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We are only not executing the same task because GPT-3 has no motivation to do anything else than memory recall. And precisely because it does so it does give yo

by tinco 4y ago

We are only not executing the same task because GPT-3 has no motivation to do anything else than memory recall. And precisely because it does so it does give you real data about the world. I think you maybe misunderstood what GPT-3 can do, maybe you haven't played with it yourself. It not only bases the answer on information in its training set, but also on information in the question. So if you in your question give it all the information that is relevant (interspersed with irrelevant information if you want) then it will respond with its best interpretation of the information it is given, just like a human would. Treat GPT-3 like someone who just awoke from a long sleep. You could give it today's newspaper to read, and then ask it questions about today. Tell it what its own personal experience was, and then it'll talk your ears off about it if you ask nicely. It is clearly executing the same task if you disregard humans tendency to prioritize other motivations than pure memory recall.

sweezyjeezy 4y ago
> it will respond with its best interpretation of the information it is given, just like a human would The reason I can respond to this reply is not because I have read and memorised reams of text of people talking about AI and am simply regurgitating it mindlessly. I am able to do it because I can consider the points you are making, and what their actual 'meaning' is, try to come up with my own meaningful response and try to verbalise it back to you. There is a point where I am not just doing statistical language modelling. If you think that is wrong, and that what we are doing is closer to GPT-3, then could you explain why you think that? I am an AI researcher, and have spent plenty of time playing with GPT-3 btw.
- tinco 4y ago
  Right for sure, I'm just trying to get to a better argument. I definitely agree that there's a great deal more consideration in your comment than in one that GPT-3 would come up with. I do wonder how far these language models can be pushed. GPT-3 seems to formulate rich models of reality to be able to extract/derive information needed to construct these answers. When I hurt your pride by suggesting you haven't fully understood GPT-3, you are motivated to come up with not just a valid response, but one that has been vetted by as many of your well developed models that form your understanding of GPT-3 so I can be suitably impressed. I'm with you that GPT-3 wouldn't go deeper than just finding some information that it thinks it's true. Though maybe GPT-3 would recognise their authority was being challenged and add that line to affirm their credentials as an AI researcher. What if GPT-3 were pushed in a similar manner, perhaps in some adversarial scheme, to not only produce information that is correct, but that is clever and exploring deep meaning, motivated by some similar feeling of pride or vindication. I think the models required to do that do not lie far from the models it needed to build to form sentences that accurately describe reality.
  - sweezyjeezy 4y ago
    Haha interesting idea - I certainly think that one issue with supervised training a la GPT is that if you ask for an opinion, the most popular one in the training data will be its default. You can start a prompt off going in a different direction, and now it says the opposite. So it's hard to conceptualise what GPT-3 actually 'believes' to be true about the world, which I feel an agent must have to be sentient. If it has all opinions stored in its memory, surely it has no belief about anything? I feel like I am capable of making a concrete decision about whether I agree with two opposing ideas in a way that a language model can't do, such as this discussion. Furthermore my belief is consistent in my outputs day to day until my mind is changed by something. If that i some complete illusion and I am just a slightly fancier autocomplete than GPT-3 - well I'd be surprised, but I can't claim to understand consciousness well enough to refute it.
    - skjoldr 4y ago
      The only real difference between what you are describing and GPT-3 is that your dataset from which you draw all your opinions about the world is unique and comes from the sensory input you had experienced in your life, stored directly in memory. Whereas GPT-3's dataset comes from slices of many other peoples' sensory experiences, stored in language. If it was possible for a single human to produce enough words that describe their own experience to rival the volume of GPT-3's dataset, then it would be possible to train a model that would essentially "hold" that person's opinions. But I don't think such consistency is required for intelligence. It is simply arguing that an intelligent being must only experience the world at a single point in space, at a time, while this kind of AI takes in the data about experiences that happened in many different points in space at many different times. It seems kinda arbitrary. What if AR tech develops to the point where you can experience "being" in other point in space through artificial sensors (say, on a robotic or drone chassis), while also being able to see and hear your real surroundings to some degree? Then you will be able to experience the same real event from multiple vantage points. Will you be able to form two different opinions on what "really" happened? Which one would be the "correct" one?
      - 4y ago
- int_19h 4y ago
  Now we just need to define "consider" and "meaningful".
tsimionescu 4y ago
> So if you in your question give it all the information that is relevant (interspersed with irrelevant information if you want) then it will respond with its best interpretation of the information it is given, just like a human would. I don't think that's actually true, as GPT-3 will tend to ignore any facts about the world that were part of its corpus just to fit a question better. For example, if you prompt it with "Who assassinated Queen Elizabeth II?", it will likely give you a name, instead of saying "Queen Elizabeth II is still alive", because "Who" questions are much more likely to receive a name as an answer than a refutation in its training corpus.
- tinco 4y ago
  I wonder how many examples it would need to respond with "hah, trick question!". I wonder how it would do if you managed to frame the question more neutrally. To be fair you might trick a 7 year old into responding with a fantasy answer as well. I tried to get GPT-3 to tell me the most popular forums on some topics, and I noticed it would never include subreddits. So I prefaced my question with "given that subreddits are also a type of forum.." and it would give me a list that would include subreddits. I have to admit that in that new list it would then fail to mention some forum that was in the previous list, so it didn't have a super reliable ability reorganize information.
- Joeri 4y ago
  Anyone who has ever spoken to a small child knows they often “think” in the same way. They are likely to answer a who question with a name, sometimes laughably made up, because this is what they think they’re supposed to do and they lack the higher order reasoning to think it through. They also will continually forget things they already know when it suits their purpose. But nobody would say a toddler is not sentient.
  - tsimionescu 4y ago
    Sure, sentience doesn't require the inability to make mistakes. But a child will eventually learn that some questions are wrong and can be challenged. They are very likely to quickly learn this when it applies to themselves (if you ask "why did you break that toy?", I very much doubt they will answer with some reason, especially if they did not break the toy). The fact that they can chose to omit facts when it suits their purpose is in fact something that LaMDA can't do (as its sole purpose is to generate the most likely series of tokens that continue the prompt).

