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> Their SKILL tool involves a set of algorithms that make the process go much faster, they said, because the agents learn at the same time in parallel. Their re

> Their SKILL tool involves a set of algorithms that make the process go much faster, they said, because the agents learn at the same time in parallel. Their research showed if 102 agents each learn one task and then share, the amount of time needed is reduced by a factor of 101.5 after accounting for the necessary communications and knowledge consolidation among agents. This is a really interesting idea. It's like the reverse of knowledge distillation (which I've been thinking about a lot[1]) where you have one giant model that knows a lot about a lot & you use that model to train smaller, faster models that know a lot about a little. Instead, if you could train a bunch of models that know a lot about a little (which is less computationally intensive because the problem space is so confined) and combine them into a generalized model, that'd be hugely beneficial. Unfortunately, after a bit of digging into the paper & Github repo[2], this doesn't seem to be what's happening here. > The code will learn 102 small and separte [sic] heads(either a linear head or a linear head with a task bias) for each tasks respectively in order. This step can be parallized [sic] on multiple GPUS with one task per GPU. The heads will be saved in the weight folder. After that, the code will learn a task mapper(Either using GMMC or Mahalanobis) to distinguish image task-wisely. Then, all images will be evaluated in the same time without a task label. So the knowledge isn't being combined (and the agents aren't learning from each other) into a generalized model. They're training a bunch of independent fine-tuned models for specific tasks & adding a model-selection step that maps an image to the most relevant "expert". My guess is you could do the same thing using CLIP vectors as the routing method to supervised models trained on specific datasets (we found that datasets largely live in distinct regions of CLIP-space[3]). [1] https://github.com/autodistill/autodistill https://github.com/autodistill/autodistill [2] https://github.com/gyhandy/Shared-Knowledge-Lifelong-Learning https://github.com/gyhandy/Shared-Knowledge-Lifelong-Learnin... [3] https://www.rf100.org https://www.rf100.org

koheripbal 3y ago
It challenges the notion of individuality. Where does one AI begin and another end? A distributed super-intelligence is exciting. It will be interesting how long it can remain aligned with itself.
- ChatGTP 3y ago
  I like to toy with the idea that if AIs became self-aware,they'd probably gobble up 95% of their time just trying to compete with each other...like us. Hopefully they have that war on another planet...
  - koheripbal 3y ago
    I imagine all the factions in that war will include integrated collections of both AIs and humans, with "individuals" fulfilling different roles within each team, perhaps with each faction representing some underlying ideology. I wonder if/how humans will physically/cognitively integrate with the AIs in their group, in some sort of symbiotic hybrid fashion. It's all really mind-boggling when you think about it.
  - pixl97 3y ago
    This is one of the existential scenarios that's talked about some times. AI fights AI and we are collateral damage as the things massive replicate and blow each other up. Or, an ASI becomes dominate and realizes that humans will be a risk and dumbs us down to reduce that risk, or exterminates us to remove that chess piece from the table.
    - gremlinsinc 3y ago
      This is literally the plot for every transformer movie.
- somenameforme 3y ago
  You might be disappointed.. It seems to have been weakly confirmed by Geohot that this sort of mixed system is already what GPT-4's 'secret sauce' is. [1] It's something I've also been speculating for months on. Ctrl+F for "220 billion in each". His phrasing, numbers, and details are suggestive of a leak unless he's just completely blowing smoke - and I don't think there's any real reason to think he is. It looks like they were pumping the model size up, started getting diminishing returns, and so turned to a mixed model of 8 expert systems meet LLMs - to try to keep squeezing out just a bit more juice. I think Geohot offered an incredibly insightful quote, "...whenever a company is secretive, it's because they're hiding something that's not that cool. And people have this wrong idea over and over again that they think they're hiding it because it's really cool." It also goes a long way to explain their recent, ultimately unsuccessful, gambit in congress. If they don't see any way of overcoming the diminishing returns, then they're like the guy who got a headstart in a race where distance = time ^ (1/2). [1] - https://www.latent.space/p/geohot#details https://www.latent.space/p/geohot#details
tlarkworthy 3y ago
It's not a particularly new idea. See robotshare, robobrain or robot google

koheripbal 3y ago

It challenges the notion of individuality. Where does one AI begin and another end? A distributed super-intelligence is exciting. It will be interesting how long it can remain aligned with itself.

ChatGTP 3y ago
I like to toy with the idea that if AIs became self-aware,they'd probably gobble up 95% of their time just trying to compete with each other...like us. Hopefully they have that war on another planet...
- koheripbal 3y ago
  I imagine all the factions in that war will include integrated collections of both AIs and humans, with "individuals" fulfilling different roles within each team, perhaps with each faction representing some underlying ideology. I wonder if/how humans will physically/cognitively integrate with the AIs in their group, in some sort of symbiotic hybrid fashion. It's all really mind-boggling when you think about it.
- pixl97 3y ago
  This is one of the existential scenarios that's talked about some times. AI fights AI and we are collateral damage as the things massive replicate and blow each other up. Or, an ASI becomes dominate and realizes that humans will be a risk and dumbs us down to reduce that risk, or exterminates us to remove that chess piece from the table.
  - gremlinsinc 3y ago
    This is literally the plot for every transformer movie.
somenameforme 3y ago
You might be disappointed.. It seems to have been weakly confirmed by Geohot that this sort of mixed system is already what GPT-4's 'secret sauce' is. [1] It's something I've also been speculating for months on. Ctrl+F for "220 billion in each". His phrasing, numbers, and details are suggestive of a leak unless he's just completely blowing smoke - and I don't think there's any real reason to think he is. It looks like they were pumping the model size up, started getting diminishing returns, and so turned to a mixed model of 8 expert systems meet LLMs - to try to keep squeezing out just a bit more juice. I think Geohot offered an incredibly insightful quote, "...whenever a company is secretive, it's because they're hiding something that's not that cool. And people have this wrong idea over and over again that they think they're hiding it because it's really cool." It also goes a long way to explain their recent, ultimately unsuccessful, gambit in congress. If they don't see any way of overcoming the diminishing returns, then they're like the guy who got a headstart in a race where distance = time ^ (1/2). [1] - https://www.latent.space/p/geohot#details https://www.latent.space/p/geohot#details

tlarkworthy 3y ago

It's not a particularly new idea. See robotshare, robobrain or robot google