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The reality is that o1 is a step away from general intelligence and back towards narrow ai. It is great for solving the kinds of math, coding and logic puzzles

The reality is that o1 is a step away from general intelligence and back towards narrow ai. It is great for solving the kinds of math, coding and logic puzzles it has been designed for, but for many kinds of tasks, including chat and creative writing, it is actually worse than 4o. It is good at the specific kinds of reasoning tasks that it was built for, much like alpha-go is great at playing go, but that does not actually mean it is more generally intelligent.

adrianN 2y ago
So-so general intelligence is a lot harder to sell than narrow competence.
kilroy123 2y ago
Yes, I don't understand their ridiculous AGI hype. I get it you need to raise a lot of money. We need to crack the code for updating the base model on the fly or daily / weekly. Where is the regular learning by doing? Not over the course of a year, spending untold billions to do it.
- tomohelix 2y ago
  Technically, the models can already learn on the fly. Just that the knowledge it can learn is limited to the context length. It cannot, to use the trendy word, "grok" it and internally adjust the weights in its neural network yet. To change this you would either need to let the model retrain itself every time it receives new information, or to have such a great context length that there is no effective difference. I suspect even meat models like our brains is still struggling to do this effectively and need a long rest cycle (i.e. sleep) to handle it. So the problem is inherently more difficult to solve than just "thinking". We may even need an entire new architecture different from the neural network to achieve this.
  - KuriousCat 2y ago
    Only small problem is that models are neither thinking nor understanding, I am not sure how this kind of wording is allowed with these models.
    - ben_w 2y ago
      All words only gain meaning through common use: where two people mean different things by some word, we influence each other until we're in agreement. Words about private internal state don't get feedback about what they actually are on the inside, just about what they look like on the outside* — "thinking" and "understanding" map to what AI give the outward impression of, even if the inside is different in whatever ways you regard as important. * This is also how people with aphantasia keep reporting their surprise upon realising that scenes in films where a character is imagining something are not merely artistic license.
  - chikere232 2y ago
    > Technically, the models can already learn on the fly. Just that the knowledge it can learn is limited to the context length. Isn't that just improving the prompt to the non-learning model?
  - mike_hearn 2y ago
    Google just published a paper on a new neural architecture that does exactly that, called Titans.
- ninetyninenine 2y ago
  I understand the hype. I think most humans understand why a machine responding to a query like never before in the history of mankind is amazing. What you’re going through is hype overdose. You’re numb to it. Like I can get if someone disagrees but it’s a next level lack of understanding human behavior if you don’t get the hype at all. There exists living human beings who are still children or with brain damage with comparable intelligence to an LLM and we classify those humans as conscious but we don’t with LLMs. I’m not trying to say LLMs are conscious but just saying that the creation of LLMs marks a significant turning point. We crossed a barrier 2 years ago somewhat equivalent to landing on the moon and i am just dumb founded that someone doesn’t understand why there is hype around this.
  - b112 2y ago
    The first plane ever flies, and people think "we can fly to the moon soon!". Yet powered flight has nothing to do with space travel, no connection at all. Gliding in the air via low/high pressure doesn't mean you'll get near space, ever, with that tech. No matter how you try. AI and AGI are like this.
    - ninetyninenine 2y ago
      That’s not true. There was not endless hype about flying to the moon when the first plane flew. People are well aware of the limits of LLMs. As slow as the progress is, we now have metrics and measurable progress towards agi even when there are clear signs of limitations on LLMs. We never had this before and everyone is aware of this. No one is delusional about it. The delusion is more around people who think other people are making claims of going to the moon in a year or something. I can see it in 10 to 30 years.
      - b112 2y ago
        That’s not true. There was not endless hype about flying to the moon when the first plane flew. I didn't say there was endless hype, I gave an example of how one technology would never result in another... even if to a layperson it seems connected. (The sky, and the moon, are "up") People are well aware of the limits of LLMs. Surely you mean "Some people". Because the point in this thread is that there is a lot of hype, and FOMO, and "OMG AGI!" chatter running around LLMs. Which will never ever make AGI.
madeofpalk 2y ago
LLMs will not give us "artificial general intelligence", whatever that means.
- swalsh 2y ago
  In my opinion it's probably closer to real agi then it's not. I think the missing piece is learning after the pretraining phase.
- nurettin 2y ago
  I think it means a self-sufficient mind, which LLMs inherently are not.
  - ben_w 2y ago
    What is "self-sufficient" in this case? Lots of debate since ChatGPT and Stable Diffusion can be summarised as A: "AI cheated by copying humans, it just mixes the bits up really small like a collage" B: "So like humans learning from books and studying artists?" A: "That doesn't count, it's totally different" Even though I am quite happy to agree that differences exist, I have yet to see a clear answer as to what about people even mean when asserting that AI learning from books is "cheating" given that it's *mandatory* for humans in most places.
    - nurettin 2y ago
      I just think that language is a big part of the puzzle, but it is not the only one. Simply generating tokens may sometimes look like thought, but as you feed the output back at itself, it quickly devolves into repeating nonsense and looks nothing like introspection. Self-sufficiency would reliably form new ideas and angles.
- righthand 2y ago
  AGI currently is an intentionally vague and undefined goal. This allows businesses to operate towards a goal, define the parameters, and relish in the “rocket launches”-esque hype without leaving the vague umbrella of AI. It allows businesses to claim a double pursuit. Not only are they building AGI but all their work will surely benefit AI as well. How noble. Right? It’s vagueness is intentional and allows you to ignore the blind truth and fill in the gaps yourself. You just have to believe it’s right around the corner.
raincole 2y ago
Which sounds like... a very good thing?
golol 2y ago
This is kind if true. I feel like the reasoning power if O1 is really only truly available on the kinds of math/coding tasks it was trained on so much.

