INSUBCONTINENT EXCLUSIVE:
OctoML, a startup founded by the team behind the Apache TVM machine learning compiler stack project, today announced it has raised a $15
million Series A round led by Amplify, with participation from Madrona Ventures, which led its $3.9 million seed round
The core idea behind OctoML and TVM is to use machine learning to optimize machine learning models so they can more efficiently run on
Washington professor Luis Ceze told me
Allen School of Computer Science - Engineering
Google, Intel, Microsoft, Nvidia, Xilinx and others, the team decided to form a commercial venture around it, which became OctoML
ways in which you can map a model to specific hardware targets
Users can upload their model to the service and it will automatically optimize, benchmark and package it for the hardware you specify and in
These optimized models run significantly faster because they can now fully leverage the hardware they run on, but what many businesses will
maybe care about even more is that these more efficient models also cost them less to run in the cloud, or that they are able to use cheaper
hardware with less performance to get the same results
For some use cases, TVM already results in 80x performance gains.Currently, the OctoML team consists of about 20 engineers
With this new funding, the company plans to expand its team
He also noted that while the Octomizer is a good start, the real goal here is to build a more fully featured MLOps platform
