Category Archives: image recognition

Next discussion meeting Apr 2: Brain-Computer Interface, now and future

During our next discussion meeting, we’ll explore the status, future potential, and human implications of neuroprostheses–particularly brain-computer interfaces. If you are local to Albuquerque, check our Meetup announcement to join or RSVP. The announcement text follows.

Focal questions

What are neuroprostheses? How are they used now and what may the future hold for technology-enhanced sensation, motor control, communications, cognition, and other human processes?

Resources (please review before the meeting)

Primary resources
• New Brain-Computer Interface Technology (video, 18 m)
https://www.youtube.com/watch?v=CgFzmE2fGXA
• Imagining the Future: The Transformation of Humanity (video, 19 m)
https://www.youtube.com/watch?v=7XrbzlR9QmI
• The Berlin Brain-Computer Interface: Progress Beyond Communication and Control (research article, access with a free Frontiers account)
https://www.frontiersin.org/articles/10.3389/fnins.2016.00530/full
• The Elephant in the Mirror: Bridging the Brain’s Explanatory Gap of Consciousness (research article)
https://www.frontiersin.org/articles/10.3389/fnsys.2016.00108/full

Other resources (recommend your own in the comments!)

• DARPA implant (planned) with up to 1 million neural connections (short article)
https://www.darpa.mil/news-events/2015-01-19

Extra Challenge: As you review the resources, think of possible implications from the perspectives of the other topics we’ve recently discussed:
• the dilemma of so much of human opinion and action deriving from non-conscious sources
• questions surrounding what it means to ‘be human’ and what values we place on our notions of humanness (e.g., individuality and social participation, privacy, ‘self-determination’ (or the illusion thereof), organic versus technologically enhanced cognition, etc.)

Brain’s facial-recognition mechanism revealed

Caltech researchers have identified the brain mechanisms that enable primates to quickly identify specific faces. In a feat of efficiency, surprisingly few feature-recognition neurons are involved in a process that may be able to distinguish among billions of faces. Each neuron in the facial-recognition system specializes in noticing one feature, such as the width of the part in the observed person’s hair. If the person is bald or has no part, the part-width-recognizing neuron remains silent. A small number of such specialized-recognizer neurons feed their inputs to other layers (patches) that integrate a higher-level pattern (e.g., hair pattern), and these integrate at yet higher levels until there is a total face pattern. This process occurs nearly instantaneously and works regardless of the view angle (as long as some facial features are visible). Also, by cataloging which neurons perform which functions and then mapping these to a relatively small set of composite faces, researchers were able to tell which face a macaque (monkey) was looking at.

These findings seem to correlate closely with Ray Kurzweil’s (Google’s Chief Technology Officer) pattern-recognition theory of mind.

Scientific American article

BMCAI library file (site members only)

Excellent article on the history and recent advances in AI

This NY Times article is worth your time, if you are interested in AI–especially if you are still under the impression AI has ossified or lost its way.