The entire industry is racing to make AI cheaper. Most people assume the answer is better chips or bigger GPU clusters. However, while the industry is buying its next 2× when there's a 1.78× speedup is sitting in the software.
We've been hard at work @unifiedsciences, building an autonomous optimization engine toward radically more efficient compute.
Today I'm very happy to share some early results where our unified engine:
1) wrote faster GEMM kernels for cuBLAS (up to 1.78x faster)
2) made an efficient AI model 6x smaller and 5x faster without any quality loss
3) optimized diverse everyday AI workloads on a consumer GPU!