It's been in development for a while: https://ieeexplore.ieee.org/abstract/document/1396377?casa_token=-gOCNaYaKZIAAAAA:Z0pSQkyDBjv6ITghDSt5YnbvrkA88fAfQV_ISknUF_5XURVI5N995YNaTVLUtacS7cTsOs7o
Even before the above paper, I recall efforts to connect (rat) brains to computers in the late 90s/early 2000s. https://link.springer.com/article/10.1023/A:1012407611130
It's a bunch of neurons that speak to a computer with a microelectrode array. So they "speak to" the neurons with electric impulses, and then "listen to" what they have to say. The computer it's connected to uses binary, but the neurons are somewhere in between. Yes, the change in electrical potential is analog, but neurons are typically in their "on" state, recovering from their "on" state, or just chilling out.
The brain is incredible because of the network of connections between neurons that store information. It'll be interesting to see if a small scale system like this can be used for anything larger scale.
Believe it or not, I studied this in school. There's some niche applications for alternative computers like this. My favorite is the way you can use DNA to solve the traveling salesman problem (https://en.wikipedia.org/wiki/DNA_computing?wprov=sfla1)
There have been other "bioprocessors" before this one, some of which have used neurons for simple image detection, e.g https://ieeexplore.ieee.org/abstract/document/1396377?casa_token=-gOCNaYaKZIAAAAA:Z0pSQkyDBjv6ITghDSt5YnbvrkA88fAfQV_ISknUF_5XURVI5N995YNaTVLUtacS7cTsOs7o. But this seems to be the first commercial application. Yes, it'll use less energy, but the applications will probably be equally as niche. Artificial neural networks can do most of the important parts (like "learn" and "rememeber") and are less finicky to work with.
Thanks for the recommendation, I was worried they would be missing some of my artists but they had 99% of my music. Can't wait to ditch Spotify.
ETA: dear lord the sound quality is so much better. I had no idea what I was missing.
In grad school I worked with MRI data (hence the username). I had to upload ~500GB to our supercomputing cluster. Somewhere around 100,000 MRI images, and wrote 20 or so different machine learning algorithms to process them. All said and done, I ended up with about 2.5TB on the supercomputer. About 500MB ended up being useful and made it into my thesis.
Don't stay in school, kids.