> achieves 76.6% on R2R-CE (Room-to-Room in Continuous Environments) I would like to know what it did the other 23.4% of the time!
maybe it did a cartwheel instead of turning right.
Mistral's Robostral Navigate: a state of the art robotics navigation model
41–50 of 117 posts
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#428B sounds tiny. Of course, that's enough to easily run on device which is nice, but surely the actual SOTA must be some much bigger model?
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#43This is very cool. Congratulations to the Mistral team. Map less navigation in the outside world has been around for quite a while. But map less navigation inside the buildings is relatively new. Some stanford researchers trained a vision model (PIGEON) which could tell the geo-location from any image. It was not released publicly due to privacy nightmarish (stalking!) possibilities but I am assuming similar type of tech has gone behind this robot. if someone knows more, feel free to correct.
here's the link to the PIGEON paper - https://lukashaas.github.io/PIGEON-CVPR24/
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#44Producing specific niche models for 100 year old industries that have mountains of data and warehouses full of folders will be the european take on AI. It may come late but it‘ll be safe and reliable. It also requires a lot of OCR.
The Niche model story is still fairly week. Evidence points to general models being equally capable to niche models at a more attractive capex (risk is spread across multiple verticals rather than concentrated in a single model capability)
We are making a niche model that we're now expanding. You'd be surprised how the general models suck for anything vision-related.
And even if you use all the tricks in the book to make them work for you, the cost can easily be 1000 _times_ more than the specialized model. Ditto for speed.
This is especially important for things like robotics or navigation.
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#45> achieves 76.6% on R2R-CE (Room-to-Room in Continuous Environments) I would like to know what it did the other 23.4% of the time!
Random, horrendous and indiscriminate killing!
[/joke]
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#46It's implied, and I'm hoping it's true, that this is a map-less navigation. Which is impressive. This kind of task is much easier if you have a pre-captured map of the environment, but if they are doing this without a map it's great. Historically you were always faced with "The Kidnapped Robot" problem where robots that didn't know where they were couldn't navigate even a little bit. Here the robot appears to be able…
I am working in Mistral robotics team. I confirm this is map-less. The only inputs are the text prompt and the front camera rgb image.
So, it has to rely on exact situational step by step commands? I'm wondering how one could conceivably deploy this in a useful way. Usually you'd need to mark areas on the map and then the robot knows where to go, A* is trivial around obstacles once you have that and a lidar. And lidars are an order of magnitude cheaper than something that can run an 8B VLA.
One could maybe autogenerate these text planning commands, but it would require a map and the robot's current location, so it doesn't really solve that, unless it can find a specific thing completely on its own. How much of a planning horizon does it have?
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#47> achieves 76.6% on R2R-CE (Room-to-Room in Continuous Environments) I would like to know what it did the other 23.4% of the time!
"Go to the next room" and there is two doors, what do you do ?", "turn at the water dispenser" and there is a sink, that sort of things I assume is the biggest thing they're facing (beside the last 1% that's worth another 99%, as usual).
On their page where the result graph is, go to navigation error, that's the one that matters for your question, and you see their model is great at not navigating "wrong", so their failure rate was that it couldn't figure it out.
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#48Producing specific niche models for 100 year old industries that have mountains of data and warehouses full of folders will be the european take on AI. It may come late but it‘ll be safe and reliable. It also requires a lot of OCR.
The Niche model story is still fairly week. Evidence points to general models being equally capable to niche models at a more attractive capex (risk is spread across multiple verticals rather than concentrated in a single model capability)
The cost is getting worse and worse for large general models, they're already way past that point in economics. Also, mMistral specialize in "on site" models, not remote. In terms of capex, renting factory/warehouse/whatever robots versus buying them and depreciate has already been played out, companies didn't want to replace human employees with robots employees.
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#49> achieves 76.6% on R2R-CE (Room-to-Room in Continuous Environments) I would like to know what it did the other 23.4% of the time!
"Go to the next room" and there is two doors, what do you do ?", "turn at the water dispenser" and there is a sink, that sort of things I assume is the biggest thing they're facing (beside the last 1% that's worth another 99%, as usual). On their page where the result graph is, go to navigation error, that's the one that matters for your question, and you see their model is great at not navigating "wrong", so their f…
I hope they put out a blooper reel.
Re: Mistral's Robostral Navigate: a state of the art robotics navigation model
#50Mistral seems to be going wide and niche. Could be a smart strategy going forward.
It's potentially a great strategy. They can't keep up with Antropic and OpenAI in pure horsepower, but there's just tons of applications for which you don't need that much power and it's better to optimize for speed and energy.