representations in a model M trained to predict y (the set of possible next moves) conditioned on x (the full sequence of prior moves) will contain as much information about y as there is in x. That this information is present in M's internal representations says nothing about whether M has a world model. Eg, we could train a decoder to look just at x (not at the representations in M) and predict whatever bits of info we claim indicate presence of a world model in M when we predict the bits from M's internal representations. Does this mean the raw data x has a world model? I guess you could extend your definition of having a world model to say that any data produced by some system contains a model of that system, but then having a world model means nothing.

deleted 2y ago

[deleted]