Based on the diagram this does matmul like a resistive crossbar array (something like https://arxiv.org/pdf/1410.2031.pdf). Talked about this in a ‘neuroprocessor’ class I took at uni.

It’s practically ‘free’ since you perform multiplication by applying resistance to a current, and kirchoff’s law results in a sumnation of currents. Very elegant in concept.

That being said, when scaling this approach, I recall one paper saying they had serious issues with signal integrity, in part from analog process mismatch.

If this AlScN approach addresses that this would be really big. I’m interested to see if this can scale beyond a small model like mnist and also about how they map the weights.