Standard Kernel Co. retweeted
We have a utilization problem.
GPUs are running <30% capacity.
@Standard_Kernel (@anneouyang + @ChrisRinard ) unlocks up to 4x performance.
Why we invested: jumpcap.com/insights/why-we-…
Standard Kernel Co. retweeted
AI progress increasingly depends on how efficiently workloads run on hardware.
@Standard_Kernel is tackling this challenge at the kernel level, unlocking more performance from modern GPUs.
We're proud to lead their seed with @generalcatalyst, @CoreWeave, @felicis, & @ericsson
Standard Kernel Co. retweeted
It’s rare to find founders so perfectly and uniquely suited to solve a problem, let alone a problem of this magnitude and importance. Proud to lead @Standard_Kernel’s seed round.
Excited to share @Standard_Kernel's seed round and some reflections on what we’ve learned about kernel generation and what we believe is next. Grateful to our amazing team, supporters, and the broader community pushing this space forward.
Standard Kernel Co. retweeted
Anne is killing it. Here's my quote from the press release
Kernel generation is key for improving performance and efficiency of AI hardware. As fleet sizes for users of AI hardware get larger, and more hardware diversity is introduced, Standard Kernel becomes key to deployment.”
Excited to share @Standard_Kernel's seed round and some reflections on what we’ve learned about kernel generation and what we believe is next. Grateful to our amazing team, supporters, and the broader community pushing this space forward.
Standard Kernel Co. retweeted
Excited to share @Standard_Kernel's seed round and some reflections on what we’ve learned about kernel generation and what we believe is next. Grateful to our amazing team, supporters, and the broader community pushing this space forward.
Standard Kernel Co. retweeted
Excited to share what friends and I have been working on at @Standard_Kernel
We've raised from General Catalyst (@generalcatalyst), Felicis (@felicis), and a group of exceptional angels.
We have some great H100 BF16 kernels in pure CUDA+PTX, featuring:
- Matmul 102%-105% perf of cuBLAs in 100 lines of code
- Attention 104% perf of FlashAttention3 in 500 lines
- Fused Llama3 FFN 120% perf of PyTorch (gpt-fast)
Reach out if you want to work on AI kernel gen with us!













