MIT solved a century-old differential equation to break 'liquid' AI's computational bottleneck | Engadget
Briefly

IGphotography via Getty Images  Last year, MIT developed an AI/ML algorithm capable of learning and adapting to new information while on the job, not just during its initial training phase.These "liquid" neural networks (in the sense) literally play 4D chess - their models requiring time-series data to operate - which makes them ideal for use in time-sensitive tasks like pacemaker monitoring, weather forecasting, investment forecasting, or autonomous vehicle navigation.
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