Right now the way the TOP500 measures speed is in FP64. But lower-precision computing (e.g., FP8, FP16) is becoming more relevant for ML workloads.

This resolves positively iff the TOP500 switches its primary ranking methodology to measure computational speed in something less precise than FP64. "Primary" will refer to the most prominently displayed list on top500.org, so if a less prominent methodology uses FP(n<64), but the most prominent list still uses FP64, this resolves no. I will use my judgment in assessing prominence.

I will not bet in this market.