One big difference between LLM progress and robotics
is that language models benefited from purely digital
feedback loops — training, testing, and scaling could
all happen in simulation.
Robotics still pays a heavy “reality tax”.
Every improvement eventually has to survive messy,
unstructured physical environments where sensing,
actuation, and safety interact in unpredictable ways.
My guess is we’ll see a ChatGPT-like moment first in
semi-structured environments (warehouses, logistics,
industrial assistance) rather than homes.
A general household robot feels closer to a GPT-4
equivalent problem than a GPT-3.5 one because reliability
matters much more when failure affects the physical world.
Robotics still pays a heavy “reality tax”. Every improvement eventually has to survive messy, unstructured physical environments where sensing, actuation, and safety interact in unpredictable ways.
My guess is we’ll see a ChatGPT-like moment first in semi-structured environments (warehouses, logistics, industrial assistance) rather than homes.
A general household robot feels closer to a GPT-4 equivalent problem than a GPT-3.5 one because reliability matters much more when failure affects the physical world.