adrianN 2y ago

So-so general intelligence is a lot harder to sell than narrow competence.

kilroy123 2y ago

Yes, I don't understand their ridiculous AGI hype. I get it you need to raise a lot of money. We need to crack the code for updating the base model on the fly or daily / weekly. Where is the regular learning by doing? Not over the course of a year, spending untold billions to do it.

tomohelix 2y ago
Technically, the models can already learn on the fly. Just that the knowledge it can learn is limited to the context length. It cannot, to use the trendy word, "grok" it and internally adjust the weights in its neural network yet. To change this you would either need to let the model retrain itself every time it receives new information, or to have such a great context length that there is no effective difference. I suspect even meat models like our brains is still struggling to do this effectively and need a long rest cycle (i.e. sleep) to handle it. So the problem is inherently more difficult to solve than just "thinking". We may even need an entire new architecture different from the neural network to achieve this.
- KuriousCat 2y ago
  Only small problem is that models are neither thinking nor understanding, I am not sure how this kind of wording is allowed with these models.
  - ben_w 2y ago
    All words only gain meaning through common use: where two people mean different things by some word, we influence each other until we're in agreement. Words about private internal state don't get feedback about what they actually are on the inside, just about what they look like on the outside* — "thinking" and "understanding" map to what AI give the outward impression of, even if the inside is different in whatever ways you regard as important. * This is also how people with aphantasia keep reporting their surprise upon realising that scenes in films where a character is imagining something are not merely artistic license.
- chikere232 2y ago
  > Technically, the models can already learn on the fly. Just that the knowledge it can learn is limited to the context length. Isn't that just improving the prompt to the non-learning model?
- mike_hearn 2y ago
  Google just published a paper on a new neural architecture that does exactly that, called Titans.
ninetyninenine 2y ago
I understand the hype. I think most humans understand why a machine responding to a query like never before in the history of mankind is amazing. What you’re going through is hype overdose. You’re numb to it. Like I can get if someone disagrees but it’s a next level lack of understanding human behavior if you don’t get the hype at all. There exists living human beings who are still children or with brain damage with comparable intelligence to an LLM and we classify those humans as conscious but we don’t with LLMs. I’m not trying to say LLMs are conscious but just saying that the creation of LLMs marks a significant turning point. We crossed a barrier 2 years ago somewhat equivalent to landing on the moon and i am just dumb founded that someone doesn’t understand why there is hype around this.
- b112 2y ago
  The first plane ever flies, and people think "we can fly to the moon soon!". Yet powered flight has nothing to do with space travel, no connection at all. Gliding in the air via low/high pressure doesn't mean you'll get near space, ever, with that tech. No matter how you try. AI and AGI are like this.
  - ninetyninenine 2y ago
    That’s not true. There was not endless hype about flying to the moon when the first plane flew. People are well aware of the limits of LLMs. As slow as the progress is, we now have metrics and measurable progress towards agi even when there are clear signs of limitations on LLMs. We never had this before and everyone is aware of this. No one is delusional about it. The delusion is more around people who think other people are making claims of going to the moon in a year or something. I can see it in 10 to 30 years.
    - b112 2y ago
      That’s not true. There was not endless hype about flying to the moon when the first plane flew. I didn't say there was endless hype, I gave an example of how one technology would never result in another... even if to a layperson it seems connected. (The sky, and the moon, are "up") People are well aware of the limits of LLMs. Surely you mean "Some people". Because the point in this thread is that there is a lot of hype, and FOMO, and "OMG AGI!" chatter running around LLMs. Which will never ever make AGI.

madeofpalk 2y ago

LLMs will not give us "artificial general intelligence", whatever that means.

swalsh 2y ago
In my opinion it's probably closer to real agi then it's not. I think the missing piece is learning after the pretraining phase.
nurettin 2y ago
I think it means a self-sufficient mind, which LLMs inherently are not.
- ben_w 2y ago
  What is "self-sufficient" in this case? Lots of debate since ChatGPT and Stable Diffusion can be summarised as A: "AI cheated by copying humans, it just mixes the bits up really small like a collage" B: "So like humans learning from books and studying artists?" A: "That doesn't count, it's totally different" Even though I am quite happy to agree that differences exist, I have yet to see a clear answer as to what about people even mean when asserting that AI learning from books is "cheating" given that it's *mandatory* for humans in most places.
  - nurettin 2y ago
    I just think that language is a big part of the puzzle, but it is not the only one. Simply generating tokens may sometimes look like thought, but as you feed the output back at itself, it quickly devolves into repeating nonsense and looks nothing like introspection. Self-sufficiency would reliably form new ideas and angles.
righthand 2y ago
AGI currently is an intentionally vague and undefined goal. This allows businesses to operate towards a goal, define the parameters, and relish in the “rocket launches”-esque hype without leaving the vague umbrella of AI. It allows businesses to claim a double pursuit. Not only are they building AGI but all their work will surely benefit AI as well. How noble. Right? It’s vagueness is intentional and allows you to ignore the blind truth and fill in the gaps yourself. You just have to believe it’s right around the corner.

raincole 2y ago

Which sounds like... a very good thing?

golol 2y ago

This is kind if true. I feel like the reasoning power if O1 is really only truly available on the kinds of math/coding tasks it was trained on so much.