6 ms·

This is a black swan event which, if anything, vindicates the hype from dreamers who were ahead of their time. They had a lot of the theory right but lacked the

This is a black swan event which, if anything, vindicates the hype from dreamers who were ahead of their time. They had a lot of the theory right but lacked the horsepower. This will complete the last mile for other AI tech and be the lacquer that gives it the all important finishing touch.

shanebellone 4y ago
"This is a black swan event" By definition, black swan events are unpredictable. This example isn't that.
- visarga 4y ago
  LLM emergence was unpredictable in 2017. Even for the best AI people.
  - shanebellone 4y ago
    ChatGPT is nothing more than long-form autocomplete. The specifics of approach are irrelevant.
    - imposter 4y ago
      A human brain is nothing more than long-form autocomplete. The specifics of approach are irrelevant.
      - FrustratedMonky 4y ago
        Exactly. All the people saying LLM's aren't important because it is just auto-complete, really don't connect the dots that humans are also just auto-complete.
        ChatGTP 4y ago
        What on earth are you talking about?
        ricardobeat 4y ago
        Our brain excels at pattern matching. We attribute a lot of human abilities to “intelligence”, but the line between that and pattern-matching (or “autocomplete” ad it’s being referred as here) is being challenged by these latest LLMs. If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?
        shanebellone 4y ago
        "If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?" That's extrapolation via approximation. Computers synthesize a specification. The difference is nuanced and entirely contextual.
        ricardobeat 4y ago
        Those are way too broad terms for this conversation to go anywhere. The point is, what's to say the LLM is not doing "extrapolation via approximation" or some process that is analog to how we think? We barely understand how the brain works to start with.
      - modriano 4y ago
        But the human brain is a much more mature product (although I will concede there are still a ton of bugs to work out that we really have no idea how to repair because the product is extremely complex and still pretty fragile).
      - makeworld 4y ago
        Everyone likes to say this, but no one seems to provide evidence. I don't believe it.
      - lamp987 4y ago
        Why do you think that?
    - auggierose 4y ago
      I knew something changed after AlphaGo. Compute could do what we thought only true intelligence can do. So I agree, LLMs are not a black swan. It will change everything, nevertheless. I keep reading these opinions that LLMs are just doing some advanced form of copy paste. Actually, we don't know what they are doing. Are they actually doing some form of modelling and abstraction? Seems likely to me.
      - Jensson 4y ago
        AlphaGo is basically the same as image recognition, not sure why you thought AlphaGo was special compared to detecting faces. AlphaGo works the same way but maps game structures on a Go board instead of mapping facial structures and comparing those to known people.
        FrustratedMonky 4y ago
        It was able to beat the top GO player. What does it matter if that technology is also used in image recognition. I'd say that if its 'brain' can play games and recognize people, or in case of ChatGPT4, can talk and play chess, this is all starting to sound pretty 'General' to me.
        auggierose 4y ago
        That's exactly the kind of attitude I am talking about. You can rationalise pretty much everything and keep moving the goal post. I've seen AI do something nobody thought was possible. If that doesn't influence how you think about AI I cannot help you.
        kthejoker2 4y ago
        Nobody?
        auggierose 4y ago
        Well, maybe the self-driving car people thought it was possible. But I don't take them seriously.
    - johnthewise 4y ago
      next bit prediction, or long-form autocomplete, may lead to general intelligence. http://mattmahoney.net/dc/rationale.html http://mattmahoney.net/dc/rationale.html
- textninja 4y ago
  The black swan event includes the unexpected emergent capabilities of LLMs, which can pass professional examinations and exhibit many attributes of general intelligence, combined with the broad availability to market and massive pressure on big industry players to adapt and innovate or die. If things keep going this way then pretty soon the black swans are going to outnumber the white ones.
  - throwaway1851 4y ago
    I don’t put much stock in the claims about GPT4 “passing” professional exams. Many copies of previously administered exams are available, and the exams are formulaic in their construction (to make them stable, predictable targets). A compressive copy of the internet brute-forcing its way through an exam (which it may even have digested already) is really not interpretable as performing well on the exam. It’s a meaningless measure because the tests were not designed with this use in mind.
  - neuronic 4y ago
    Single stories of LLM success are just as problematic as single stories of LLM failures. As always. The fact is that we have a dangerous tool at hand that absolutely REQUIRES skepticism if you are trying to get *facts* out of it. I agree that LLMs are extremely likely to impact many areas of work, particularly bullshit work. But as it stands you absolutely cannot use them as fact machines, the results can be catastrophic. What it does well, among others: - Scaffolding text, breaking writers block etc. - Compose basic texts from minimal input, for example for bullshit tasks -> I generated an internal "vision statement" during a Miro workshop for my team by inputting a bunch of bullet points gathered from the team members brain storming. It created a concise, fluid text that everybody liked. It's now the vision statement. - Point you in good directions, give you ideas What it does NOT well, among others: - provide factual responses. all responses MUST be scrutinized because they are likely containing false information. This is very dangerous for society ("Can I take this medicine with this other medicine?") - Compose creative texts that are coherent and novel. ChatGPT texts can be quite fun but they rarely make sense beyond very superficial screening and convey no deeper message. However, ChatGPT-like tools are used with a lot of naivety and often blind acceptance instead of using them as tools to aid your work.

