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OctoML is charging ahead with its machine learning deployment software and on Friday announced a $15 million investment round to help support growth.
The Seattle startup spun out of the University of Washington this past July, when it raised a $3.9 million seed round. Founded by a group of computer science experts, the company aims to help companies deploy machine learning models on various hardware configurations.
OctoML is led by the creators of Apache TVM, an open source “deep learning compiler stack” that started as a research project at the UW’s Paul G. Allen School of Computer Science & Engineering a few years ago. It has attracted a thriving community of users including tech giants such as Amazon and Facebook that want to optimize and automate their deep learning models for IoT/edge or cloud deployment on an increasing number of platforms such as phones, cars, health devices, and other use cases.
The idea is to reduce the amount of cost and time it takes companies to develop and deploy deep learning software for specific hardware. OctoML recently began demoing the “Octomizer,” its first TVM-based software-as-a-service offering “that enables anyone to turn their ML models into highly optimized packages for deployment in the edge and in the cloud,” CEO Luis Ceze wrote in a blog post.
“The ‘secret’ sauce in our technology is to use ML to optimize ML, reducing the optimization and tuning time by orders of magnitude,” Ceze said.
Ceze, a UW computer science professor and recent GeekWire Geek of the Week, said the fresh cash will help OctoML continue hiring during an economic downturn that is forcing other tech startups to trim staff. The company has already has tripled headcount since July and employs 20 people.
“This is a hard time to be positive about the future but we see very good things ahead,” Ceze said. “Machine learning and artificial intelligence will be key components of nearly every software application and it needs to be easy, efficient and portable. That is what we are making possible with OctoML.”
Amplify Partners led the Series A round, which included participation from Madrona Venture Group.
“The OctoML team is unparalleled in their experience in the TVM open source community and their understanding of how ML will help both model builders and model users embrace the intelligent applications era,” Madrona Managing Director Matt McIlwain said in a statement.
Ceze previously started Corensic, a debugging startup that F5 Networks acquired in 2012. He’s also a venture partner at Madrona. His four co-founders include:
- Tianqi Chen, who received his Ph.D. last year from the Allen School and is CTO.
- Jason Knight, a former principal engineer and AI leader at Intel who earned a Ph.D. in electrical engineering at Texas A&M.
- Thierry Moreau, who earned his Ph.D. in 2018 from the Allen School and taught a graduate level machine learning class with Ceze.
- Jared Roesch, currently a Ph.D. student at the Allen School who worked at Zentopy, Invoca, and Mozilla Research.
Advising the company is Arvind Krishnamurthy, a UW computer science professor since 2005; Zachary Tatlock, an assistant computer science professor at the UW since 2013; and Carlos Guestrin, the Amazon Professor of Machine Learning at the UW who sold Seattle machine learning startup Turi to Apple in 2016. Guestrin is currently Apple’s senior director of machine learning and AI.
OctoML is the latest machine learning/artificial intelligence startup to come out of the Seattle region. Xnor.ai, a spinout from the Allen Institute for Artificial Intelligence, had been working with partners on low-cost, low-power AI monitoring devices before its blockbuster acquisition to Apple this past January.
