jetsamflotsam

Datatype requirements vary in time and space for a given application. We're just beginning to optimize for this, so there is yet much to discover.

Exactly. Being precise about logarithmic vs linear utilizations is key here. I tried making a similar point about the inefficiency of IEEE-754 redundant NaN encodings here: https://arxiv.org/pdf/2508.05621

Having ~a quadrillion redundant bitstrings all mapping to NaN sounds pretty bad, but logarithmic/information utilization-wise, this is actually not too bad.

I feel like many of the comments missed the point or didn't read the article. What I believe this article is stating (and I've read this many times during my PhD for various reasons), is that the input data distributions affect how many transistor state changes there are during multiplication. Since these events are a large portion of energy loss/heat generation, the clocks won't be throttled as much for certain data patterns.

There was a workshop paper from SC24 that did more experiments around this I believe. I can't find it now though.

Yeah I'm not sure how to put this into words either, but I feel you. Do you know of any good AI "thought-leader" that's sensible and not AI-pilled or a complete doomer? Some reasonable middle-ground that helps us navigate an era of immense technological innovation?