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So... Who builds the AI? This is why I think the AI industry is mostly smoke and mirrors. If these tools are really as revolutionary as they claim they are, th

by imiric 1y ago

So... Who builds the AI? This is why I think the AI industry is mostly smoke and mirrors. If these tools are really as revolutionary as they claim they are, then they should be able to build better versions of themselves, and we should be seeing exponential improvements of their capabilities. Yet in the last year or so we've seen marginal improvements based mainly on increasing the scale and quality of the data they're trained on, and the scale of deployments, with some clever engineering work thrown in.

trgn 1y ago
> who builds the ai 3 to 5 companies iso of the hundreds of thousands who sell software now
TeMPOraL 1y ago
> If these tools are really as revolutionary as they claim they are, then they should be able to build better versions of themselves, and we should be seeing exponential improvements of their capabilities. Recursive self-improvement is literally the endgame scenario - hard takeoff, singularity, the works. Are you really saying you're dissatisfied with the progress of those tools because they didn't manage to end the world as we know it just yet?
- fellatio 1y ago
  Nope. Just that 1. Is better than people. 2. Isn't better than people. Pick one! If the former then yes singularity. The only hope is it's "good will" (wouldn't bet on that) or turning off switches. If the latter you still need more workers (programmers or whatever they'll be called) due to increased demand for compute solutions.
  - TeMPOraL 1y ago
    > Nope. Just that 1. Is better than people. 2. Isn't better than people. Pick one! That's too coarse of a choice. It's better than people at increasingly large number of distinct tasks. But it's not good enough to recursively self-improve just yet - though it is doing it indirectly: it's useful enough to aid researchers and businesses in creating next generation of models. So in a way, the recursion and resulting exponent are already there, we're just in such early stages that it looks like linear progress.
    - fellatio 1y ago
      Thanks. Your nuanced version is better. In that version I can still ignore most of LinkedIn and Twitter and assume there will still be a need for people. Not just at OMGAD (OpenAI...) but at thousands of companies.
- no_wizard 1y ago
  I don’t believe the technology horizon in the next 5 years is sufficiently developed for recursive self improvement to work so well it requires no human intervention, by which I mean it will hit a limit and the technology will still be a tool not a sentient (near sentient?) thing. I think there will be a wall hit eventually with this, much like there was with visual recognition in the mid 2010s[0]. It will continue to improve but not exponentially To be fair I am bullish it will make white collar work fundamentally different but smart companies will use it to accelerate their workforce productivity, reliability and delivery, not simply cut labor to the bone, despite that seemingly being every CEOs wet dream right now [0]: remember when everyone was making demos and apps that would identify objects and such, and all the facial augmentation stuff? My general understanding is that the tech is now in the incremental improvement stage. I think LLMs will hit the same stage in the near term and likely hover there for quite awhile
  - TeMPOraL 1y ago
    > I don’t believe the technology horizon in the next 5 years is sufficiently developed for recursive self improvement to work so well it requires no human intervention I'm personally 50/50 on this prediction at this point. It doesn't feel like we have enough ingredients for end-to-end recursive self-improvement in the next 5 years, but the overall pace is such that I'm hesitant to say it's not likely either. Still, my reply was to the person who seemed to say they won't be impressed until they see AIs "able to build better versions of themselves" and "exponential improvements of their capabilities" - to this I'm saying, if/when it happens, it'll be the last thing that they'll ever be impressed with. > remember when everyone was making demos and apps that would identify objects and such, and all the facial augmentation stuff? My general understanding is that the tech is now in the incremental improvement stage. I thought that this got a) boring, and b) all those advancements got completely blown away by multimodal LLMs and other related models. My perspective is that we had a breakthrough across the board in this a couple years ago, after the stuff you mentioned happened, and that isn't showing signs of slowing down.
