Major updates to its Kernels project, which standardizes how custom GPU kernels are packaged, distributed, and consumed.
The release adds trusted kernel publishers, kernel signing, revamped command-line tooling, and improved coverage across frameworks and backends.
As custom kernels become more important for model performance, safer packaging and distribution are becoming part of the AI infrastructure stack rather than a niche optimization detail.