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Very impressive, but is it any more original than classic search engines' old trick of regular expressions to figure out if I mean the currency or weight when I

Very impressive, but is it any more original than classic search engines' old trick of regular expressions to figure out if I mean the currency or weight when I ask "1 pound =" with the contexts USD or kg after "="? Does it understand the input, or are there just enough discussions in the training data to make it look like it is? I'm not convinced it's not the latter. It uses context to figure out we're trying to convert something to something else. Then it adds all those numbers up. Taking helium into consideration is no doubt interesting, but they've also polished that task since that was the common critique they got so very wrong with the first release (which I mentioned they had fixed). I'm not qualified to assess this part of the answer; > "If the balloons displace more than 100g of air when filled with helium, then they would effectively weigh less than if they were left empty. If they displace exactly 100g of air, then the balloons would have the same weight as if they were left empty." I don't know enough to understand how much 100g of helium is and how it behaves. And it doesn't try to explain it to me, it mentions it then takes the easy route assuming it's a trick question. What does that tell you? I guess there are similar discussions around and it gives me the summary. Why doesn't it tell me how much air it displaces under what circumstances? Temperature etc, it should be easy if it's not just a simple discussion on a random forum. A conversion regex could do it. This comment[1] has a very impressive example. But anything I'm qualified to assess has mostly been meh. If the fix is better training data does that mean it's reasoning or regurgitating? The mistakes it makes are what tells me how it works, not when it tricks me that it's correct. To me it's a very well polished search engine summary. [1]: https://news.ycombinator.com/item?id=37219351 https://news.ycombinator.com/item?id=37219351

