The speaker describes the historical compute allocation as roughly 50% research, 10% model development, and 40% inference, equivalent to training accounting for about 60% and inference 40%.

“um then you know let's say 60 or so far it's been like 60 percent training 40 percent inference but that training gets broken down further and that's actually like 50 percent of the compute is research like 10 percent of the compute is development and then 40 percent is inference and what i mean by research and development is you know researchers are generating ideas testing new architectures testing new data mixes testing new hyper parameters whatever it is they're doing new attention techniques”