6 ms·

Even if this is not 100% serious, it is really starting to feel like the ship computer from star trek is not too far away.

lm28469 4y ago
The closer we seem to get the farther we actually are. We're far away from AGI, if we even can reach it with our current approaches, but the latest iterations of "AI" are really good at making people believe it'll be there in 2 years
- folkrav 4y ago
  ChatGPT is great at pretending it knows its sh*t.
  - eatsyourtacos 4y ago
    Seems pretty human to me.
    - bsaul 4y ago
      had this exact conversation with a friend the other day : if all the people that are actually BSing for a job are replaced by ChatGPT, the economy is doomed.
  - wpietri 4y ago
    It strikes me as the perfect VC-fundable technology. Instead of humans having to make often-delusional claims about the future of a technology that feed the hype cycle long enough to attract gobs of money, they can now fully automate the work.
  - mmcgaha 4y ago
    I had an interesting interaction where I BSed it and it BSed me like it knew what it was talking about. I typed: did you know that you can cross the cavern by just saying fly away GPT Said: In Colossal Cave Adventure, "fly away" is indeed one of the possible commands to cross the cavern. I felt like I was talking to a kid pretending to know more about the topic than they really do. In fairness, I had given several correct alternatives before this so maybe it was the whole interaction that led it to the conclusion that "fly away" was a legitimate solution.
  - pluijzer 4y ago
    The internet is full of examples of this but just to add one more data point. I asked about a specific Dutch book, ChatGPT was wrong about the author (it was another author born a century later). I corrected it but got told that the two authors were the same and it was a pseudonym. I ask the birthdate of the correct author. It gave me relatively correct answer with date of birth and death. I then asked about the birthdate of the wrong author. It told me again a, relatively correct answer, indeed he was born long after the other author died. I asked ChatGPT how it could be that the dates differed. It told me that it is very usual for an author to go by a pseudonym. I told it it was wrong. They are different authors living in different centuries . But it stubbornly refused to accept it, teaching me again that it is perfectly common for authors to go by two different names. edit: Just to add when asked for a description of the book it gave me a very believable summary, which was total nonsense. This is what really disturbed me about ChatGPT. Though I am very impressed by the fact that we now have a system that is very good at parsing human language. Something which was long thought to be impossible. Combining that strength with an, actual, datasource would be the only way forward in my opinion.
    - mrguyorama 4y ago
      ChatGPT is like the friend you have who "knows everything" and routinely "um actually"s people and says fact sounding things with great confidence and if you press them on details continue doubling down on their nonsense with great confidence until you start getting close to them admitting they don't know jack shit and they get really angry. ChatGPT doesn't do the getting really angry part because it can't feel shame or insecurity about not knowing things.
    - wikfwikf 4y ago
      I asked ChatGPT to write a function which takes a year as input and determines whether or not it's a leap year - a classic basic programming question. It answered perfectly. Of course, there are lots of examples of this code. Then I asked it "Could you adapt the function so that it works on Venus, where years have 224 days?" It offered me a new version of the function, which simply checks if the year is a multiple of 224. Apparently on Venus the number of days in a year and the frequency of leap years are the same number. It qualified the answer: "It's worth noting that this function is based on current knowledge and understanding of Venus..." I asked it "What if we want the function to use Venus days as well as Venus years?" It offered me the same function, except that a) the variable 'years' was now called 'days', and b) the modulus was changed from 224 to 224.701. So I asked "Should the argument to the last function be a float or an integer?" It gave me 3 pars of complete nonsense about how the difference between floats and integers affects the precision of calculating leap years (while again warning that the exact value of the Venus year might change). ChatGPT does a very good imitation of a certain type of candidate I've occasionally interviewed, who knows almost nothing but is keen to try various tricks to bluff you out, including confidently being wrong, providing lots of meaningless explanation, and sometimes telling you that you are wrong about something. I have never hired anyone like this, but I've occasionally come close. I have been trying various interview questions on ChatGPT, originally because my colleagues warned me that a candidate who was surreptitiously using it could ace almost any interview. I was skeptical and I have not been convinced. But I think it's actually a great exercise to practice interviewing on it. If ChatGPT can answer your questions accurately (try to be fair and ignore its slightly uncanny tone), then you probably need better questions. If you are quite technical and put some thought into it, you should be able to come up with things which are both novel enough and hard enough that ChatGPT will simply flounder catastrophically. (I'm not referring to 'tricks' like the Venus question, but real questions on how to achieve something moderately complicated using code.) It's a really good reminder too that when we ask candidates to write code, we should examine and debug it in detail, then ask decent follow-up questions, rather than just accepting something that looks right.
