OctoML

The first hardware target from our collaboration with is now available in OctoML! Check out why the Cortex-A72 processor could be a perfect fit for your edge machine learning deployments.

https://octoml.ai/blog/accelerating-machine-learning-at-the-edge-arm-cortex-a72

Earlier this week at , Phil Mazenett presented a short demo of how OctoML and VMware work better together with OctoML delivering ML model acceleration and VMWare providing great infrastructure to run AI at high performance.

Check it out:

OctoML and VMware - Better Together Demo Earlier this week at VMworld, we presented a short demo of how OctoML and VMware work better together with OctoML delivering ML model acceleration and VMWare...

The MLPerf results released this week contain the first two pioneering inference benchmarks accelerated via Apache TVM and automated with the MLCommons Collective Knowledge framework.

We’re creating a blueprint for future submissions that will be completely vendor, hardware and ML framework agnostic - while still delivering world-class results. Join us:

OctoML joins the community effort to democratize MLPerf inference benchmarking OctoML enters the MLPerf inference benchmark with the first two submissions accelerated via Apache TVM and automated with MLCommons' Collective Knowledge framework.

Want more hardware options for deploying your machine learning models to production?

OctoML now supports inferencing targets from multiple clouds to the edge, including hardware from leading industry vendors like AWS, GCP, NVIDIA, AMD, Arm, and Intel.

OctoML expands deployment choice with new multi-cloud and edge targets The OctoML Deployment Platform now supports inferencing targets from the cloud to the edge, including hardware from industry vendors like AWS, GCP, NVIDIA, AMD, Arm, and Intel.