Dotscience Emerges from Stealth to Eliminate the Biggest Pain Points of Operationalizing AI

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According to a new press release, “Dotscience, the pioneer in DevOps for machine learning (ML), today emerged from stealth with its platform for collaborative, end-to-end ML data and model management. By giving teams the unique ability to collaboratively track runs—a record of the data, code and parameters used when training an AI model—Dotscience empowers ML and data science teams in industries including fintech, autonomous vehicles, healthcare and consultancies to achieve reproducibility, accountability, collaboration and continuous delivery across the AI model lifecycle. The Dotscience platform is now available as SaaS or on-prem, and on the Amazon Web Services (AWS) Marketplace in August.”

Luke Marsden, founder and CEO of Dotscience, noted, “The current state of AI development is a lot like software development in the 1990s. Before the movement called DevOps, modern best practices such as version control, continuous integration and continuous delivery were far less common and it was normal that software took six months to ship. Now software ships in minutes… At Dotscience, we are applying the same principles of collaboration, control and continuous delivery of DevOps to AI in order to simplify, accelerate and control AI development.”

The release continues, “Data science and machine learning teams commonly face a multitude of issues that make ML projects more likely to fail and create financial, reputational or legal risks for the business. These include wasted time, difficulties collaborating, mistakes made when manually tracking data, no reproducibility or provenance, lack of automated testing, manually deploying models, unmonitored models and losing track of what is running and where it came from resulting in ‘snowflake deployments’.”

Read more at Business Wire.

Image used under license from Shutterstock.com

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