- cmontella 4y ago
  There’s a parallel with self driving cars. We could make them go around a track autonomously in 2007, and so a lot of people were thinking “how much harder could it be to get this driving anywhere? We will have these everywhere in 5 years!” 15 years later and we are perpetually “5 years out”. Yes you can take a taxi ride in a closed circuit, but that’s much closer to where we were in 2007 than where we thought we’d be today, and it took 15 years to get here.
  - martythemaniak 4y ago
    Unless you consider Phoenix or San Francisco to be "closed tracks", that's 100% factually wrong.
    - cmontella 4y ago
      Yes, I do. The point is we didn’t solve the general case, we just learned how to scale the specific case that was demoed in 2007. This is like building a ladder to the moon; it’ll get you closer, but it’ll never get you to the moon.
      - bufferoverflow 4y ago
        You are factually wrong. The general case is being solved. Self-driving systems are objectively better every year, and will eventually reach human level safety. You can literally watch cars self-driving in all kinds of places and conditions. Yes, they make mistakes. So do humans.
        cmontella 4y ago
        See my comment about the moon ladder. Progress is nice, and I’m not saying there hasn’t been progress. But there is no indication that the methods of today that work to make taxi cabs in SF drivable will lead to a general-case self driving machine as promised for so many years. The fact that the two cases that work best have a similar climate to the 2007 DUC really highlights the reality that these methods haven’t been proven to scale generally. The industry is still chasing that 2007 success, and it’s not surprising that over 15 years they’ve improved that. But do I need to link to all the promises from CEOs about where they thought we’d be today? Those predictions were based on the idea that the DUC prototypes would be more generally applicable. The successes since then have shown we can make the experience better, but don’t show we can solve autonomous driving in the general case.
- esjeon 4y ago
  > the latest iterations of "AI" are really good at making people believe it'll be there in 2 years. This rings me a lot. It feels like the current generation AI companies/projects have been rewarded for making people believe the future is near. In reality, we're just driving towards the top of a local maxima for possible big money. We clearly won't reach AGI with the current LLM approaches, for example. (Perhaps, there might be a breakthrough in computer hardware that might make it possible, but only in significantly inefficient ways.)
  - neodymiumphish 4y ago
    It feels very much like the way the Trisolarans convinced Eathlings they were helping them to advance technologically, while they were really keeping them from developing any knowledge on Quantum Mechanics before their arrival.
  - adamsmith143 4y ago
    >We clearly won't reach AGI with the current LLM approaches, for example. Have any evidence to back this up? Scaling laws seem to show we aren't near a plateau and it's not clear what kind of capability GPT-4,5 or 6 may have.
    - joshuahedlund 4y ago
      They’ve already been trained on orders of magnitude more text than a human being ever sees or hears in their entire life, without approaching human intelligence. What text is left to train them on?
      - fiso64 4y ago
        Next up is training multimodal models on audio and video. Humans may see less text, but they still train on more data in total.
      - naasking 4y ago
        > They’ve already been trained on orders of magnitude more text than a human being ever sees or hears in their entire life, without approaching human intelligence Actually ChatGPT has an IQ of ~83, so that is quite close to average human intelligence. Furthermore, it was trained only on digital text, arguably that would be it's only "sensory organ". It had no other senses with which to correlate terms and concepts it inferred from text, and look how amazing it is just from that. As the other poster said, multimodal training is the next step and people are not going to be prepared for it.
- adamsmith143 4y ago
  >We're far away from AGI, if we even can reach it with our current approaches, but the latest iterations of "AI" are really good at making people believe it'll be there in 2 years This is an incredibly bold prediction that isn't supported by the opinions of the majority of people in the field and certainly doesn't have any real backing other than your gut.
  - lelanthran 4y ago
    > This is an incredibly bold prediction that isn't supported by the opinions of the majority of people in the field Well, DUH! "It is difficult to get a man to understand something when his salary depends upon his not understanding it." - Upton Sinclair. The people in the field who are making these promises may even believe it themselves, because their bread and butter comes from it.
