“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
Same here. I wait to see real life calculations done by such circuits. They won’t be able to e.g. do a simple float addition without losing/mangling a bunch of digits.
But maybe the analog precision is sufficient for AI, which is an imprecise matter from the start.
You don’t need to simulate float addition. You can sum two voltages by just connecting two wires - and that’s real number addition
I know. My point was that this is horribly imprecise, even if their circuits are exceptionally good.
There is a reason why all other chips run digital…
How is it imprecise? It’s the same thing as taking two containers of water and pouring them into a third one. It will contain the sum of the precious two exactly. Or if you use gears to simulate orbits. Rounding errors are a digital thing.
Analog has its own set of issues (e.g. noise, losses, repeatability), but precision is not one of them. Arguably, the main reason digital took over is because it’s programmable and it’s good for general computing. Turing completeness means you can do anything if you throw enough memory and time at it, while analog circuits are purpose-made
So you list the reasons for imprecision: noise, losses, repeatability problems (there are more), but still consider it precise?
Adding two containers of water is only as precise as you can get leakage under control, and can rely on a repeatable shape of the containers. Both is something chip level logic simply does not deliver.
@Treczoks @flemtone Thing is, the final LLM inference is usually done at reduced precision. 8-16 bits usually, but even 4bits or lower with different layers of varying precision.