This looks to not be an openly available model, but I think if it were, availability of an easy single-camera navigation setup could allow for a lot of cool hobbyist projects.
If you're wondering what prevents or mitigates AI hallucinations on the AI layer from replicating or acting out on the physical layer look up QNX. They manage the deterministic reasonin gof robotics. You know them better as Blackberry.
It'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 to follow directions as long as they are interpretable from its current vision (or via dead reckoning).
Producing 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)
It seems like a stronger story for robotics, since smaller models can always react to the environment faster than large models for a given level of hardware resources. Also because robots that keep their models local for latency or robustness reasons aren't going to be carrying many kilowatts of inference capacity.
For a claim such as state of the art, or claims such as "great at any task" needs something of more substance. I've seen maze-solving robot competitions which can zoom around in seconds. The sped up video in the first part, and the "obstacle avoidance" are too slow for me to believe this is state of the art.
While impressive at 8B, what would the expectation be in real life, that it's run remotely or autonomously with a strapped on GPU and battery?
I've used that example as a contrast of what I've seen before. If you can point me at comparable efforts, in the same category as what Mistral is doing, I'd be interested in having a comparative look.
All I can think of are robot dogs, Tesla bots, and whatever flavor of the month Japanese robots show up at trade shows.
Ok, this is really cool. The fact that the robot can use pointing to decide where to go is a great design decision, and robotics really is the next frontier. Definitely cheering on Mistral here!
This looks to not be an openly available model, but I think if it were, availability of an easy single-camera navigation setup could allow for a lot of cool hobbyist projects.
If you're wondering what prevents or mitigates AI hallucinations on the AI layer from replicating or acting out on the physical layer look up QNX. They manage the deterministic reasonin gof robotics. You know them better as Blackberry.
It'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 to follow directions as long as they are interpretable from its current vision (or via dead reckoning).
Producing 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)
It seems like a stronger story for robotics, since smaller models can always react to the environment faster than large models for a given level of hardware resources. Also because robots that keep their models local for latency or robustness reasons aren't going to be carrying many kilowatts of inference capacity.
I expect the bitter lesson to continue to be bitter. Mistral must at least attempt to catch up to SOTA 6 months ago.
> 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!
Presumably it did not make it to the other Room.
No word on pricing or inference options i could see so not that interresting if it is not available to test.
For a claim such as state of the art, or claims such as "great at any task" needs something of more substance. I've seen maze-solving robot competitions which can zoom around in seconds. The sped up video in the first part, and the "obstacle avoidance" are too slow for me to believe this is state of the art.
While impressive at 8B, what would the expectation be in real life, that it's run remotely or autonomously with a strapped on GPU and battery?
it is state of the art, those maze solving things are a different art.
I've used that example as a contrast of what I've seen before. If you can point me at comparable efforts, in the same category as what Mistral is doing, I'd be interested in having a comparative look.
All I can think of are robot dogs, Tesla bots, and whatever flavor of the month Japanese robots show up at trade shows.
Ok, this is really cool. The fact that the robot can use pointing to decide where to go is a great design decision, and robotics really is the next frontier. Definitely cheering on Mistral here!
How long until Tesla buys Mistral?
I don't think so. I think Tesla merger with SpaceX, which has the Cursor team and reportedly working on foundation model there.
I imagine the EU would block any attempted takeover of Mistral given recent Anthropic and US govt actions.
Robots handle clean labs well; messy real‑world environments are still the real bottleneck.
Mistral seems to be going wide and niche. Could be a smart strategy going forward.
Maybe their LLMs are not the best but design is top-notch!
I love Uniqlo even more after seeing this.
Frontier labs are realizing that software/models themselves don’t have real moats and move to embodied ai.
SOTA 80% means a practically useless robot. What are they really imagining their ICP to be here?
What does this comment mean?
Was it tested on a road in a car ?
I'm ready for my home helper robot that makes dinner and does the dishes and takes out the trash.
But I'm scared for when those home helpers get drafted to fight in wars, either for or against me...
I suspect the latter will come way before the former...