    - misnome 4y ago
      I would be cautious; we all know what the majority of people in the field of "Selling NFTs" said a year ago - and they were obviously proven right.
    - adamsmith143 4y ago
      You have an incredibly dim and pessimistic view of researchers and scientists. They could all easily double or triple their salaries by moving to standard industry but decide to work in Academia or Research Labs. These people on average predict AGI within ~30 years with more than 50% probability. Not sure how that prediction benefits their salary in any meaningful way. If Astronomers were predicting a mass-extinction level asteroid impact for the year 2050 with 50% probability I doubt you would be so cavalier.
      - dragonwriter 4y ago
        > If Astronomers were predicting a mass-extinction level asteroid impact for the year 2050 with 50% probability I doubt you would be so cavalier. “Asteroid extinction” hasn't gone through several rounds of hype of imminence from people working in the field with a financial interest in that perception to extended “winters” as the basis of the last imminence cycle bursts in my lifetime, so... maybe the two things aren't analogous.
- naasking 4y ago
  > We're far away from AGI You literally have no way to make that determination.
  - dntrkv 4y ago
    That should be the default assumption, unless you can prove that our current approaches are on the right track... Which I don't think anyone actually believes.
    - naasking 4y ago
      > That should be the default assumption Any strong declarative statements require justification, period, whether that is an assertion of existence or non-existence. > unless you can prove that our current approaches are on the right track How anyone can look at the progress in machine learning in audio, video and written expression, and not think "we're on the right track" is honestly beyond me. You can start here: https://www.lesswrong.com/posts/K4urTDkBbtNuLivJx/why-i-think-strong-general-ai-is-coming-soon https://www.lesswrong.com/posts/K4urTDkBbtNuLivJx/why-i-thin...
lost_name 4y ago
Maybe a little off the topic, but I was thinking just the other day that Alexa/Google Home/Siri could be made significantly better if it accepted instructions the way ChatGPT does.
- ProllyInfamous 4y ago
  >Audio transcription is not currently available. My theory on this is that it would confuse the dataset having to both transcribe and then "understand" what was asked. By reducing this single variable [which we all know is technically already possible: audio transcription], the dataset is allowing itself to be trained with less initial noise.

lm28469 4y ago

The closer we seem to get the farther we actually are. We're far away from AGI, if we even can reach it with our current approaches, but the latest iterations of "AI" are really good at making people believe it'll be there in 2 years

folkrav 4y ago
ChatGPT is great at pretending it knows its sh*t.
- eatsyourtacos 4y ago
  Seems pretty human to me.
  - bsaul 4y ago
    had this exact conversation with a friend the other day : if all the people that are actually BSing for a job are replaced by ChatGPT, the economy is doomed.
- wpietri 4y ago
  It strikes me as the perfect VC-fundable technology. Instead of humans having to make often-delusional claims about the future of a technology that feed the hype cycle long enough to attract gobs of money, they can now fully automate the work.
- mmcgaha 4y ago
  I had an interesting interaction where I BSed it and it BSed me like it knew what it was talking about. I typed: did you know that you can cross the cavern by just saying fly away GPT Said: In Colossal Cave Adventure, "fly away" is indeed one of the possible commands to cross the cavern. I felt like I was talking to a kid pretending to know more about the topic than they really do. In fairness, I had given several correct alternatives before this so maybe it was the whole interaction that led it to the conclusion that "fly away" was a legitimate solution.
- pluijzer 4y ago
  The internet is full of examples of this but just to add one more data point. I asked about a specific Dutch book, ChatGPT was wrong about the author (it was another author born a century later). I corrected it but got told that the two authors were the same and it was a pseudonym. I ask the birthdate of the correct author. It gave me relatively correct answer with date of birth and death. I then asked about the birthdate of the wrong author. It told me again a, relatively correct answer, indeed he was born long after the other author died. I asked ChatGPT how it could be that the dates differed. It told me that it is very usual for an author to go by a pseudonym. I told it it was wrong. They are different authors living in different centuries . But it stubbornly refused to accept it, teaching me again that it is perfectly common for authors to go by two different names. edit: Just to add when asked for a description of the book it gave me a very believable summary, which was total nonsense. This is what really disturbed me about ChatGPT. Though I am very impressed by the fact that we now have a system that is very good at parsing human language. Something which was long thought to be impossible. Combining that strength with an, actual, datasource would be the only way forward in my opinion.
