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AI

Machine learning deployment platform OctoML raises $85M

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OctoML, a platform that helps enterprises optimize and deploy machine learning (ML) models, has raised $85 million in a series C round of funding.

While countless companies are dabbling with ways to leverage AI to improve their businesses and bottom line, transitioning AI projects beyond the pilot stage and into real-world production scenarios comes is no easy feat. Indeed, in its State of AI in 2020 report, McKinsey found that just 16% of respondents from across industries had taken their deep learning beyond the pilot stage — and this, ultimately, is what OctoML is all about.

From pilot to production

Founded out of Seattle in 2019, OctoML helps companies deploy ML models through to production environments. It does this by automatically tailoring models to suit the target hardware platform, cloud provider, or edge device, with no manual rewriting or re-architecting required — in other words, it saves a significant amount of time and resources. The company has cemented official partnerships with major hardware firms such as AMD, Arm, and Qualcomm.

OctoML is built on the open source Apache TVM, which is a machine learning compiler framework for central processing units (CPUs), graphics processing units (GPUs), and machine learning accelerators — it enables ML engineers to run more efficient computations on any hardware. Perhaps most notably, OctoML was founded by the Apache TVM creators, which includes CEO Luis Ceze.

“The ever-growing ecosystem of ML hardware backends and diverse models are generating an insurmountable amount of manual work to optimize and fine-tune models before deployment,” Ceze noted in a press release. “This is resulting in skyrocketing costs, significant delays in time to production, and impeding new use cases in resource-constrained edge devices.”

In short, OctoML wants to help AI projects succeed by removing barriers and improving accessibility to a far broader spectrum of users. That might mean smaller engineering teams with fewer resources, or larger businesses such as Toyota that are looking to make better use of their existing resources.

Prior to now, OctoML had raised around $47 million, and with another $85 million in the bank from its lead investors Tiger Global Management, Addition, Madrona Venture Group, and Amplify Partners, the company said that it’s well-financed to expand its roster of partnerships across hardware vendors and cloud providers.

“Our ecosystem efforts are driven by our vision for the company, which is to make ML accessible to as many developers, anywhere and on any device,” Ceze explained.

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Categories
AI

OctoML raises $28M for machine learning deployment optimization

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Studies like the 2020 State of AI report from McKinsey have found that businesses capable of deploying multiple AI models are considered high performers, but a survey of business leaders included in the report found fewer than 20% have taken deep learning projects beyond the pilot stage. It’s well known that most businesses face challenges deploying AI in production, which has led to a rise in startups that serve needs like AIOps or auditing. In the latest news for such a company, OctoML today raised a $28 million series B funding round.

OctoML helps businesses accelerate AI model inference and training and relies on the open source Apache TVM machine learning compiler framework. TVM is currently being used by companies like Amazon, AMD, Arm, Facebook, Intel, Microsoft, and Qualcomm. OctoML will use the funding to continue building out products like its Octomizer platform and investing in its go-to-market strategy and customer service teams.

“We started the TVM work as a research project at the University of Washington about five years ago, and all the key people in the project are part of — they all got their Ph.D.s and are part of the company now,” OctoML CEO and cofounder Luis Ceze told VentureBeat. “We’re focused on making inference fast on any hardware, and support cloud and edge deployments.” 

Last month, OctoML joined more than 20 startups — including Algorithmia and Determined AI — that have banded together to create the AI Infrastructure Alliance, an effort to promote interoperability between the offerings from AI startups and advance alternatives to popular cloud AI services.

The $28 million funding round was led by Addition Capital, with participation from existing investors Madrona Venture Group and Amplify Partners.

OctoML has raised $47 million to date, including a $3.9 million seed funding round in October 2019, just months after the company was founded. OctoML is based in Seattle with remote employees across the United States.

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