“The new device is built from arrays of resistive random-access memory (RRAM) cells… The team was able to combine the speed of analog computation with the accuracy normally associated with digital processing. Crucially, the chip was manufactured using a commercial production process, meaning it could potentially be mass-produced.”
Article is based on this paper: https://www.nature.com/articles/s41928-025-01477-0
Thank you for the link, it was very interesting.
Even though analogue neural networks have the drawback that you can’t copy the neuron weights (currently, but tech may evolve to do it), they can still have use cases in lower powered edge devices.
I think we’ll probably end up with hybrid designs, using digital for most parts except the calculations.
For low power neural nets look up “spiking neural networks”