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I don't know where you're getting your data that there's no obvious path, or that it's unfounded optimism. When the chatbots first came out they were unusable f

I don't know where you're getting your data that there's no obvious path, or that it's unfounded optimism. When the chatbots first came out they were unusable for code, now they're borderline good for many tasks and excellent at others, and it's only been a couple of years. Every tool has its limitations at any given time, and I think your pessimism is entirely speculative.

krupan 2y ago
Nobody has to prove a negative, my friend
- naasking 2y ago
  Anybody making a claim should be able to justify it or admit it's conjecture.
  - namaria 2y ago
    Goes both ways. Your extending the line in some particular way from the past couple of years isn't much more than an article of faith.
    - naasking 2y ago
      It's more than the past couple of years, steady improvements in machine learning stretch back decades at this point. There is no indication this is stopping or slowing down, quite the contrary. We also already know that better is possible because the human brain is still better in many ways, and it exists. You can claim that continued progression is speculative, and some aspects are, but it's hardly "an article of faith", unlike "we've suddenly hit a surprising wall we can't surmount".
      - Izkata 2y ago
        > steady improvements in machine learning stretch back decades at this point Except that's not how it's actually gone. It's more like, improvements happen in erratic jumps as new methods are discovered, then improvements slow or stall out when the limits of those methods are reached.
        naasking 2y ago
        No, that's just how it looked from the outside if you weren't tracking closely. Even emergent abilities are a mirage when you look at the actual data: https://hai.stanford.edu/news/ais-ostensible-emergent-abilities-are-mirage https://hai.stanford.edu/news/ais-ostensible-emergent-abilit...
        Izkata 2y ago
        I'm not talking "past 3 years", I'm talking "past 50 years": https://en.m.wikipedia.org/wiki/AI_winter https://en.m.wikipedia.org/wiki/AI_winter And really, there was a version of what I'm talking about in the shorter timespan with LLMs - OpenAI's GPT models existed for several years before someone got the idea to put it behind a chat interface and the popularity / apparent capability exploded a few years ago.
        naasking 2y ago
        > OpenAI's GPT models existed for several years before someone got the idea to put it behind a chat interface and the popularity / apparent capability exploded a few years ago. That's exactly what I said in the post you responded to: there weren't erratic jumps, there was steady progress over decades.
        Izkata 2y ago
        You keep switching back and forth between short and long time periods, as if the rapid steady growth of the past couple years is how it's gone for decades. This is not the case - we're currently in a short* period of rapid growth after a decade or so of stagnation. That's what "erratic" means, it has not been steady - over the past several decades there have been several times where we've seen rapid growth for a short period, then it hits a wall and we see very little or no growth until the next breakthrough. * Granted we don't know for sure it'll be short this time, but hints are that we're starting to hit that wall with improvements slowing down.
      - deleted 2y ago
        [deleted]
dns_snek 2y ago
What we have now are LLMs that some consider to be good at tasks that are incremental, limited in scope, and require constant human oversight with many iterations. What you want is an LLM that is exceptionally good at completely rewriting a poorly written codebase spanning tens or hundreds of thousands of lines of code, which works reliably with minimal oversight and without introducing hundreds of critical and hard to diagnose bugs. Not realizing that these tasks are many orders of magnitudes apart in complexity is where the "unfounded optimism" comment comes from.

krupan 2y ago

Nobody has to prove a negative, my friend

naasking 2y ago
Anybody making a claim should be able to justify it or admit it's conjecture.
- namaria 2y ago
  Goes both ways. Your extending the line in some particular way from the past couple of years isn't much more than an article of faith.
  - naasking 2y ago
    It's more than the past couple of years, steady improvements in machine learning stretch back decades at this point. There is no indication this is stopping or slowing down, quite the contrary. We also already know that better is possible because the human brain is still better in many ways, and it exists. You can claim that continued progression is speculative, and some aspects are, but it's hardly "an article of faith", unlike "we've suddenly hit a surprising wall we can't surmount".
    - Izkata 2y ago
      > steady improvements in machine learning stretch back decades at this point Except that's not how it's actually gone. It's more like, improvements happen in erratic jumps as new methods are discovered, then improvements slow or stall out when the limits of those methods are reached.
      - naasking 2y ago
        No, that's just how it looked from the outside if you weren't tracking closely. Even emergent abilities are a mirage when you look at the actual data: https://hai.stanford.edu/news/ais-ostensible-emergent-abilities-are-mirage https://hai.stanford.edu/news/ais-ostensible-emergent-abilit...
        Izkata 2y ago
        I'm not talking "past 3 years", I'm talking "past 50 years": https://en.m.wikipedia.org/wiki/AI_winter https://en.m.wikipedia.org/wiki/AI_winter And really, there was a version of what I'm talking about in the shorter timespan with LLMs - OpenAI's GPT models existed for several years before someone got the idea to put it behind a chat interface and the popularity / apparent capability exploded a few years ago.
        naasking 2y ago
        > OpenAI's GPT models existed for several years before someone got the idea to put it behind a chat interface and the popularity / apparent capability exploded a few years ago. That's exactly what I said in the post you responded to: there weren't erratic jumps, there was steady progress over decades.
        Izkata 2y ago
        You keep switching back and forth between short and long time periods, as if the rapid steady growth of the past couple years is how it's gone for decades. This is not the case - we're currently in a short* period of rapid growth after a decade or so of stagnation. That's what "erratic" means, it has not been steady - over the past several decades there have been several times where we've seen rapid growth for a short period, then it hits a wall and we see very little or no growth until the next breakthrough. * Granted we don't know for sure it'll be short this time, but hints are that we're starting to hit that wall with improvements slowing down.
    - deleted 2y ago
      [deleted]

dns_snek 2y ago

What we have now are LLMs that some consider to be good at tasks that are incremental, limited in scope, and require constant human oversight with many iterations. What you want is an LLM that is exceptionally good at completely rewriting a poorly written codebase spanning tens or hundreds of thousands of lines of code, which works reliably with minimal oversight and without introducing hundreds of critical and hard to diagnose bugs. Not realizing that these tasks are many orders of magnitudes apart in complexity is where the "unfounded optimism" comment comes from.