@itsolelehmann: something i feel like most people don’t know about, but that i’m very bullish on: world models for robotics. this is ho…

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Summary

World models for robotics enable faster and cheaper training by generating simulated footage, exemplified by LTX-2.5, to achieve advanced physical navigation in machines.

something i feel like most people don’t know about, but that i’m very bullish on: world models for robotics. this is how we'll speedrun robotics training. right now, teaching robots requires collecting huge amounts of footage from real machines operating in real environments (which is slow / expensive) but world models are AI video models that can generate simulated versions of that training footage (which is much faster and cheaper) so robots can practice across thousands of environments, failures, and rare edge cases *without* teams having to physically film every example. LTX-2.5 is one example: > generates video and audio of how a scene could unfold > can be adapted to robots, cars, drones, and factories > runs on infrastructure the company controls the endgame is machines that can navigate the physical world better than we do. (think full self-driving, but for every physical task)
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something i feel like most people don’t know about, but that i’m very bullish on:

world models for robotics.

this is how we’ll speedrun robotics training.

right now, teaching robots requires collecting huge amounts of footage from real machines operating in real environments (which is slow / expensive)

but world models are AI video models that can generate simulated versions of that training footage (which is much faster and cheaper)

so robots can practice across thousands of environments, failures, and rare edge cases without teams having to physically film every example.

LTX-2.5 is one example:

generates video and audio of how a scene could unfold can be adapted to robots, cars, drones, and factories runs on infrastructure the company controls

the endgame is machines that can navigate the physical world better than we do.

(think full self-driving, but for every physical task)

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