Assuming that models continue to get 90% more efficient every 18 months, and assuming that hardware continues to get 2x more powerful per watt every 2 years...
Aren't we still like a decade away from an Argon model being able to run on battery power for any reasonable amount of time that would fit on a robot that isn't the size of a school bus?
Add on another couple of years for the speed to get to what it likely needs to be to be generally useful instead of narrowly useful?
I mean - I guess we're maybe 5-7 years away from a reasonably priced robot you could plug into the wall like an old vacuum cleaner (that runs on this type of tech).
I think for 95%+ of applications.. you just need a link to a data center anywhere.
My assumption is the hardware will have one/several smaller models running on it for locomotion, balance, etc.
Then the hardware "phones home" for decision making and planning.
Essentially the planning doesn't need to be close to the device as long as the local models can handle some part of the plan execution and make sure the robot doesn't fall over. The latency shouldn't be an issue. In fact more powerful centralized compute quickly creates an advantage over slower local compute in terms of end to end planning.
I'm naive, but wouldn't industrial applications be enabled by this anyway? You'll have in-house inference hardware that a robot can talk to via local network.
Also, your model probably doesn't need like a lot of its knowledge to control a robot.
That's only bringing up the horizon maybe 1 year. At industrial scale - I guess something like an Amazon warehouse could start to be interesting with a local datacenter IN the warehouse within 2-3 years.
From a cost perspective, I just can't imagine that heavily, heavily specialized models wouldn't crush a general model, though - which Amazon already does.
Assuming that models continue to get 90% more efficient every 18 months, and assuming that hardware continues to get 2x more powerful per watt every 2 years...
Aren't we still like a decade away from an Argon model being able to run on battery power for any reasonable amount of time that would fit on a robot that isn't the size of a school bus?
Add on another couple of years for the speed to get to what it likely needs to be to be generally useful instead of narrowly useful?
I mean - I guess we're maybe 5-7 years away from a reasonably priced robot you could plug into the wall like an old vacuum cleaner (that runs on this type of tech).
I think for 95%+ of applications.. you just need a link to a data center anywhere.
My assumption is the hardware will have one/several smaller models running on it for locomotion, balance, etc.
Then the hardware "phones home" for decision making and planning.
Essentially the planning doesn't need to be close to the device as long as the local models can handle some part of the plan execution and make sure the robot doesn't fall over. The latency shouldn't be an issue. In fact more powerful centralized compute quickly creates an advantage over slower local compute in terms of end to end planning.
I'm naive, but wouldn't industrial applications be enabled by this anyway? You'll have in-house inference hardware that a robot can talk to via local network.
Also, your model probably doesn't need like a lot of its knowledge to control a robot.
That's only bringing up the horizon maybe 1 year. At industrial scale - I guess something like an Amazon warehouse could start to be interesting with a local datacenter IN the warehouse within 2-3 years.
From a cost perspective, I just can't imagine that heavily, heavily specialized models wouldn't crush a general model, though - which Amazon already does.
And? 5-7 years is nothing at the scale of our modern society and the outcome of what you describe could be enormous.
I don't disagree.
It just seems like jumping the shark a little bit.
It's basically completely unviable for a few years still.
It's viable today via network.
I don't think it's viable in the sense that they are still in a demo stage.
Also, I would assume these models are going to get bigger before they get smaller (but they will get smaller over the long run)
> It's viable today via network.
For a set of tasks that almost no one would use a robot for...