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Highlights from opening keynotes at the 2021 Ray Summit. A newly released report from McKinsey forecasts an upcoming explosion in AI applications across all industries and domains. With this surge in demand to incorporate machine learning (ML) and AI into software, developers now have an array of open source and commercial software tools and componentsContinue reading “Combine the development experience of a laptop with the scale of the cloud”
Key features of ML monitoring solutions, why companies need a holistic MLOps platform that includes model monitoring, and challenges companies face in making that happen. By Ben Lorica and Paco Nathan. According to the 2020 Gartner Hype Cycle for Artificial Intelligence, machine learning (ML) is entering the Trough of Disillusionment phase. This is the phaseContinue reading “Model Monitoring Enables Robust Machine Learning Applications”
When I wrote about enterprise applications of reinforcement learning (RL) a little over a year ago, I cited a few examples of applications for recommenders and personalization systems. At the time, the examples I listed came from large technology companies, specifically Netflix, JD, Facebook, and YouTube, as only large companies tended to have the resourcesContinue reading “Applications of Reinforcement Learning: Recent examples from large US companies”
Compute-intensive applications that incorporate machine learning should be built on top of Ray. By Ben Lorica and Ion Stoica. [This post originally appeared on the Anyscale blog.] Introduction As machine learning and AI become prevalent in software services and applications, most backend platforms now consist of business logic and machine learning (inference). Business logic andContinue reading “Why you should build your AI Applications with Ray”
The Data Exchange Podcast: Steve Touw on why data governance needs to go from the boardroom into code.
The rise of tools and processes to manage and control data. By Assaf Araki and Ben Lorica. Data has emerged as an imperative foundational asset for all organizations. Data fuels significant initiatives such as digital transformation and the adoption of analytics, machine learning, and AI. Organizations that are able to tame, manage, and unlock theirContinue reading “What is DataOps?”
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