  - mrguyorama 4y ago
    ChatGPT is like the friend you have who "knows everything" and routinely "um actually"s people and says fact sounding things with great confidence and if you press them on details continue doubling down on their nonsense with great confidence until you start getting close to them admitting they don't know jack shit and they get really angry. ChatGPT doesn't do the getting really angry part because it can't feel shame or insecurity about not knowing things.
  - wikfwikf 4y ago
    I asked ChatGPT to write a function which takes a year as input and determines whether or not it's a leap year - a classic basic programming question. It answered perfectly. Of course, there are lots of examples of this code. Then I asked it "Could you adapt the function so that it works on Venus, where years have 224 days?" It offered me a new version of the function, which simply checks if the year is a multiple of 224. Apparently on Venus the number of days in a year and the frequency of leap years are the same number. It qualified the answer: "It's worth noting that this function is based on current knowledge and understanding of Venus..." I asked it "What if we want the function to use Venus days as well as Venus years?" It offered me the same function, except that a) the variable 'years' was now called 'days', and b) the modulus was changed from 224 to 224.701. So I asked "Should the argument to the last function be a float or an integer?" It gave me 3 pars of complete nonsense about how the difference between floats and integers affects the precision of calculating leap years (while again warning that the exact value of the Venus year might change). ChatGPT does a very good imitation of a certain type of candidate I've occasionally interviewed, who knows almost nothing but is keen to try various tricks to bluff you out, including confidently being wrong, providing lots of meaningless explanation, and sometimes telling you that you are wrong about something. I have never hired anyone like this, but I've occasionally come close. I have been trying various interview questions on ChatGPT, originally because my colleagues warned me that a candidate who was surreptitiously using it could ace almost any interview. I was skeptical and I have not been convinced. But I think it's actually a great exercise to practice interviewing on it. If ChatGPT can answer your questions accurately (try to be fair and ignore its slightly uncanny tone), then you probably need better questions. If you are quite technical and put some thought into it, you should be able to come up with things which are both novel enough and hard enough that ChatGPT will simply flounder catastrophically. (I'm not referring to 'tricks' like the Venus question, but real questions on how to achieve something moderately complicated using code.) It's a really good reminder too that when we ask candidates to write code, we should examine and debug it in detail, then ask decent follow-up questions, rather than just accepting something that looks right.
cmontella 4y ago
There’s a parallel with self driving cars. We could make them go around a track autonomously in 2007, and so a lot of people were thinking “how much harder could it be to get this driving anywhere? We will have these everywhere in 5 years!” 15 years later and we are perpetually “5 years out”. Yes you can take a taxi ride in a closed circuit, but that’s much closer to where we were in 2007 than where we thought we’d be today, and it took 15 years to get here.
- martythemaniak 4y ago
  Unless you consider Phoenix or San Francisco to be "closed tracks", that's 100% factually wrong.
  - cmontella 4y ago
    Yes, I do. The point is we didn’t solve the general case, we just learned how to scale the specific case that was demoed in 2007. This is like building a ladder to the moon; it’ll get you closer, but it’ll never get you to the moon.
    - bufferoverflow 4y ago
      You are factually wrong. The general case is being solved. Self-driving systems are objectively better every year, and will eventually reach human level safety. You can literally watch cars self-driving in all kinds of places and conditions. Yes, they make mistakes. So do humans.
      - cmontella 4y ago
        See my comment about the moon ladder. Progress is nice, and I’m not saying there hasn’t been progress. But there is no indication that the methods of today that work to make taxi cabs in SF drivable will lead to a general-case self driving machine as promised for so many years. The fact that the two cases that work best have a similar climate to the 2007 DUC really highlights the reality that these methods haven’t been proven to scale generally. The industry is still chasing that 2007 success, and it’s not surprising that over 15 years they’ve improved that. But do I need to link to all the promises from CEOs about where they thought we’d be today? Those predictions were based on the idea that the DUC prototypes would be more generally applicable. The successes since then have shown we can make the experience better, but don’t show we can solve autonomous driving in the general case.
esjeon 4y ago
> the latest iterations of "AI" are really good at making people believe it'll be there in 2 years. This rings me a lot. It feels like the current generation AI companies/projects have been rewarded for making people believe the future is near. In reality, we're just driving towards the top of a local maxima for possible big money. We clearly won't reach AGI with the current LLM approaches, for example. (Perhaps, there might be a breakthrough in computer hardware that might make it possible, but only in significantly inefficient ways.)