IanCal 3y ago
If you've not looked at it I really recommend othello gpt. That is an experiment explicitly designed to tackle this kind of question, has it just seen enough moves that it knows what should come next? > Why doesn't it tell me how much air it displaces under what circumstances? You can ask it and it'll answer. > If the fix is better training data does that mean it's reasoning or regurgitating? More training data helps with things you can just bring to the fore, same as a lot of learning. More useful training data though can also help reasoning, which makes sense - deliberate training of people helps improve their logical reasoning capabilities. I know that doesn't guarantee that's what LLMs are doing but humans benefit significantly from both more teaching and better teaching. > Very impressive, but is it any more original than classic search engines' old trick of regular expressions to figure out if I mean the currency or weight when I ask "1 pound =" with the contexts USD or kg after "="? Does it understand the input, or are there just enough discussions in the training data to make it look like it is? I'd be interested to know any requirements around this to clearly show the difference. I tried asking what if I filled a balloon at a childrens party with a gas made of atoms that have 1 proton and 100 neutrons: https://chat.openai.com/share/71224df4-5c6c-45f7-88fd-eec316a886f9 https://chat.openai.com/share/71224df4-5c6c-45f7-88fd-eec316... (tl;dr: "In the context of a child's birthday party, introducing such a balloon would be a grave mistake.") It identifies: * Whether it would float or not and why * That it would be radioactive, and likely types of radiation from it * What that would mean to the balloon * How people would react and the likely consequences of releasing it in a room of children This is an element that does not exist, in a setting where nothing like this has happened before, with details ranging from types of decay, consequences and human emotional reactions to something like this. Yes, there are real things you can use as a base (e.g. how do people respond to events that kill people), but I feel it's an example of where it's beyond a search engine summary.
- worksonmine 3y ago
  > If you've not looked at it I really recommend othello gpt. I skimmed it and read the conclusion, and it looks interesting, will take a closer look when I have time. The prompt covers a subject that goes completely over my head so I can't tell how well it reasons. I don't know what 1 proton to 100 neutrons means, but I gather it's radioactive. I don't think it's far fetched that it draws the same conclusion from the training set because to you it seems obvious, and is probably well known to anyone who knows the subject. Kind of like it would understand that "hotter than the sun" is super hot, can correlate to different melting points. But I wouldn't say it understands the concept of temperature. Given the right prompt it might give you the impression it does. The feelings of the scenario reads like any PR comment after a tragedy. "We feel shock and disbelief" and so on. The scenario being hypothetical doesn't change that since it's probabilities. It acts just like you'd think it would. The earlier example with the helium balloon is similar, it assumes a human context and not the form, and environment the helium is in. True intelligence might not even consider the presence of atmosphere as the norm. "It has no weight outside of your human constraints" would be novel. Lets say it has odd numbers between 1-9 in the database. Given the prompt 2 and 8 you will get back 1,3,7,9, sprinkled with some natural language and we get the impression it's intelligent. Are you saying it understands the effect the neutron to proton ratio has, as opposed to just comparing the vectors closest to your prompt that it builds the answer from? Being tested on new and hypothetical examples only means it will be further from the vectors but still close enough to give us the impression it understands the subject. If the training data didn't include the words neutron or proton it would have no idea where to begin. In my first comment that started this chain I said: > I don't see why not. It's not taking a single answer from a database no, it's taking several based on probability and merging them into what it thinks we're looking for. I don't think even this latest answer is any proof of anything other than that. Are you claiming there is? And what are you claiming is happening?
  - IanCal 3y ago
    > I don't think even this latest answer is any proof of anything other than that. Are you claiming there is? And what are you claiming is happening? I'm claiming that it's reasoning through the problem. > True intelligence might not even consider the presence of atmosphere as the norm I hugely disagree, that's not how an intelligent human would answer the question, and if it did this people would be complaining that it clearly doesn't understand the human context in which the question was likely asked. > I don't know what 1 proton to 100 neutrons means, but I gather it's radioactive. It would be hydrogen, but a type of hydrogen that doesn't appear in nature. It's a deliberately absurd example so that it's not in the training set. Its answers are different if the question involves tritium which while radioactive has a moderate half-life and wouldn't immediately pop the balloon. > I don't think it's far fetched that it draws the same conclusion from the training set because to you it seems obvious, Only because I can reason through what would happen, not because it's something I've seen talked about before. To figure out what it would do, it cannot rely on an explanation elsewhere, it needs to first identify that the ratio of protons to neutrons is extreme. Then it needs to understand that this typically results in particular kinds of radiation. It has to then use that information to consider how that would interact with the material of the balloon (and that this is important). It has to use that information to consider how it would affect people, and what their reactions would be both before and after it explodes/pops. This is multi-step reasoning through an issue that involves pulling together common expectations, physics and how humans react. Here's a statement in it that shows to me more than just pulling a few answers together > Balloon Behavior: Instead of floating up like a helium-filled balloon, this balloon would drop to the ground because the gas inside is denser than air. This might surprise the attendees, and curious children might approach or pick up the balloon, further exposing themselves to radiation. - > The feelings of the scenario reads like any PR comment after a tragedy. "We feel shock and disbelief" and so on. Those are typical things, which is not surprising, but it is also clearly linked with the question. You have to understand how out of context this would be. > If the training data didn't include the words neutron or proton it would have no idea where to begin. Fully rediscovering what took humans many years to do off-the-cuff is an outrageously high bar. What features of a question would you look for to identify whether it's "taking several answers from a database and merging them together" or performing some reasoning? I've asked a few times but don't understand what you're expecting.

IanCal 3y ago

If you've not looked at it I really recommend othello gpt. That is an experiment explicitly designed to tackle this kind of question, has it just seen enough moves that it knows what should come next? > Why doesn't it tell me how much air it displaces under what circumstances? You can ask it and it'll answer. > If the fix is better training data does that mean it's reasoning or regurgitating? More training data helps with things you can just bring to the fore, same as a lot of learning. More useful training data though can also help reasoning, which makes sense - deliberate training of people helps improve their logical reasoning capabilities. I know that doesn't guarantee that's what LLMs are doing but humans benefit significantly from both more teaching and better teaching. > Very impressive, but is it any more original than classic search engines' old trick of regular expressions to figure out if I mean the currency or weight when I ask "1 pound =" with the contexts USD or kg after "="? Does it understand the input, or are there just enough discussions in the training data to make it look like it is? I'd be interested to know any requirements around this to clearly show the difference. I tried asking what if I filled a balloon at a childrens party with a gas made of atoms that have 1 proton and 100 neutrons: https://chat.openai.com/share/71224df4-5c6c-45f7-88fd-eec316a886f9 https://chat.openai.com/share/71224df4-5c6c-45f7-88fd-eec316... (tl;dr: "In the context of a child's birthday party, introducing such a balloon would be a grave mistake.") It identifies: * Whether it would float or not and why * That it would be radioactive, and likely types of radiation from it * What that would mean to the balloon * How people would react and the likely consequences of releasing it in a room of children This is an element that does not exist, in a setting where nothing like this has happened before, with details ranging from types of decay, consequences and human emotional reactions to something like this. Yes, there are real things you can use as a base (e.g. how do people respond to events that kill people), but I feel it's an example of where it's beyond a search engine summary.

