At @hackwithtrees, we built a project that retrofits self-driving into ANY car, powered by the Jetson Thor. Won 1st place on @nvidia’s edge AI track! 🥳
Went from organizing last year to competing this year and it honestly hit different 🥹 love this community 💚
Links below!
@sophiecliffa8@ScalingIntelLab@kkaitlyn111 Thanks for your input Soph! Chief artist is a #real#position at this lab. We use them to generate a controllable corpus of images with supervision. This is used to #fine-tune our #VLM, resulting in a model with improved compositional visual understanding in #anime.
@stuart_sul wow congrats! are there any plans to port over these ideas to amd gpus w/ hipkittens? i've been working on this recently, although the communication-computation overlap methods may be quite different 😅
We're open-sourcing Mixture-of-Kittens (MoK), our MoE training megakernel for NVL72s.
It fuses all Mixture-of-Experts communication and computation into a single, fully deterministic kernel, and runs up to 2.37x faster than the strongest public baselines.
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Kinda wild that our community got together and collectively made Kimi inference on MI355X faster than B200 across all settings. Congrats to the winners team RadeonFlow and thanks again to AMD for working so closely with our community