From one piece Chelsea Finn: This is the State of the Art in Robotics 8 beliefs, in the piece's order there
-
Their words
But I think the PhD is an incredible opportunity to first learn a lot about how to handle uncertainty, how to pick good problems to work on.
-
Their words
I mean at the very least I actually think that just starting with a generalist policy and then fine-tuning it even like right off the bat uh can be really effective.
-
korrents.com
Robot models will reach ChatGPT-level capability within the next few years, even without a ChatGPT-style moment.Their words
at the same time in terms of the capabilities of these models I think that we are really starting to get to the point where these models are actually useful in the real world and I think that getting to the kind of the capabilities of chat GBT I think is um yeah very much on the horizon in the next few years.
+ 5 more
-
Their words
I think that the distribution channel for physical models is going to be slower uh unfortunately because you actually need a physical robot there
-
korrents.com
A model you have to fine-tune for each thing you want it to do is not a general-purpose model.Their words
But if you have to fine-tune a model, you actually aren't getting a general purpose model um for the things that you want it to do because you have to fine-tune it for each individual thing.
-
Their words
Um, and while this generally improves the reliability of the model, uh, people eventually get tired and it's hard to get really, really high reliability with a person that's manually tuning this. And so what would be even better is if the AI system itself can iterate on the scenario in which you want it to have higher reliability where it on its own automatically seeks out places where it needs more data, where it needs more supervision.
-
Their words
Uh and this means that they're going to be far more useful when they're operating fully autonomously. And as a result, this requires us to develop physical AI systems that make far fewer mistakes than the machine learning systems that have been deployed thus far.
-
Their words
And in all of these applications, the customer is making a decision based off of the recommendation of the AI model more or less. Uh, and this means that if the customer is ultimately like kind of making the decision, this means that if the system makes a mistake, um, that's okay because usually the person can kind of recognize that or or decide what to do even despite that mistake.