- yusina 1y ago
  Moving goal posts? This was a response to the claim that AIs are the new code.
  - TeMPOraL 1y ago
    Not really. GP claims they expect to see exponential improvements to be impressed - seemingly without realizing how such exponent will look like once it's happening and starts to look obviously exponential.
- mlboss 1y ago
  Recursive self-improvement will never happen. We will hit physical limitation before that: energy, rate earth minerals, datacenter etc. The only way we can have recursive self-improvement if Robots take over and start expanding to other planets/solar systems.
- imiric 1y ago
  No, that's not what I'm saying. The progress has been adequate and expected, save for very few cases such as generative image and video, which has exceeded my expectations. Before we reach the point where AI is self-improving on its own, we should go through stages where AI is being improved by humans using AI. That is, if these tools are capable of reasoning and are able to solve advanced logic, math, and programming challenges as shown in benchmarks, then surely they must be more capable of understanding and improving their own codebases with assistance from humans than humans could do alone. My point is that if this was being done, we should be seeing much greater progress than we've seen so far. Either these tools are intelligent, or they're highly overrated. Which wouldn't mean that they can't be useful, just not to the extent that they're being marketed as.
  - Eisenstein 1y ago
    > if these tools are capable of reasoning and are able to solve advanced logic, math, and programming challenges as shown in benchmarks The benchmarks are make of questions that humans created and can answer, and are not composed of anything which a human hasn't been able to answer. > then surely they must be more capable of understanding and improving their own codebases with assistance from humans than humans could do alone. I don't think that logic follows. The models have proven that they can have more breadth of knowledge than a single human, but not more capability. Also, they have no particular insight into their own codebases. They only know what is in their training data -- they can use that to form patterns and solve new problems, but they still only have the that and whatever information is given with the question as base knowledge. > My point is that if this was being done, we should be seeing much greater progress than we've seen so far. The point is taken, but I think your reasoning is weak. > Either these tools are intelligent, or they're highly overrated. Which wouldn't mean that they can't be useful, just not to the extent that they're being marketed as. I may have missed the marketing you have seen, but I don't see the big AI companies claiming that they are anything but tools that can help humans do things or replace certain human tasks. They do not advertise super human capability in intelligence tasks. I suspect you are seeing a lot of hype and unfounded expectations, and using that as a basis for a calculation. The formula might be right, but the variables are incorrect. We have a seen a LOT of progress with AI and language models in the last few years, but expecting them to go from 'can understand language and solve complicated novel problems' to 'making better versions of themselves using solutions that humans haven't been able to come up with yet' is a bit much to expect. I don't know if one would call them intelligent, but something can be intelligent but at the same time not able to make substantial leaps forward in emerging fields.
iLoveOncall 1y ago
> If these tools are really as revolutionary as they claim they are, then they should be able to build better versions of themselves, and we should be seeing exponential improvements of their capabilities. Yet in the last year or so we've seen marginal improvements based mainly on increasing the scale and quality of the data they're trained on, and the scale of deployments, with some clever engineering work thrown in. Yes and we've actually been able to witness in public the dubious contributions that Copilot has made on public Microsoft repositories.

