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I'm somewhat intrigued by this study https://www.eurekalert.org/pub_releases/2019-11/bcom-dnn110419.php

One innovation is to use a "mesoscope" to measure the activity of a large number of neurons simultaneously. This is the kind of development I've been waiting for.



First, measure the activity of neuron populations in response to thousands of images.

Then develop an artificial neural net to mimic that neural activity.

Then, give the artificial neural net new images, and see how its simulated neurons respond.

Compare the simulated output to how brains respond to those same images.


"To test whether the network had indeed learned to predict neural responses to visual images like a living mouse brain would do, we showed the network images it had not seen during learning and saw that it predicted the biological neuronal responses with high accuracy,"


If the method continues to work with other brain data, this could accelerate both AI and brain modeling.

(Whether this leads to good or evil is another question)

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Robots failed for Tesla and now Boeing. Humans are re-introduced to the factory.

"... the planemaker struggled to keep the robots moving in sync on the outside and inside of the fuselage panels, creating production snarls..."



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The evolution of cat and mouse begins...

"Their system advances ongoing efforts to develop fully automated technology capable of detecting fake news by achieving 90 per cent accuracy in a key area of research known as stance detection.

Given a claim in one post or story and other posts and stories on the same subject that have been collected for comparison, the system can correctly determine if they support it or not nine out of 10 times.

That is a new benchmark for accuracy by researchers using a large dataset created for a 2017 scientific competition called the Fake News Challenge."



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