MIT’s new ‘liquid’ neural network learns on the job — so robots can adapt to changing conditions

MIT researchers have invented an adaptive “liquid” neural network that could improve decision-making in self-driving cars and medical diagnosis. The algorithm adjusts to changes experienced by real-world systems by changing their underlying equations as they receive new data. “This is a way forward for the future of robot control, natural language processing, video processing — any form of time series data processing,” said Ramin Hasani, the study paper’s lead author. “The potential is really significant.” [Read: How this company leveraged AI to become the Netflix of Finland] Hasani said the system is inspired by a tiny worm — the C. elegans: It…

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