Energy Economy AI: The Prime Challenge and How to Meet it

Left to the current trend, AI, using "Brute Force" computing is gradually depleting power generation stations which are needed in places where they cannot be avoided. This defines "Energy Economy AI" as the challenge of the day.

The BitMint team is working on matching data resolution to decision difficulty, and expecting to thereby cut power reequreemnt by 2/3! Today AI engines over-analyze simple cases and under-analyze complex cases. There are more simple cases than there are complex cases. The solution: limit the data consumption for simple cases. To do this we capture a situation with a uniform mathematical framework that merges the concepts of space and time, as well as redefining time and energy. This "Neighborhood" framework is then applied in low resolution and subsequently analyzed with inference engines. If the result is of poor credibility, the resolution of capturing the state is increased, new inference applied, and credibility checked again. And so on, stopping when credibility reached a pre set threshold.

The most ambitious objective for this energy economy AI is breaking through the Darwin's barrier, and discovering the new physics that lays hidden so far.