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One Simple Chart: how open source projects interact with users

Core members of an open source projects make an effort to interact with users through a variety of means. They give talks at local events (now moved online), they answer questions online, and they resolve issues identified by users (using tools like GitHub). As far as answering questions from users, over the past couple ofContinue reading “One Simple Chart: how open source projects interact with users”

One Simple Chart: where do consumers prefer AI data be processed

With machine learning and AI being embedded in a growing number of products and systems, privacy and security become central for users and companies. Every company now has a Privacy Policy to comply with regulations like GDPR and CCPA. And in the not-so-distant future, companies will have teams focused on managing risks stemming from dataContinue reading “One Simple Chart: where do consumers prefer AI data be processed”

One Simple Chart: which sectors are using reinforcement learning

Interest in reinforcement learning has grown steadily over the last decade. In a recent post, I described emerging applications of RL in recommendation and personalization systems, and in business simulation and optimization. In this post, I wanted to examine which industry sectors have been mentioning reinforcement learning in their job postings. Let’s place demand forContinue reading “One Simple Chart: which sectors are using reinforcement learning”

Here’s what you need to look for in a model server to build ML-powered services

Ray Serve simplifies the integration of classic web serving and model serving. By Ben Lorica and Ion Stoica.

One Simple Chart: Computational Limits of Deep Learning

man using stylus pen for touching the digital tablet screen

While deep learning proceeds to set records across a variety of tasks and benchmarks, the amount of computing power needed is becoming prohibitive. A recent paper – “The Computational Limits of Deep Learning” – from M.I.T., Yonsei University, and the University of Brasilia, estimates of the amount of computation, economic costs, and environmental impact thatContinue reading “One Simple Chart: Computational Limits of Deep Learning”