Dynamically Typed

Decoding brain signals into text

DT #37 — April 12, 2020

Neurologists Joseph Makin et al. at UC San Francisco used a-250 electrode brain implant to decode human brain signals into text with techniques from machine translation—at a word error rate of only 3%. The implant technology won’t be widely usable anytime soon, if ever, but you can download the code it runs on anyway: jgmakin/machine_learning.

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Recent models, datasets, and tools for machine learning research.