What does this mean? My guess is they couldn’t co-locate Mythos close enough to reduce latency?
(I’m assuming this experiment pre-dates the export controls)
I doubt network latency is the reason. Even when connecting from literally across the world network latency is lost in the noise of overall response latency of even fast models.
The overall response latency of the model very well could have been the difference, though. AFAIK Mythos is structured to do relatively slow "deep thinking".
Here's how non robotics engineers used AI to do a short robot integration task faster than other non robotics engineers without AI.
Where "better" mostly means faster, and who knows what happens on longer horizons, with actual robotics experts, robustness requirements, or tasks where the hard part is control rather than API spelunking.
It’s good they are the one seeing those things because otherwise no one else would have. Now if only seeing things would translate into getting any actual economic value out of them… instead of losing billions. But hey, who am I to do a reality check on this shameless piece of hype.