by imiric 1y ago

trgn 1y ago

> who builds the ai 3 to 5 companies iso of the hundreds of thousands who sell software now

TeMPOraL 1y ago

> If these tools are really as revolutionary as they claim they are, then they should be able to build better versions of themselves, and we should be seeing exponential improvements of their capabilities. Recursive self-improvement is literally the endgame scenario - hard takeoff, singularity, the works. Are you really saying you're dissatisfied with the progress of those tools because they didn't manage to end the world as we know it just yet?

fellatio 1y ago
Nope. Just that 1. Is better than people. 2. Isn't better than people. Pick one! If the former then yes singularity. The only hope is it's "good will" (wouldn't bet on that) or turning off switches. If the latter you still need more workers (programmers or whatever they'll be called) due to increased demand for compute solutions.
- TeMPOraL 1y ago
  > Nope. Just that 1. Is better than people. 2. Isn't better than people. Pick one! That's too coarse of a choice. It's better than people at increasingly large number of distinct tasks. But it's not good enough to recursively self-improve just yet - though it is doing it indirectly: it's useful enough to aid researchers and businesses in creating next generation of models. So in a way, the recursion and resulting exponent are already there, we're just in such early stages that it looks like linear progress.
  - fellatio 1y ago
    Thanks. Your nuanced version is better. In that version I can still ignore most of LinkedIn and Twitter and assume there will still be a need for people. Not just at OMGAD (OpenAI...) but at thousands of companies.
no_wizard 1y ago
I don’t believe the technology horizon in the next 5 years is sufficiently developed for recursive self improvement to work so well it requires no human intervention, by which I mean it will hit a limit and the technology will still be a tool not a sentient (near sentient?) thing. I think there will be a wall hit eventually with this, much like there was with visual recognition in the mid 2010s[0]. It will continue to improve but not exponentially To be fair I am bullish it will make white collar work fundamentally different but smart companies will use it to accelerate their workforce productivity, reliability and delivery, not simply cut labor to the bone, despite that seemingly being every CEOs wet dream right now [0]: remember when everyone was making demos and apps that would identify objects and such, and all the facial augmentation stuff? My general understanding is that the tech is now in the incremental improvement stage. I think LLMs will hit the same stage in the near term and likely hover there for quite awhile
- TeMPOraL 1y ago
  > I don’t believe the technology horizon in the next 5 years is sufficiently developed for recursive self improvement to work so well it requires no human intervention I'm personally 50/50 on this prediction at this point. It doesn't feel like we have enough ingredients for end-to-end recursive self-improvement in the next 5 years, but the overall pace is such that I'm hesitant to say it's not likely either. Still, my reply was to the person who seemed to say they won't be impressed until they see AIs "able to build better versions of themselves" and "exponential improvements of their capabilities" - to this I'm saying, if/when it happens, it'll be the last thing that they'll ever be impressed with. > remember when everyone was making demos and apps that would identify objects and such, and all the facial augmentation stuff? My general understanding is that the tech is now in the incremental improvement stage. I thought that this got a) boring, and b) all those advancements got completely blown away by multimodal LLMs and other related models. My perspective is that we had a breakthrough across the board in this a couple years ago, after the stuff you mentioned happened, and that isn't showing signs of slowing down.
yusina 1y ago
Moving goal posts? This was a response to the claim that AIs are the new code.
- TeMPOraL 1y ago
  Not really. GP claims they expect to see exponential improvements to be impressed - seemingly without realizing how such exponent will look like once it's happening and starts to look obviously exponential.
mlboss 1y ago
Recursive self-improvement will never happen. We will hit physical limitation before that: energy, rate earth minerals, datacenter etc. The only way we can have recursive self-improvement if Robots take over and start expanding to other planets/solar systems.
imiric 1y ago
No, that's not what I'm saying. The progress has been adequate and expected, save for very few cases such as generative image and video, which has exceeded my expectations. Before we reach the point where AI is self-improving on its own, we should go through stages where AI is being improved by humans using AI. That is, if these tools are capable of reasoning and are able to solve advanced logic, math, and programming challenges as shown in benchmarks, then surely they must be more capable of understanding and improving their own codebases with assistance from humans than humans could do alone. My point is that if this was being done, we should be seeing much greater progress than we've seen so far. Either these tools are intelligent, or they're highly overrated. Which wouldn't mean that they can't be useful, just not to the extent that they're being marketed as.
- Eisenstein 1y ago
  > if these tools are capable of reasoning and are able to solve advanced logic, math, and programming challenges as shown in benchmarks The benchmarks are make of questions that humans created and can answer, and are not composed of anything which a human hasn't been able to answer. > then surely they must be more capable of understanding and improving their own codebases with assistance from humans than humans could do alone. I don't think that logic follows. The models have proven that they can have more breadth of knowledge than a single human, but not more capability. Also, they have no particular insight into their own codebases. They only know what is in their training data -- they can use that to form patterns and solve new problems, but they still only have the that and whatever information is given with the question as base knowledge. > My point is that if this was being done, we should be seeing much greater progress than we've seen so far. The point is taken, but I think your reasoning is weak. > Either these tools are intelligent, or they're highly overrated. Which wouldn't mean that they can't be useful, just not to the extent that they're being marketed as. I may have missed the marketing you have seen, but I don't see the big AI companies claiming that they are anything but tools that can help humans do things or replace certain human tasks. They do not advertise super human capability in intelligence tasks. I suspect you are seeing a lot of hype and unfounded expectations, and using that as a basis for a calculation. The formula might be right, but the variables are incorrect. We have a seen a LOT of progress with AI and language models in the last few years, but expecting them to go from 'can understand language and solve complicated novel problems' to 'making better versions of themselves using solutions that humans haven't been able to come up with yet' is a bit much to expect. I don't know if one would call them intelligent, but something can be intelligent but at the same time not able to make substantial leaps forward in emerging fields.

iLoveOncall 1y ago

> If these tools are really as revolutionary as they claim they are, then they should be able to build better versions of themselves, and we should be seeing exponential improvements of their capabilities. Yet in the last year or so we've seen marginal improvements based mainly on increasing the scale and quality of the data they're trained on, and the scale of deployments, with some clever engineering work thrown in. Yes and we've actually been able to witness in public the dubious contributions that Copilot has made on public Microsoft repositories.