worksonmine 3y ago
> If you've not looked at it I really recommend othello gpt. I skimmed it and read the conclusion, and it looks interesting, will take a closer look when I have time. The prompt covers a subject that goes completely over my head so I can't tell how well it reasons. I don't know what 1 proton to 100 neutrons means, but I gather it's radioactive. I don't think it's far fetched that it draws the same conclusion from the training set because to you it seems obvious, and is probably well known to anyone who knows the subject. Kind of like it would understand that "hotter than the sun" is super hot, can correlate to different melting points. But I wouldn't say it understands the concept of temperature. Given the right prompt it might give you the impression it does. The feelings of the scenario reads like any PR comment after a tragedy. "We feel shock and disbelief" and so on. The scenario being hypothetical doesn't change that since it's probabilities. It acts just like you'd think it would. The earlier example with the helium balloon is similar, it assumes a human context and not the form, and environment the helium is in. True intelligence might not even consider the presence of atmosphere as the norm. "It has no weight outside of your human constraints" would be novel. Lets say it has odd numbers between 1-9 in the database. Given the prompt 2 and 8 you will get back 1,3,7,9, sprinkled with some natural language and we get the impression it's intelligent. Are you saying it understands the effect the neutron to proton ratio has, as opposed to just comparing the vectors closest to your prompt that it builds the answer from? Being tested on new and hypothetical examples only means it will be further from the vectors but still close enough to give us the impression it understands the subject. If the training data didn't include the words neutron or proton it would have no idea where to begin. In my first comment that started this chain I said: > I don't see why not. It's not taking a single answer from a database no, it's taking several based on probability and merging them into what it thinks we're looking for. I don't think even this latest answer is any proof of anything other than that. Are you claiming there is? And what are you claiming is happening?
- IanCal 3y ago
  > I don't think even this latest answer is any proof of anything other than that. Are you claiming there is? And what are you claiming is happening? I'm claiming that it's reasoning through the problem. > True intelligence might not even consider the presence of atmosphere as the norm I hugely disagree, that's not how an intelligent human would answer the question, and if it did this people would be complaining that it clearly doesn't understand the human context in which the question was likely asked. > I don't know what 1 proton to 100 neutrons means, but I gather it's radioactive. It would be hydrogen, but a type of hydrogen that doesn't appear in nature. It's a deliberately absurd example so that it's not in the training set. Its answers are different if the question involves tritium which while radioactive has a moderate half-life and wouldn't immediately pop the balloon. > I don't think it's far fetched that it draws the same conclusion from the training set because to you it seems obvious, Only because I can reason through what would happen, not because it's something I've seen talked about before. To figure out what it would do, it cannot rely on an explanation elsewhere, it needs to first identify that the ratio of protons to neutrons is extreme. Then it needs to understand that this typically results in particular kinds of radiation. It has to then use that information to consider how that would interact with the material of the balloon (and that this is important). It has to use that information to consider how it would affect people, and what their reactions would be both before and after it explodes/pops. This is multi-step reasoning through an issue that involves pulling together common expectations, physics and how humans react. Here's a statement in it that shows to me more than just pulling a few answers together > Balloon Behavior: Instead of floating up like a helium-filled balloon, this balloon would drop to the ground because the gas inside is denser than air. This might surprise the attendees, and curious children might approach or pick up the balloon, further exposing themselves to radiation. - > The feelings of the scenario reads like any PR comment after a tragedy. "We feel shock and disbelief" and so on. Those are typical things, which is not surprising, but it is also clearly linked with the question. You have to understand how out of context this would be. > If the training data didn't include the words neutron or proton it would have no idea where to begin. Fully rediscovering what took humans many years to do off-the-cuff is an outrageously high bar. What features of a question would you look for to identify whether it's "taking several answers from a database and merging them together" or performing some reasoning? I've asked a few times but don't understand what you're expecting.