shanebellone 4y ago

"This is a black swan event" By definition, black swan events are unpredictable. This example isn't that.

visarga 4y ago
LLM emergence was unpredictable in 2017. Even for the best AI people.
- shanebellone 4y ago
  ChatGPT is nothing more than long-form autocomplete. The specifics of approach are irrelevant.
  - imposter 4y ago
    A human brain is nothing more than long-form autocomplete. The specifics of approach are irrelevant.
    - FrustratedMonky 4y ago
      Exactly. All the people saying LLM's aren't important because it is just auto-complete, really don't connect the dots that humans are also just auto-complete.
      - ChatGTP 4y ago
        What on earth are you talking about?
        ricardobeat 4y ago
        Our brain excels at pattern matching. We attribute a lot of human abilities to “intelligence”, but the line between that and pattern-matching (or “autocomplete” ad it’s being referred as here) is being challenged by these latest LLMs. If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?
        shanebellone 4y ago
        "If it can look at a picture, explain what’s in it, and hypothesize about physics inside the picture’s environment, is it “just pattern matching”?" That's extrapolation via approximation. Computers synthesize a specification. The difference is nuanced and entirely contextual.
        ricardobeat 4y ago
        Those are way too broad terms for this conversation to go anywhere. The point is, what's to say the LLM is not doing "extrapolation via approximation" or some process that is analog to how we think? We barely understand how the brain works to start with.
    - modriano 4y ago
      But the human brain is a much more mature product (although I will concede there are still a ton of bugs to work out that we really have no idea how to repair because the product is extremely complex and still pretty fragile).
    - makeworld 4y ago
      Everyone likes to say this, but no one seems to provide evidence. I don't believe it.
    - lamp987 4y ago
      Why do you think that?
  - auggierose 4y ago
    I knew something changed after AlphaGo. Compute could do what we thought only true intelligence can do. So I agree, LLMs are not a black swan. It will change everything, nevertheless. I keep reading these opinions that LLMs are just doing some advanced form of copy paste. Actually, we don't know what they are doing. Are they actually doing some form of modelling and abstraction? Seems likely to me.
    - Jensson 4y ago
      AlphaGo is basically the same as image recognition, not sure why you thought AlphaGo was special compared to detecting faces. AlphaGo works the same way but maps game structures on a Go board instead of mapping facial structures and comparing those to known people.
      - FrustratedMonky 4y ago
        It was able to beat the top GO player. What does it matter if that technology is also used in image recognition. I'd say that if its 'brain' can play games and recognize people, or in case of ChatGPT4, can talk and play chess, this is all starting to sound pretty 'General' to me.
      - auggierose 4y ago
        That's exactly the kind of attitude I am talking about. You can rationalise pretty much everything and keep moving the goal post. I've seen AI do something nobody thought was possible. If that doesn't influence how you think about AI I cannot help you.
        kthejoker2 4y ago
        Nobody?
        auggierose 4y ago
        Well, maybe the self-driving car people thought it was possible. But I don't take them seriously.
  - johnthewise 4y ago
    next bit prediction, or long-form autocomplete, may lead to general intelligence. http://mattmahoney.net/dc/rationale.html http://mattmahoney.net/dc/rationale.html
textninja 4y ago
The black swan event includes the unexpected emergent capabilities of LLMs, which can pass professional examinations and exhibit many attributes of general intelligence, combined with the broad availability to market and massive pressure on big industry players to adapt and innovate or die. If things keep going this way then pretty soon the black swans are going to outnumber the white ones.
- throwaway1851 4y ago
  I don’t put much stock in the claims about GPT4 “passing” professional exams. Many copies of previously administered exams are available, and the exams are formulaic in their construction (to make them stable, predictable targets). A compressive copy of the internet brute-forcing its way through an exam (which it may even have digested already) is really not interpretable as performing well on the exam. It’s a meaningless measure because the tests were not designed with this use in mind.
- neuronic 4y ago
  Single stories of LLM success are just as problematic as single stories of LLM failures. As always. The fact is that we have a dangerous tool at hand that absolutely REQUIRES skepticism if you are trying to get *facts* out of it. I agree that LLMs are extremely likely to impact many areas of work, particularly bullshit work. But as it stands you absolutely cannot use them as fact machines, the results can be catastrophic. What it does well, among others: - Scaffolding text, breaking writers block etc. - Compose basic texts from minimal input, for example for bullshit tasks -> I generated an internal "vision statement" during a Miro workshop for my team by inputting a bunch of bullet points gathered from the team members brain storming. It created a concise, fluid text that everybody liked. It's now the vision statement. - Point you in good directions, give you ideas What it does NOT well, among others: - provide factual responses. all responses MUST be scrutinized because they are likely containing false information. This is very dangerous for society ("Can I take this medicine with this other medicine?") - Compose creative texts that are coherent and novel. ChatGPT texts can be quite fun but they rarely make sense beyond very superficial screening and convey no deeper message. However, ChatGPT-like tools are used with a lot of naivety and often blind acceptance instead of using them as tools to aid your work.