5 ms·

To me, it seemed like they spent there money to get there. They talked about the massive datacenter they built, but will it pay off is the question.

by ddxv 2y ago

jiggawatts 2y ago
They may not need direct subscription revenue to recoup their investment. A variant of multi-modal LLMs may be the solution to self-driving cars, home robotics, and more. I keep saying that to be a really effective driver, an AI model will need a theory of mind, which the larger LLMs appear to have. Similarly, any such model will need to be able to do OCR and read arbitrary street signs, and understand what the sign meant. Most modern LLMs can already do this.
- steve_adams_86 2y ago
  Since when do LLMS appear to possess theory of mind? The papers I've read on this show impressive capabilities, but only within conditions where language-based training would strongly indicate appropriate outputs for the LLM to use. Outside of familiar conditions, or even realistic conditions, they don't do well. It's all still statistical string-building.
  - sebzim4500 2y ago
    Can you give an example prompt that shows a lack of theory of mind? It used to be easy, but now that models have improved I've noticed that the 'LLM doubters' nowadays are forced to make generic, almost spiritual, claims rather than making concrete statements.
    - emptysongglass 2y ago
      The burden isn't on us, it's on people making claims that LLMs do possess theory of mind. You're the one who has to prove it, not us.
      - sebzim4500 2y ago
        If you use any of the conventional tests that exist of theory of mind (most famously the Sally-Anne Test [1] but also the others) then SOTA reasoning models will get near 100%. Even if you try to come up with similar questions which you expect not to be in the training set they will still get them right. In the absence of any evidence to the contrary, this is convincing evidence in my opinion. [1] https://en.wikipedia.org/wiki/Sally%E2%80%93Anne_test https://en.wikipedia.org/wiki/Sally%E2%80%93Anne_test
        esafak 2y ago
        Maybe having a theory of mind isn't the big deal we thought it was. People are so conditioned to expect such things only from biological lifeforms, where theory of mind comes packaged with many other abilities that robots currently lack, that we reflexively dismiss the robot.
        zipy124 2y ago
        That same source you link says that your view of 100% is not accepted as a consesus: "... GPT-4's ability to reason about the beliefs of other agents remains limited (59% accuracy on the ToMi benchmark),[15] and is not robust to "adversarial" changes to the Sally-Anne test that humans flexibly handle.[16][17] While some authors argue that the performance of GPT-4 on Sally-Anne-like tasks can be increased to 100% via improved prompting strategies,[18] this approach appears to improve accuracy to only 73% on the larger ToMi dataset."
        sebzim4500 2y ago
        We are talking about frontier models not GPT-4
        zipy124 2y ago
        Yes but I am using the same source the commenter used to backup their figure, merely saying look your source doesn't say what you claim it does. If they wanted to talk about frontier models maybe they should have cited a link to talking about frontier models performance.
- MrMan 2y ago
  [dead]
- HarHarVeryFunny 2y ago
  You're not going to run a SOTA LLM of this size off batteries (robotics), even in a car where the alternator is charging them, nor can you afford to rely on a high-speed internet connection being available 100% in a life or death (FSD) application. I don't have so much faith in the future of current-architecure LLMs, but I do think that AGI will be needed for safe FSD and general-purpose robots that need to learn and operate in an uncontrolled environment such as a home.
  - ggreer 2y ago
    A typical car alternator outputs 1.5-3kW of electricity, and EVs can output arbitrary amounts of power for electronics (though that will reduce range). That's more than enough to run purpose-built circuitry for a SOTA LLM. For a home robot, you could run the compute in the home instead of in the robot's body. I don't think AGI is needed for FSD because we already have safe FSD in the form of Waymo, and competitors aren't far behind. People forget that self-driving doesn't have to be perfect. It just has to be better than human drivers. Human drivers get sleepy, drunk, angry, and/or distracted. They can't see in 360º or react in milliseconds. Most cyclists and pedestrians prefer current FSD implementations to human drivers, as the computer-driven cars are much better about yielding, giving a wide berth, and being patient.
    - HarHarVeryFunny 2y ago
      Waymo is obviously pretty decent, but it's easy to drive 99.9% of the time. It's when there's invisible black ice on the road, or an animal runs out in front of you, or you lose visibility due to sun glare or whatever (I once had windshield wiper fluid = water flash freeze on contact) - maybe mud on a camera, or a wheel falls off your car or the one in front, etc, etc, that things get weird. Having autonomous cars that are statistically safer then the average driver is a reasonable bar to allow them on the road, but for ME to want to drive one I want it to be safer than me, and I am not a hot-headed teenager, or gaga 80-yr old, or drunken fool, and since I have AGI (Actual General Intelligence) I react pretty well to weird shit.

