4 ms·

Again, in a very limited setting, under a limited set of rules. And even in that setting: Have we achieved a 100% completely autonomous car yet, that can drive

Again, in a very limited setting, under a limited set of rules. And even in that setting: Have we achieved a 100% completely autonomous car yet, that can drive a vehicle safely, no matter the conditions, without ever requiring any human intervention? My point isnt't that the systems we can build today aren't impressive. They are, beyond belief sometimes. But they are not AGIs, nor are they close to, and making systems of limited scope better at their limited tasks, doesn't equate to getting closer to a generally intelligent system. One thing that would make an AGI an actually general intelligence, is the ability to apply knowledge of one task to an arbitrary number of tasks. For example, in terms of drawing the beautiful volcano-landscapes that my GPU tower running stable diffusion is currently making, even the best self-driving AI is useless. Likewise, as impressive as stable diffusion is, I doubt it could even get my car out of the driveway.

Retric 4y ago
I disagree it’s a very limited setting. We are constantly moving to less constrained problems. What used to be a very limited setting is now perhaps a somewhat limited one. The options aren’t binary chose of using A* for pathing in a video game or AGI, it’s finding ever more generalizable solutions to ever wider range of problems. The thing is as processing power keeps improving we need ever fewer limits to active human levels of performance from these systems. I don’t think AGI is just waiting for sufficient flops, but I think that’s closer to the truth than we want to admit.
- usrbinbash 4y ago
  > I disagree it’s a very limited setting. An automated vehicle has a couple of well defined controls. It cannot play the piano. It cannot recommend products. It cannot take a picture and tell me what kind of bird that is. In fact, it probably cannot even drive offroad, despite that being a very closely related task to what it is made to do. A person trained to drive a car on roads may have difficulty time on his first few offroad drives, but can quickly aquire the skills. He won't be completely unable to function either, because to a human, navigating is navigating, whether we walk through our own homes, or drive a vehicle over rough terrain. To AI as we currently understand it, all of these are completely different tasks.
  - Retric 4y ago
    Driving a car involves effectively infinite possible choices over time. It’s both qualitatively and quantitatively vastly less constrained than chess. Classifying them both as very limited is clearly wrong. Also, the DARPA grand challenge was for self driving cars off road, it’s a simpler problem no need to check for traffic lights and stop signs it’s the same general problem. Which brings up another possibility, there are only so many tasks we might want AI for so specific systems for every single one is effectively the same thing as AGI.
danaris 4y ago
> Likewise, as impressive as stable diffusion is, I doubt it could even get my car out of the driveway. Even this analogy oversells the state of "AI" today, as it implies that it would be possible to simply "swap in" stable-diffusion for the self-driving software in your Tesla (or whatever car with similar software) without spending months figuring out how to even hook up the inputs and outputs in such a way that you could get stable-diffusion to somehow activate when you want to drive. Their IO models are so completely different—one takes a stream of largely-visual input and determines in real time whether it represents something it has been trained to recognize as "road", "danger", etc, and thus whether it should issue real-time outputs to the car's axles, brakes, etc, while the other takes discrete text or visual input prompts and uses them to generate discrete visual outputs—that it doesn't even make sense to think about how one could replace the other. They're not AIs. They're simply software programs, using machine learning algorithms to produce highly-tailored, human-opaque results that can, yes, be pretty amazing. But given all the excessive hype and disinformation lately around what these programs can do, I've made a conscious effort not to refer to them as "AI," because people have too many sci-fi associations with it, and it causes far too many of them to anthropomorphize them and impute far, far more ability and "intelligence" to them than they actually have.
- Retric 4y ago
  Self driving AI’s have complete control over a car just as you have complete control over your body. Humans can’t swap to a hummingbird or sharks body but are our template for AGI, so why argue self driving AI’s need that ability?
  - danaris 4y ago
    A self driving car's software can't write a poem, or even read one. Not even in the limited ways Stable Diffusion can. I'm not arguing that self-driving car software needs these abilities. I'm arguing that self-driving car software is not in the same class as AGI, which would need to be able to do all these things to some extent.
    - deleted 4y ago

Retric 4y ago

I disagree it’s a very limited setting. We are constantly moving to less constrained problems. What used to be a very limited setting is now perhaps a somewhat limited one. The options aren’t binary chose of using A* for pathing in a video game or AGI, it’s finding ever more generalizable solutions to ever wider range of problems. The thing is as processing power keeps improving we need ever fewer limits to active human levels of performance from these systems. I don’t think AGI is just waiting for sufficient flops, but I think that’s closer to the truth than we want to admit.

usrbinbash 4y ago
> I disagree it’s a very limited setting. An automated vehicle has a couple of well defined controls. It cannot play the piano. It cannot recommend products. It cannot take a picture and tell me what kind of bird that is. In fact, it probably cannot even drive offroad, despite that being a very closely related task to what it is made to do. A person trained to drive a car on roads may have difficulty time on his first few offroad drives, but can quickly aquire the skills. He won't be completely unable to function either, because to a human, navigating is navigating, whether we walk through our own homes, or drive a vehicle over rough terrain. To AI as we currently understand it, all of these are completely different tasks.
- Retric 4y ago
  Driving a car involves effectively infinite possible choices over time. It’s both qualitatively and quantitatively vastly less constrained than chess. Classifying them both as very limited is clearly wrong. Also, the DARPA grand challenge was for self driving cars off road, it’s a simpler problem no need to check for traffic lights and stop signs it’s the same general problem. Which brings up another possibility, there are only so many tasks we might want AI for so specific systems for every single one is effectively the same thing as AGI.

danaris 4y ago

> Likewise, as impressive as stable diffusion is, I doubt it could even get my car out of the driveway. Even this analogy oversells the state of "AI" today, as it implies that it would be possible to simply "swap in" stable-diffusion for the self-driving software in your Tesla (or whatever car with similar software) without spending months figuring out how to even hook up the inputs and outputs in such a way that you could get stable-diffusion to somehow activate when you want to drive. Their IO models are so completely different—one takes a stream of largely-visual input and determines in real time whether it represents something it has been trained to recognize as "road", "danger", etc, and thus whether it should issue real-time outputs to the car's axles, brakes, etc, while the other takes discrete text or visual input prompts and uses them to generate discrete visual outputs—that it doesn't even make sense to think about how one could replace the other. They're not AIs. They're simply software programs, using machine learning algorithms to produce highly-tailored, human-opaque results that can, yes, be pretty amazing. But given all the excessive hype and disinformation lately around what these programs can do, I've made a conscious effort not to refer to them as "AI," because people have too many sci-fi associations with it, and it causes far too many of them to anthropomorphize them and impute far, far more ability and "intelligence" to them than they actually have.

Retric 4y ago
Self driving AI’s have complete control over a car just as you have complete control over your body. Humans can’t swap to a hummingbird or sharks body but are our template for AGI, so why argue self driving AI’s need that ability?
- danaris 4y ago
  A self driving car's software can't write a poem, or even read one. Not even in the limited ways Stable Diffusion can. I'm not arguing that self-driving car software needs these abilities. I'm arguing that self-driving car software is not in the same class as AGI, which would need to be able to do all these things to some extent.
  - deleted 4y ago