New Deep Learning Startup, OctoML, Launches to Automate Deployment of Deep Learning

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According to a recent press release, “OctoML is leveraging the power and traction of Apache TVM, an open source project originated by the founding team, to enable companies of every size to harness the power of deep learning without the expensive heavy lifting of tuning and securing models to each hardware configuration that a customer might need. Apache TVM is an automated deep learning model optimization and compilation stack that powers efficient model deployment in major technology companies like Amazon, Facebook, Microsoft, Xilinx, and Qualcomm. It is backed by a thriving community of more [than] 270 contributors worldwide, including people from major tech companies and academic institutions. The mission of the project is to enable data engineers to easily optimize and deploy models across a broad set of hardware in a portable manner.”

Luis Ceze, co-founder and CEO, commented, “It has been awesome to see the community take off around Apache TVM. It is clear that researchers and large tech companies see both the utility and value it can offer in pushing the state of the art in efficiency machine learning in research and production settings… The promise of Apache TVM is so high that hardware companies are actively looking to optimize for it and companies with lean teams need solutions to not only deploy these models but keep them up and running. That is the opportunity that OctoML is pursuing. OctoML’s automated model optimization technology leveraging TVM, leads to lower engineering and operating costs for customers, and lowers the risk of dependence on specific platforms.”

Read more at Business Wire.

Image used under license from Shutterstock.com

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