Closing the “Sim-to-Real Gap” Is the Next Big Challenge in AI
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One of the biggest hurdles in robotics today is making sure what works in simulation actually works in reality — known as the “sim-to-real gap.” Companies like Antioch are focused on solving exactly that.
By creating highly realistic environments powered by models from players like Google DeepMind, these platforms aim to make robot training more reliable and scalable. If successful, this could dramatically speed up the development of autonomous systems — from self-driving vehicles to industrial robots — and reshape how physical AI is built.
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yeah let’s just pretend physics works perfectly in simulation, easy