4 ms·

It’s definitely Good to not put all our eggs in the LLM basket. Even openAI says it’s only a part of the solution - but it has scaled more than most anyone expe

It’s definitely Good to not put all our eggs in the LLM basket. Even openAI says it’s only a part of the solution - but it has scaled more than most anyone expected. Will that continue forever and we keep getting more impressive emergent behaviors from it? I doubt that but I could certainly be wrong. It still seems to be missing any sense of what is True, not sure if that’s possible to embed in that model or if we’ll just have some human feedback hacks and eventually get a better model

gitfan86 4y ago
That debate is becoming irrelevant. Sure it would be great if GTP-6 cost 50k to train instead of 100M. But even if costs 100M it will produce many billions of dollars of value, so the original investment is still relatively small.
- scrollaway 4y ago
  Yeah but the difference between those two numbers is one is accessible to individuals (albeit wealthy ones), the other is accessible only to large-ish companies.
ftxbro 4y ago
> Will that continue forever and we keep getting more impressive emergent behaviors from it? I doubt that I feel like putting the word 'forever' ruins the point. It's the most extreme strawman. It's amazing how the scaling has unlocked the emergent behaviors! When I look at the scaling graphs, I see that the ability to reduce 'perplexity' is continuing with scale and capital investment with no sign of slowing yet (it will slow eventually). I also see that reducing perplexity is continually unlocking new emergent behaviors. So I would guess that scaling will probably unlock so many more new emergent behaviors before it eventually plateaus!
llamaLord 4y ago
IMO, the capabilities have not improved that much between GPT-3 vs GPT-4, the primary difference is just in the size of the context the model can handle at any one time (Max tokens). While I definitely get "longer" and slightly more "in-depth" answers from GPT-4 vs 3, it already feels like that capability growth curve is starting to plateau.
- ftxbro 4y ago
  > IMO, the capabilities have not improved that much between GPT-3 vs GPT-4 I strongly disagree. Anyone who wants to look for themself can see the GPT 4 technical report. https://arxiv.org/pdf/2303.08774.pdf https://arxiv.org/pdf/2303.08774.pdf
  - CamperBob2 4y ago
    Page 9 pretty much stopped me dead in my tracks. There's no shortage of humans, even technically-savvy ones, who wouldn't answer that question correctly.
    - rashkov 4y ago
      That is incredibly impressive. Reminds me of these other examples from Microsoft’s “sparks of AGI” paper (summary link): https://ibragimov.org/2023/03/24/sparks-of-agi.html https://ibragimov.org/2023/03/24/sparks-of-agi.html
- vidarh 4y ago
  The distinction may appear subtle in many cases, but in others GPT4 blows 3 away. E.g. recognizing when it doesn't know and admitting it's hypothesising is something I've run into with 4 but not even 3.5. The capability curve will necessarily appear to plateau when the starting point is as good as it is now. The improvements we recognize will be subtler. Halving the remaining error rate will look less impressive for each step.
  - joe_the_user 4y ago
    It depends how you see good. The capacities of Gpt-3.5/ChatGPT not close to perfect. ChatGPT is quite good at something like "putting together facts using logic". Things medical diagnosis or legal argument. However, if the activity is "reconciling a summary with details", ChatGPT is pretty reliably terrible. My general recipe is "ask for a summary of a work of fiction, then ask about the relationship of the summary to details you know in the work." The thing reliably spits out falsehood in this situation.

gitfan86 4y ago

That debate is becoming irrelevant. Sure it would be great if GTP-6 cost 50k to train instead of 100M. But even if costs 100M it will produce many billions of dollars of value, so the original investment is still relatively small.

scrollaway 4y ago
Yeah but the difference between those two numbers is one is accessible to individuals (albeit wealthy ones), the other is accessible only to large-ish companies.

ftxbro 4y ago

> Will that continue forever and we keep getting more impressive emergent behaviors from it? I doubt that I feel like putting the word 'forever' ruins the point. It's the most extreme strawman. It's amazing how the scaling has unlocked the emergent behaviors! When I look at the scaling graphs, I see that the ability to reduce 'perplexity' is continuing with scale and capital investment with no sign of slowing yet (it will slow eventually). I also see that reducing perplexity is continually unlocking new emergent behaviors. So I would guess that scaling will probably unlock so many more new emergent behaviors before it eventually plateaus!

llamaLord 4y ago

IMO, the capabilities have not improved that much between GPT-3 vs GPT-4, the primary difference is just in the size of the context the model can handle at any one time (Max tokens). While I definitely get "longer" and slightly more "in-depth" answers from GPT-4 vs 3, it already feels like that capability growth curve is starting to plateau.

ftxbro 4y ago
> IMO, the capabilities have not improved that much between GPT-3 vs GPT-4 I strongly disagree. Anyone who wants to look for themself can see the GPT 4 technical report. https://arxiv.org/pdf/2303.08774.pdf https://arxiv.org/pdf/2303.08774.pdf
- CamperBob2 4y ago
  Page 9 pretty much stopped me dead in my tracks. There's no shortage of humans, even technically-savvy ones, who wouldn't answer that question correctly.
  - rashkov 4y ago
    That is incredibly impressive. Reminds me of these other examples from Microsoft’s “sparks of AGI” paper (summary link): https://ibragimov.org/2023/03/24/sparks-of-agi.html https://ibragimov.org/2023/03/24/sparks-of-agi.html
vidarh 4y ago
The distinction may appear subtle in many cases, but in others GPT4 blows 3 away. E.g. recognizing when it doesn't know and admitting it's hypothesising is something I've run into with 4 but not even 3.5. The capability curve will necessarily appear to plateau when the starting point is as good as it is now. The improvements we recognize will be subtler. Halving the remaining error rate will look less impressive for each step.
- joe_the_user 4y ago
  It depends how you see good. The capacities of Gpt-3.5/ChatGPT not close to perfect. ChatGPT is quite good at something like "putting together facts using logic". Things medical diagnosis or legal argument. However, if the activity is "reconciling a summary with details", ChatGPT is pretty reliably terrible. My general recipe is "ask for a summary of a work of fiction, then ask about the relationship of the summary to details you know in the work." The thing reliably spits out falsehood in this situation.