by tinco 4y ago

sweezyjeezy 4y ago

> it will respond with its best interpretation of the information it is given, just like a human would The reason I can respond to this reply is not because I have read and memorised reams of text of people talking about AI and am simply regurgitating it mindlessly. I am able to do it because I can consider the points you are making, and what their actual 'meaning' is, try to come up with my own meaningful response and try to verbalise it back to you. There is a point where I am not just doing statistical language modelling. If you think that is wrong, and that what we are doing is closer to GPT-3, then could you explain why you think that? I am an AI researcher, and have spent plenty of time playing with GPT-3 btw.

tinco 4y ago
Right for sure, I'm just trying to get to a better argument. I definitely agree that there's a great deal more consideration in your comment than in one that GPT-3 would come up with. I do wonder how far these language models can be pushed. GPT-3 seems to formulate rich models of reality to be able to extract/derive information needed to construct these answers. When I hurt your pride by suggesting you haven't fully understood GPT-3, you are motivated to come up with not just a valid response, but one that has been vetted by as many of your well developed models that form your understanding of GPT-3 so I can be suitably impressed. I'm with you that GPT-3 wouldn't go deeper than just finding some information that it thinks it's true. Though maybe GPT-3 would recognise their authority was being challenged and add that line to affirm their credentials as an AI researcher. What if GPT-3 were pushed in a similar manner, perhaps in some adversarial scheme, to not only produce information that is correct, but that is clever and exploring deep meaning, motivated by some similar feeling of pride or vindication. I think the models required to do that do not lie far from the models it needed to build to form sentences that accurately describe reality.
- sweezyjeezy 4y ago
  Haha interesting idea - I certainly think that one issue with supervised training a la GPT is that if you ask for an opinion, the most popular one in the training data will be its default. You can start a prompt off going in a different direction, and now it says the opposite. So it's hard to conceptualise what GPT-3 actually 'believes' to be true about the world, which I feel an agent must have to be sentient. If it has all opinions stored in its memory, surely it has no belief about anything? I feel like I am capable of making a concrete decision about whether I agree with two opposing ideas in a way that a language model can't do, such as this discussion. Furthermore my belief is consistent in my outputs day to day until my mind is changed by something. If that i some complete illusion and I am just a slightly fancier autocomplete than GPT-3 - well I'd be surprised, but I can't claim to understand consciousness well enough to refute it.
  - skjoldr 4y ago
    The only real difference between what you are describing and GPT-3 is that your dataset from which you draw all your opinions about the world is unique and comes from the sensory input you had experienced in your life, stored directly in memory. Whereas GPT-3's dataset comes from slices of many other peoples' sensory experiences, stored in language. If it was possible for a single human to produce enough words that describe their own experience to rival the volume of GPT-3's dataset, then it would be possible to train a model that would essentially "hold" that person's opinions. But I don't think such consistency is required for intelligence. It is simply arguing that an intelligent being must only experience the world at a single point in space, at a time, while this kind of AI takes in the data about experiences that happened in many different points in space at many different times. It seems kinda arbitrary. What if AR tech develops to the point where you can experience "being" in other point in space through artificial sensors (say, on a robotic or drone chassis), while also being able to see and hear your real surroundings to some degree? Then you will be able to experience the same real event from multiple vantage points. Will you be able to form two different opinions on what "really" happened? Which one would be the "correct" one?
    - 4y ago
int_19h 4y ago
Now we just need to define "consider" and "meaningful".

tsimionescu 4y ago

> So if you in your question give it all the information that is relevant (interspersed with irrelevant information if you want) then it will respond with its best interpretation of the information it is given, just like a human would. I don't think that's actually true, as GPT-3 will tend to ignore any facts about the world that were part of its corpus just to fit a question better. For example, if you prompt it with "Who assassinated Queen Elizabeth II?", it will likely give you a name, instead of saying "Queen Elizabeth II is still alive", because "Who" questions are much more likely to receive a name as an answer than a refutation in its training corpus.

tinco 4y ago
I wonder how many examples it would need to respond with "hah, trick question!". I wonder how it would do if you managed to frame the question more neutrally. To be fair you might trick a 7 year old into responding with a fantasy answer as well. I tried to get GPT-3 to tell me the most popular forums on some topics, and I noticed it would never include subreddits. So I prefaced my question with "given that subreddits are also a type of forum.." and it would give me a list that would include subreddits. I have to admit that in that new list it would then fail to mention some forum that was in the previous list, so it didn't have a super reliable ability reorganize information.
Joeri 4y ago
Anyone who has ever spoken to a small child knows they often “think” in the same way. They are likely to answer a who question with a name, sometimes laughably made up, because this is what they think they’re supposed to do and they lack the higher order reasoning to think it through. They also will continually forget things they already know when it suits their purpose. But nobody would say a toddler is not sentient.
- tsimionescu 4y ago
  Sure, sentience doesn't require the inability to make mistakes. But a child will eventually learn that some questions are wrong and can be challenged. They are very likely to quickly learn this when it applies to themselves (if you ask "why did you break that toy?", I very much doubt they will answer with some reason, especially if they did not break the toy). The fact that they can chose to omit facts when it suits their purpose is in fact something that LaMDA can't do (as its sole purpose is to generate the most likely series of tokens that continue the prompt).