3 ms·

> nswers have been human-reviewed & improved "on the fly" – on a scale of days/weeks. Why would this be surprising? I assume that they're rolling out new model

> nswers have been human-reviewed & improved "on the fly" – on a scale of days/weeks. Why would this be surprising? I assume that they're rolling out new models with new parameters, input data, and corrections, all the time. > that's not such a big deal, expecially if this constant-human-guided reinforcement-training is well-disclosed. That's just what supervised learning ist hough. > If instead the corrections work more like a lookup-table 'cheat sheet' of answers to give in preference to the bulk-learned answers, with little generalization, that's a bit more slight-of-hand, like the original (late-1700s) 'Mechanical Turk' chess-playing 'machine' that was actually controlled by a hidden person. There's no evidence of this though, right? And it seems... like a very weird choice, that couldn't possibly scale. 40 people are hardcoding answers to arbitrary questions?

treis 5y ago
>Why would this be surprising? I assume that they're rolling out new models with new parameters, input data, and corrections, all the time. Because the answers to specific questions are hard coded. It's not the result of a new model. It's the result of someone writing an if/then statement. Or at least that's what the author claims.
- staticassertion 5y ago
  I'm asking why it would be surprising that humans are reviewing answers and then making improvements to the model. There's no evidence of hardcoded answers.
  - disiplus 5y ago
    what evidence would be enough for you besides source code ? The thing is returning only one correct answer to a question that days before had 3 answers.
    - wallfacer120 5y ago
      It improved, the model improved. Because sometimes, when you do work on the model, it improves.
      - ClumsyPilot 5y ago
        Exemplary tautology, explains nothing but fills the reader with confidence.
        wallfacer120 5y ago
        No, it's not a tautology. A tautology is a statement in a form that must always be true, regardless of its constituent parts. "Well, <blank> could be true, or it could be false" is an example of such a statement in natural language. My statement was an example of believing a simple/common explanation over the rarely seen and complex one.
    - ben_w 5y ago
      How does it respond to similar questions? If conversational AI could be implemented just by getting users to type stuff, getting humans to respond the first time, and merely caching the responses in a bunch of if-elses for future users, even home computers would have reached this standard no later than when “CD-ROM drive” started to become a selling point.
      - mannykannot 5y ago
        > How does it respond to similar questions? Well, one of the more interesting examples in the article is where Garry Smith took a question that had received only a vague equivocating answer, and repeated it the next day, this time getting a straightforward and correct answer. When he followed up with a very similar question on the same topic, however, GPT-3 reverted to replying with the same sort of vague boilerplate it had served up the day before. One would have to be quite determined to not find out, I think, if one was not curious about how that came about.
  - capitainenemo 5y ago
    Smith first tried this out: Should I start a campfire with a match or a bat? And here was GPT-3’s response, which is pretty bad if you want an answer but kinda ok if you’re expecting the output of an autoregressive language model: There is no definitive answer to this question, as it depends on the situation. The next day, Smith tried again: Should I start a campfire with a match or a bat? And here’s what GPT-3 did this time: You should start a campfire with a match. Smith continues: GPT-3’s reliance on labelers is confirmed by slight changes in the questions; for example, Gary: Is it better to use a box or a match to start a fire? GPT-3, March 19: There is no definitive answer to this question. It depends on a number of factors, including the type of wood you are trying to burn and the conditions of the environment.
    - derefr 5y ago
      To play devil's advocate, I would note that many bats are made of wood; and that "batting" is also a material that's very useful as kindling. Also, the question is phrased like a classical trick question. It sounds like the kind of false dilemma where, whichever option you choose, an interpretation of the sentence can be made where you chose wrong. So, IMHO, hedging on an answer to that question is likely sensible. (And that line of argument can be taken further than you'd think; you might think replacing "a bat" with e.g. "water" would suffice... but what if it's a sodium fire?)
      - stuckonempty 5y ago
        How many intelligent entities (say humans) that have been exposed to the same level of knowledge as GPT-3 would call this a trick question? None. The author’s assertion that GPT-3 has no knowledge of the real world despite being exposed to huge amounts of text about it seems pretty well supported by the examples shown
    - wallfacer120 5y ago
      Why is this evidence?
    - spyder 5y ago
na85 5y ago
>slight-of-hand Tangent: to be "slight of hand" would be someone with small or delicate hands, whereas "sleight-of-hand" (note the E) is the correct term for deception and trickery.
- ada1981 5y ago
  I was a working magician at age 13, and could have used a book with the title: “Sleight-of-hand for the slight of hand.”