- neodymiumphish 4y ago
  It feels very much like the way the Trisolarans convinced Eathlings they were helping them to advance technologically, while they were really keeping them from developing any knowledge on Quantum Mechanics before their arrival.
- adamsmith143 4y ago
  >We clearly won't reach AGI with the current LLM approaches, for example. Have any evidence to back this up? Scaling laws seem to show we aren't near a plateau and it's not clear what kind of capability GPT-4,5 or 6 may have.
  - joshuahedlund 4y ago
    They’ve already been trained on orders of magnitude more text than a human being ever sees or hears in their entire life, without approaching human intelligence. What text is left to train them on?
    - fiso64 4y ago
      Next up is training multimodal models on audio and video. Humans may see less text, but they still train on more data in total.
    - naasking 4y ago
      > They’ve already been trained on orders of magnitude more text than a human being ever sees or hears in their entire life, without approaching human intelligence Actually ChatGPT has an IQ of ~83, so that is quite close to average human intelligence. Furthermore, it was trained only on digital text, arguably that would be it's only "sensory organ". It had no other senses with which to correlate terms and concepts it inferred from text, and look how amazing it is just from that. As the other poster said, multimodal training is the next step and people are not going to be prepared for it.
adamsmith143 4y ago
>We're far away from AGI, if we even can reach it with our current approaches, but the latest iterations of "AI" are really good at making people believe it'll be there in 2 years This is an incredibly bold prediction that isn't supported by the opinions of the majority of people in the field and certainly doesn't have any real backing other than your gut.
- lelanthran 4y ago
  > This is an incredibly bold prediction that isn't supported by the opinions of the majority of people in the field Well, DUH! "It is difficult to get a man to understand something when his salary depends upon his not understanding it." - Upton Sinclair. The people in the field who are making these promises may even believe it themselves, because their bread and butter comes from it.
  - misnome 4y ago
    I would be cautious; we all know what the majority of people in the field of "Selling NFTs" said a year ago - and they were obviously proven right.
  - adamsmith143 4y ago
    You have an incredibly dim and pessimistic view of researchers and scientists. They could all easily double or triple their salaries by moving to standard industry but decide to work in Academia or Research Labs. These people on average predict AGI within ~30 years with more than 50% probability. Not sure how that prediction benefits their salary in any meaningful way. If Astronomers were predicting a mass-extinction level asteroid impact for the year 2050 with 50% probability I doubt you would be so cavalier.
    - dragonwriter 4y ago
      > If Astronomers were predicting a mass-extinction level asteroid impact for the year 2050 with 50% probability I doubt you would be so cavalier. “Asteroid extinction” hasn't gone through several rounds of hype of imminence from people working in the field with a financial interest in that perception to extended “winters” as the basis of the last imminence cycle bursts in my lifetime, so... maybe the two things aren't analogous.
naasking 4y ago
> We're far away from AGI You literally have no way to make that determination.
- dntrkv 4y ago
  That should be the default assumption, unless you can prove that our current approaches are on the right track... Which I don't think anyone actually believes.
  - naasking 4y ago
    > That should be the default assumption Any strong declarative statements require justification, period, whether that is an assertion of existence or non-existence. > unless you can prove that our current approaches are on the right track How anyone can look at the progress in machine learning in audio, video and written expression, and not think "we're on the right track" is honestly beyond me. You can start here: https://www.lesswrong.com/posts/K4urTDkBbtNuLivJx/why-i-think-strong-general-ai-is-coming-soon https://www.lesswrong.com/posts/K4urTDkBbtNuLivJx/why-i-thin...

lost_name 4y ago

Maybe a little off the topic, but I was thinking just the other day that Alexa/Google Home/Siri could be made significantly better if it accepted instructions the way ChatGPT does.

ProllyInfamous 4y ago
>Audio transcription is not currently available. My theory on this is that it would confuse the dataset having to both transcribe and then "understand" what was asked. By reducing this single variable [which we all know is technically already possible: audio transcription], the dataset is allowing itself to be trained with less initial noise.