Today OctoML, provider of a machine learning acceleration platform, released a major platform expansion in order to accelerate the development of AI-powered applications by eliminating bottlenecks in machine learning development. 

This release is intended to enable app developers and IT operations teams to transform trained machine learning models into agile, portable, production-ready software functions that integrate with their existing application stacks and DevOps workflows.

According to OctoML, the platform expansion will help to conquer the challenges of enterprise software development by abstracting out complexities, stripping away dependencies, and delivering models as production-ready software functions.

“AI has the potential to change the world, but it first needs to become sustainable and accessible,” said Luis Ceze, CEO of OctoML. “Today’s manual, specialized ML deployment workflows are keeping application developers, DevOps engineers and IT operations teams on the sidelines. Our new solution is enabling them to work with models like the rest of their application stack, using their own DevOps workflows and tools. We aim to do that by giving customers the ability to transform models into performant, portable functions that can run on any hardware.”

A few key features of this platform expansion include: 

  • Automation detects and resolves dependencies, cleans and optimizes model code, and accelerates and packages the model for any hardware product 
  • OctoML CLI brings users a local experience of OctoML’s feature set and integrates with SaaS capabilities to create accelerated hardware-independent models-as-functions 
  • Comprehensive fleet of over 80 deployment targets in the cloud and at the edge with accelerated computing, including GPUs, CPUs, NPUs, from NVIDIA, Intel, AMD, ARM, and AWS Graviton 
  • Expansive software catalog covering all major ML frameworks, acceleration engines, and software stacks from chip makers 

“NVIDIA Triton is the top choice for AI inference and model deployment for workloads of any size, across all major industries worldwide,” said Shankar Chandrasekaran, product marketing manager at NVIDIA. “Its portability, versatility and flexibility make it an ideal companion for the OctoML platform.”