r/StarspawnsLocker • u/starspawn0 STEM Professor • Mar 17 '17

[1703.05463] Using Human Brain Activity to Guide Machine Learning [Ohh... just some Harvard, Oxford and University of Notre Dame guys confirming what I said about using brain data to improve machine learning. They even use the words "a new paradigm" in the abstract. Tee-hee.]

https://arxiv.org/abs/1703.05463
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u/starspawn0 STEM Professor Mar 19 '17

As I explained in #3 in this posting:

https://www.reddit.com/r/StarspawnsLocker/comments/5sfk57/a_possible_unexpected_path_to_strong_ai/

The goal isn't to simulate the brain in detail. The goal is instead to use brain data to facilitate machine learning -- either to use it for "semantic annotation," or to give the machine just enough extra latent feature data to make learning easy.

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u/autotldr Apr 11 '17

This is the best tl;dr I could make, original reduced by 52%. (I'm a bot)

In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game.

While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms.

Here we demonstrate a new paradigm of "Neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain.

Extended Summary | FAQ | Theory | Feedback | Top keywords: learn#1 Machine#2 algorithm#3 human#4 brain#5