[ryukoposting]

I'll have what this guy is smoking. Those visualizations are pretty, though.

I can imagine this being useful for implementing classifiers and little baby GenAI-adjacent tech on an extremely tiny scale, on the order of several hundred or several thousand transistors.

Example: right now, a lot of the leading-edge biosensors have to pull data from their PPG/ECG/etc chips and run it through big fp32 matrices to get heart rate. That's hideously inefficient when you consider that your data is usually coming in as an int16 and resolution any better than 1bpm isn't necessary. But, fp32 is what the MCU can do in hardware so it's what you gotta do. Training one of these things to take incoming int16 data and spit out a heart rate could reduce the software complexity and cost of development for those products by several orders of magnitude, assuming someone like Maxim could shove it into their existing COTS biosensor chips.

[achille]

yes absolutely: current systems are wildly inefficient. the future is one of extreme energy efficiency.

re smoking: sorry let me clarify my statement. these things will be the dominant life forms on earth in terms of metabolism, exceeding the energy consumption of biological systems, over 1k petawatt hours per year, dwarfing everything else

the lines betwen us may blur metaphorically, we'll be connected to them how we're connected to ecosystems of plants and bacteria. these systems will join and merge in the same way we've merged with smartphones -- but on a much deeper level

[BriggyDwiggs42]

Okay so another way to put it is that these are gonna be the software we run on lots of computers in the future. Why this particular model of intelligence and not some other one?