81–90 of 117 posts
> 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]
Made a comment that needed an additional tag because the joke might be getting a little too real in the near future
REWARD?
+5 to Foresight
On the other hand it reminds me of 2010ish robotic demo videos from academic researchers and willow garage.
Problem with robotics is usually that it's easy to produce a good-enough looking demo, but it's really hard to make somethin work in the general case. As exemplified by autonomous driving.
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Please oh please try to make Kärcher adopt your stuff. Even their latest premium cleaning bots are hopeless when they don't know where they are, even when I tell them where they are. Or, I don't know, make your own vacuums.
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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…
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.
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This is Mistral though. I assume the model can be run locally.
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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.
Nice! Thanks for confirming. If the last instruction is 'go back to where you started' does it work?
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The General Models' business-model is also looking more weak every iteration. Costs of simple tasks grow extensively: OCR with "Mistral OCR" at $4 per 1000 pages vs OCR with Opus 4.8 at sometimes¹ $1 per "page". Or just the immense costs when burning tokens in an unoptimized agentic coding environment costing tens of dollars for a few simple classes or functions versus a highly optimized "autocomplete" model costing…
the counter point is that building or selecting the specialized model may cost as much as the lifetime inference costs of the task with the specialized model. If I need to pay someone 300k to make the model and infrastructure... then I would need to process many documents to recoup my OCR costs compared to asking claude code nicely. Perhaps the model zoo is becoming good enough that the cost to find a specialized mod…
I mean, I also I think the "agentic calendar assistant" is more likely to come out of the Valley than Europe[1] and that the big AI startups will buy some of the niche AI startups gaining traction in strategic markets, but there are lots of niches that notionally benefit from transformer-based models
[1]probably a calendar assistant with a ludicrously inflated valuation based mostly on the assumption that Google/Meta/Anthropic will buy them to shut them down three years later...
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This is Mistral though. I assume the model can be run locally.
So the vacuum cleaner manufacturer would just require customers to install mistral on their local LLM hostbox? Or maybe they'd sell you a host to go with it you couldn't get into and honest cross fingers we aren't peeking!
I wish we lived in the alternate universe where everybody has a home server that could run this sort of thing.