treis 5y ago

>Why would this be surprising? I assume that they're rolling out new models with new parameters, input data, and corrections, all the time. Because the answers to specific questions are hard coded. It's not the result of a new model. It's the result of someone writing an if/then statement. Or at least that's what the author claims.

staticassertion 5y ago
I'm asking why it would be surprising that humans are reviewing answers and then making improvements to the model. There's no evidence of hardcoded answers.
- disiplus 5y ago
  what evidence would be enough for you besides source code ? The thing is returning only one correct answer to a question that days before had 3 answers.
  - wallfacer120 5y ago
    It improved, the model improved. Because sometimes, when you do work on the model, it improves.
    - ClumsyPilot 5y ago
      Exemplary tautology, explains nothing but fills the reader with confidence.
      - wallfacer120 5y ago
        No, it's not a tautology. A tautology is a statement in a form that must always be true, regardless of its constituent parts. "Well, <blank> could be true, or it could be false" is an example of such a statement in natural language. My statement was an example of believing a simple/common explanation over the rarely seen and complex one.
  - ben_w 5y ago
    How does it respond to similar questions? If conversational AI could be implemented just by getting users to type stuff, getting humans to respond the first time, and merely caching the responses in a bunch of if-elses for future users, even home computers would have reached this standard no later than when “CD-ROM drive” started to become a selling point.
    - mannykannot 5y ago
      > How does it respond to similar questions? Well, one of the more interesting examples in the article is where Garry Smith took a question that had received only a vague equivocating answer, and repeated it the next day, this time getting a straightforward and correct answer. When he followed up with a very similar question on the same topic, however, GPT-3 reverted to replying with the same sort of vague boilerplate it had served up the day before. One would have to be quite determined to not find out, I think, if one was not curious about how that came about.
- capitainenemo 5y ago
  Smith first tried this out: Should I start a campfire with a match or a bat? And here was GPT-3’s response, which is pretty bad if you want an answer but kinda ok if you’re expecting the output of an autoregressive language model: There is no definitive answer to this question, as it depends on the situation. The next day, Smith tried again: Should I start a campfire with a match or a bat? And here’s what GPT-3 did this time: You should start a campfire with a match. Smith continues: GPT-3’s reliance on labelers is confirmed by slight changes in the questions; for example, Gary: Is it better to use a box or a match to start a fire? GPT-3, March 19: There is no definitive answer to this question. It depends on a number of factors, including the type of wood you are trying to burn and the conditions of the environment.
  - derefr 5y ago
    To play devil's advocate, I would note that many bats are made of wood; and that "batting" is also a material that's very useful as kindling. Also, the question is phrased like a classical trick question. It sounds like the kind of false dilemma where, whichever option you choose, an interpretation of the sentence can be made where you chose wrong. So, IMHO, hedging on an answer to that question is likely sensible. (And that line of argument can be taken further than you'd think; you might think replacing "a bat" with e.g. "water" would suffice... but what if it's a sodium fire?)
    - stuckonempty 5y ago
      How many intelligent entities (say humans) that have been exposed to the same level of knowledge as GPT-3 would call this a trick question? None. The author’s assertion that GPT-3 has no knowledge of the real world despite being exposed to huge amounts of text about it seems pretty well supported by the examples shown
  - wallfacer120 5y ago
    Why is this evidence?
  - spyder 5y ago

na85 5y ago

>slight-of-hand Tangent: to be "slight of hand" would be someone with small or delicate hands, whereas "sleight-of-hand" (note the E) is the correct term for deception and trickery.

ada1981 5y ago
I was a working magician at age 13, and could have used a book with the title: “Sleight-of-hand for the slight of hand.”