4 ms·

We need models that can read long texts like a bunch of scientific papers, a book, or the whole git repo of an app. And we need models that can do iterative cha

We need models that can read long texts like a bunch of scientific papers, a book, or the whole git repo of an app. And we need models that can do iterative changes - diff models, they can be trained of course on git commits.

kgarten 4y ago
the models we have today will never be able to read .. they are just able to produce something that we cannot distinguish from human output. we should be more careful on how we use them. in my opinion, ChatGPT and similar will be horrible for search on the web, as we are flooded with text that looks like a human wrote it but it does not add any knowledge or new insight.
- hybridity 4y ago
  When I give ChatGPT a piece of literature or code that it has never seen before, it is able to analyze it and respond back at least semi-intelligibly. This would make me conclude that the models we have today can in fact read, and typically rather well.
  - humanistbot 4y ago
    That is because it has seen literature or code that is syntactically similar enough to what you give it, so that it can autocomplete its way to a semi-intelligent response.
- babyshake 4y ago
  This line of thought always brings to mind the "mission accomplished" XKCD: https://xkcd.com/810/ https://xkcd.com/810/
- gitgud 4y ago
  > the models we have today will never be able to read .. Never say never
  - humanistbot 4y ago
    > Never say never When we are talking about THE MODELS WE HAVE TODAY, then yes, we can say never.
- barking_biscuit 4y ago
  >the models we have today will never be able to read They already do read.
  - kgarten 4y ago
    Then we have a different definition of reading. To read means to understand and comprehend for me.
    - barking_biscuit 4y ago
      Then we have a different definition of understanding. A good half of these debates come down to definitions at this point. To me, ChatGPT clearly displays degrees of understanding. Often when I ask it to do things like make a certain modification to a piece of code, I'll ask it "why did you choose to do it like that?" and it gives a coherent explanation. That it correctly did what I asked and that it's explanation of why it did that way comport with one another implies understanding in my view. How could it not? What else would that imply? And if I ask a human to do the same thing and get the same result you'd have no problem with saying "well it's able to do that because it understands, and if it didn't understand then it would have zero capability of doing that". So, what's with the double standard?
      - kgarten 4y ago
        Yes, as I said we have different definitions. For me, it's matrix multiplications on data made to output things that are approximations to what a human has written before on that question or text you're prompting it. I know how training a deep neural network works and there's no reading involved for me :) It's just estimating what a person would write (being trained on a really large data set of what people wrote). If it's trained on gibberish, it will just output gibberish. If I ask you to read a book with gibberish words would you do it? ChatGPT would (according to you) "read it" and recite the gibberish I gave it without a problem. The matrix multiplications used to build these models don't show any comprehension, agency, or consciousness. Their point is to estimate the next data point given the previous data point, they will perform the same task independent from which training data we give them. That's not reading. I don't say this might not change in the future, yet treating ChatGPT like a human using words like "reading," "understanding" etc. or intelligence for that matter is just anthropomorphizing for me.
zitterbewegung 4y ago
Right now chatgpt employs humans to correct itself by tagging incorrect responses. Chatgpt has ingested paper or book and git repos.
- visarga 4y ago
  It doesn't memorize training data except for very repetitive bits. It needs a fresh copy of the paper in the prompt but only 10% fits.
  - sebzim4500 4y ago
    Making the context 10x longer would 'only' cost about 100x as much compute. Presumably you could take GPT-3 (trained with the normal context) and then finetune it on a comparitively small amount of data with the new context length, so it shouldn't be enormously expensive to train either. Would be interesting to see how well it could 'understand' a paper, or if more layers etc. would be needed.
    - visarga 4y ago
      Well, it depends. Perceiver can handle big context. https://arxiv.org/abs/2103.03206 https://arxiv.org/abs/2103.03206
Gigachad 4y ago
It would be expensive but probably worth it. Most companies would pay hundreds to have an AI model scan their whole codebase and be able to answer questions about it.

kgarten 4y ago

the models we have today will never be able to read .. they are just able to produce something that we cannot distinguish from human output. we should be more careful on how we use them. in my opinion, ChatGPT and similar will be horrible for search on the web, as we are flooded with text that looks like a human wrote it but it does not add any knowledge or new insight.

hybridity 4y ago
When I give ChatGPT a piece of literature or code that it has never seen before, it is able to analyze it and respond back at least semi-intelligibly. This would make me conclude that the models we have today can in fact read, and typically rather well.
- humanistbot 4y ago
  That is because it has seen literature or code that is syntactically similar enough to what you give it, so that it can autocomplete its way to a semi-intelligent response.
babyshake 4y ago
This line of thought always brings to mind the "mission accomplished" XKCD: https://xkcd.com/810/ https://xkcd.com/810/
gitgud 4y ago
> the models we have today will never be able to read .. Never say never
- humanistbot 4y ago
  > Never say never When we are talking about THE MODELS WE HAVE TODAY, then yes, we can say never.
barking_biscuit 4y ago
>the models we have today will never be able to read They already do read.
- kgarten 4y ago
  Then we have a different definition of reading. To read means to understand and comprehend for me.
  - barking_biscuit 4y ago
    Then we have a different definition of understanding. A good half of these debates come down to definitions at this point. To me, ChatGPT clearly displays degrees of understanding. Often when I ask it to do things like make a certain modification to a piece of code, I'll ask it "why did you choose to do it like that?" and it gives a coherent explanation. That it correctly did what I asked and that it's explanation of why it did that way comport with one another implies understanding in my view. How could it not? What else would that imply? And if I ask a human to do the same thing and get the same result you'd have no problem with saying "well it's able to do that because it understands, and if it didn't understand then it would have zero capability of doing that". So, what's with the double standard?
    - kgarten 4y ago
      Yes, as I said we have different definitions. For me, it's matrix multiplications on data made to output things that are approximations to what a human has written before on that question or text you're prompting it. I know how training a deep neural network works and there's no reading involved for me :) It's just estimating what a person would write (being trained on a really large data set of what people wrote). If it's trained on gibberish, it will just output gibberish. If I ask you to read a book with gibberish words would you do it? ChatGPT would (according to you) "read it" and recite the gibberish I gave it without a problem. The matrix multiplications used to build these models don't show any comprehension, agency, or consciousness. Their point is to estimate the next data point given the previous data point, they will perform the same task independent from which training data we give them. That's not reading. I don't say this might not change in the future, yet treating ChatGPT like a human using words like "reading," "understanding" etc. or intelligence for that matter is just anthropomorphizing for me.

zitterbewegung 4y ago

Right now chatgpt employs humans to correct itself by tagging incorrect responses. Chatgpt has ingested paper or book and git repos.

visarga 4y ago
It doesn't memorize training data except for very repetitive bits. It needs a fresh copy of the paper in the prompt but only 10% fits.
- sebzim4500 4y ago
  Making the context 10x longer would 'only' cost about 100x as much compute. Presumably you could take GPT-3 (trained with the normal context) and then finetune it on a comparitively small amount of data with the new context length, so it shouldn't be enormously expensive to train either. Would be interesting to see how well it could 'understand' a paper, or if more layers etc. would be needed.
  - visarga 4y ago
    Well, it depends. Perceiver can handle big context. https://arxiv.org/abs/2103.03206 https://arxiv.org/abs/2103.03206

Gigachad 4y ago

It would be expensive but probably worth it. Most companies would pay hundreds to have an AI model scan their whole codebase and be able to answer questions about it.