Long live analog!

Link is not loading, probably due to DNS ad-blocking being blocked. Can someone save it to archive?

Here is an alt link: https://news.cornell.edu/stories/2025/08/researchers-build-f...

Alternative link from Cornell's website: https://news.cornell.edu/stories/2025/08/researchers-build-f...

Seems to be the press release for this article: https://www.nature.com/articles/s41928-025-01422-1

Anyone know where I can read it?

It seems it will still use some digital process to encode and decode whatever is transmitted or received, I could be misreading it.

I have always thought that digital killed analogue prematurely and unnecessarily. I hope this works out.

Surely mechanical clocks are digital in the sense that time is quantized into ticks by the escapement. The various gears do not rotate continuously.

Don't you just love how marketing has to slap a "AI" paragraph in there?

The bigger deal is 200mW for 30Ghz. Which incidentally... Is probably never going to be nice for modern AI.

> One example of an analog computer is a mechanical clock. It calculates that passage of time by means of springs, gears and an escapement that models the real world. Many other examples include slide rules (yes, I'm that old), speedometers, spring or liquid thermometers, and more.

What we call "computer" today is really a "general-purpose computer."

Although, personally I think it's a stretch of semantics to call a mechanical clock a "computer."

When I started to really get into robotics, mechanics, and automation back in the late 80s and early 90s, the fork in the road of Rodney Brooke's subsumption architecture, but still digital, approach versus Mark Tilden's BEAM analog approach really had me trying both.

CPGs (Central Pattern Generators) were often implemented using simple RC (resistor-capacitor) circuits within his "nervous net" (NvNet) architectures. The RC circuits generated rhythmic patterns that drove the robots' motor behaviors, allowing gaits to emerge naturally from the interaction of these analog components with the environment and the robot's mechanical structure. This approach enabled adaptive, robust locomotion without requiring complex digital control systems.

His 6-legged robots could lose a leg, and the system would take feedback from the stuck or missing leg, and learn to walk with 5 or 4 legs. Amazing stuff.