[ly3xqhl8g9]

The most off the beaten path to AGI I heard through the grapevine is to not have artificial neural networks, as in algorithms involving matmul running on silicon, at all. But instead, going on the path of the laziest engineer is the best engineer, to rely on the fact that neurons, actual neurons from someone's brain, already "know" how to make efficient, good-enough, general learning architectures and therefore in order to obtain programmatic human-like intelligence one would 'simply'† have to implant them not in mice [1] but in an actual vat and 'simply' interface with the whatever a group of neurons can be called, a soma(?). Given this Brain-on-a-Chip architecture, we wouldn't have to stick GPUs in our cars to achieve self-driving, but even more wetware (and of course, ignore the occasional screams of dread as the wetware becomes aware of themselves and how condemned they are to an existence of left-right-accelerate-break).

It would have been interesting seeing someone like Carmack going in this direction, but from the little details he gave he seems less interested in cells and Kjeldahl flasks and more of the same type-a-type-a on the ol' QWERTY.

† 'simply' might involve multiple decades of research and Buffett knows how many billions

[1] Human neurons implanted in mice influence behavior, https://www.nature.com/articles/s41586-022-05277-w