'Dataflow Architectures for AI' is a 6-course specialization from IBM Research that compares leading accelerator architectures through hands-on labs.

Open models and llm-d enabled IBM Research to explore quantum error correction hardware at 11.5× lower inference cost than an all-proprietary configuration.