To me, it seemed like they spent there money to get there. They talked about the massive datacenter they built, but will it pay off is the question.

by ddxv 2y ago

To me, it seemed like they spent there money to get there. They talked about the massive datacenter they built, but will it pay off is the question.

jiggawatts 2y ago

They may not need direct subscription revenue to recoup their investment. A variant of multi-modal LLMs may be the solution to self-driving cars, home robotics, and more. I keep saying that to be a really effective driver, an AI model will need a theory of mind, which the larger LLMs appear to have. Similarly, any such model will need to be able to do OCR and read arbitrary street signs, and understand what the sign meant. Most modern LLMs can already do this.

steve_adams_86 2y ago
Since when do LLMS appear to possess theory of mind? The papers I've read on this show impressive capabilities, but only within conditions where language-based training would strongly indicate appropriate outputs for the LLM to use. Outside of familiar conditions, or even realistic conditions, they don't do well. It's all still statistical string-building.
- sebzim4500 2y ago
  Can you give an example prompt that shows a lack of theory of mind? It used to be easy, but now that models have improved I've noticed that the 'LLM doubters' nowadays are forced to make generic, almost spiritual, claims rather than making concrete statements.
  - emptysongglass 2y ago
    The burden isn't on us, it's on people making claims that LLMs do possess theory of mind. You're the one who has to prove it, not us.
    - sebzim4500 2y ago
      If you use any of the conventional tests that exist of theory of mind (most famously the Sally-Anne Test [1] but also the others) then SOTA reasoning models will get near 100%. Even if you try to come up with similar questions which you expect not to be in the training set they will still get them right. In the absence of any evidence to the contrary, this is convincing evidence in my opinion. [1] https://en.wikipedia.org/wiki/Sally%E2%80%93Anne_test https://en.wikipedia.org/wiki/Sally%E2%80%93Anne_test
      - esafak 2y ago
        Maybe having a theory of mind isn't the big deal we thought it was. People are so conditioned to expect such things only from biological lifeforms, where theory of mind comes packaged with many other abilities that robots currently lack, that we reflexively dismiss the robot.
      - zipy124 2y ago
        That same source you link says that your view of 100% is not accepted as a consesus: "... GPT-4's ability to reason about the beliefs of other agents remains limited (59% accuracy on the ToMi benchmark),[15] and is not robust to "adversarial" changes to the Sally-Anne test that humans flexibly handle.[16][17] While some authors argue that the performance of GPT-4 on Sally-Anne-like tasks can be increased to 100% via improved prompting strategies,[18] this approach appears to improve accuracy to only 73% on the larger ToMi dataset."
        sebzim4500 2y ago
        We are talking about frontier models not GPT-4
        zipy124 2y ago
        Yes but I am using the same source the commenter used to backup their figure, merely saying look your source doesn't say what you claim it does. If they wanted to talk about frontier models maybe they should have cited a link to talking about frontier models performance.
MrMan 2y ago
[dead]
HarHarVeryFunny 2y ago
You're not going to run a SOTA LLM of this size off batteries (robotics), even in a car where the alternator is charging them, nor can you afford to rely on a high-speed internet connection being available 100% in a life or death (FSD) application. I don't have so much faith in the future of current-architecure LLMs, but I do think that AGI will be needed for safe FSD and general-purpose robots that need to learn and operate in an uncontrolled environment such as a home.
- ggreer 2y ago
  A typical car alternator outputs 1.5-3kW of electricity, and EVs can output arbitrary amounts of power for electronics (though that will reduce range). That's more than enough to run purpose-built circuitry for a SOTA LLM. For a home robot, you could run the compute in the home instead of in the robot's body. I don't think AGI is needed for FSD because we already have safe FSD in the form of Waymo, and competitors aren't far behind. People forget that self-driving doesn't have to be perfect. It just has to be better than human drivers. Human drivers get sleepy, drunk, angry, and/or distracted. They can't see in 360º or react in milliseconds. Most cyclists and pedestrians prefer current FSD implementations to human drivers, as the computer-driven cars are much better about yielding, giving a wide berth, and being patient.
  - HarHarVeryFunny 2y ago
    Waymo is obviously pretty decent, but it's easy to drive 99.9% of the time. It's when there's invisible black ice on the road, or an animal runs out in front of you, or you lose visibility due to sun glare or whatever (I once had windshield wiper fluid = water flash freeze on contact) - maybe mud on a camera, or a wheel falls off your car or the one in front, etc, etc, that things get weird. Having autonomous cars that are statistically safer then the average driver is a reasonable bar to allow them on the road, but for ME to want to drive one I want it to be safer than me, and I am not a hot-headed teenager, or gaga 80-yr old, or drunken fool, and since I have AGI (Actual General Intelligence) I react pretty well to weird shit.