Yeah, I get the marketing perspective; just, we typically describe primitive data types in terms of what they are from a technical perspective rather than a marketing perspective.
fp16 & fp8 refer to IEEE 754 floating point which has notable differences from bfloat16 & make them have worse performance for machine learning.
Yeah the point is 'reduced precision FP16' would make a lot more sense - since it actually describes what it does. 'Brain' floating point makes you wonder how Neuralink are planning to use this datatype.