Shelly Fan in Singularity Hub:
A tiny ball of brain cells hums with activity as it sits atop an array of electrodes. For two days, it receives a pattern of electrical zaps, each stimulation encoding the speech peculiarities of eight people. By day three, it can discriminate between speakers. Dubbed Brainoware, the system raises the bar for biocomputing by tapping into 3D brain organoids, or “mini-brains.” These models, usually grown from human stem cells, rapidly expand into a variety of neurons knitted into neural networks.
Like their biological counterparts, the blobs spark with electrical activity—suggesting they have the potential to learn, store, and process information. Scientists have long eyed them as a promising hardware component for brain-inspired computing. This week, a team at Indiana University Bloomington turned theory into reality with Brainoware. They connected a brain organoid resembling the cortex—the outermost layer of the brain that supports higher cognitive functions—to a wafer-like chip densely packed with electrodes.
The mini-brain functioned like both the central processing unit and memory storage of a supercomputer. It received input in the form of electrical zaps and outputted its calculations through neural activity, which was subsequently decoded by an AI tool. When trained on soundbites from a pool of people—transformed into electrical zaps—Brainoware eventually learned to pick out the “sounds” of specific people. In another test, the system successfully tackled a complex math problem that’s challenging for AI.
More here.