Over 54 days of Llama 3 405B pre-training, the job was interrupted 466 times, roughly once every three hours. At that failure rate the checkpoint interval barely matters; what decides how much of a sixteen-thousand-GPU cluster do…
A 75% idle GPU is usually not a compute problem. Across the configurations one VLDB study measured, DNN training spent between 10% and 70% of every epoch blocked on I/O, and the storage system was not busy. The data path has its …
Two servers run the same model on the same GPUs. One reports 4,200 tokens per second and is unusable; the other reports 2,600 and feels instant. Throughput is a property of the server, latency is a property of the request, and th…
A frontier model can write a function. An agentic runtime can read a codebase, plan a migration, edit forty files, run the tests, fix what broke, and open a pull request. The difference is not intelligence; it is the system that …
Data-parallel training all-reduces the entire gradient after every step, which is why frontier pretraining happens inside one building with a purpose-built fabric. DiLoCo synchronises every five hundred steps instead of every one…
One workflow, 150,000 tokens down to 2,000. A subagent that burns fifty thousand tokens and returns fifteen hundred. A hundred installed skills that cost two thousand tokens until one is needed. Four separate advances, four separ…
A fraud model can score perfect recall offline and block nothing in production, because its training join looked a few hours into the future. Feature stores exist to enforce one contract: a training row may only see what the serv…