Lassi Liikkanen shows 3 key applications: detection, prediction, and generation.

A fantastic overview of design process for products that use machine learning from Josh Lovejoy and Jess Holbrook. Here's a case study that applies these principles to Google Clips camera.

Class Central analyzed online courses on machine learning and selected the best.

This one-day workshop explores several issues in the domain of generative models for creativity and design. 32 papers were published.

Oliver Roeder says that “computer art” isn’t any more provocative than “paint art” or “piano art.” The algorithmic software is written by humans, after all, using theories thought up by humans, using a computer built by humans, using specifications written by humans, using materials gathered by humans, in a company staffed by humans, using tools built by humans, and so on. Computer art is human art — a subset, rather than a distinction.Robert Hart looks for legal precedents.

McKinsey analyzed 800 jobs to find how easily they can be automated. Lots of interesting insights. Here's a website to check your job. It started to happen with creative jobs in 2023 (see examples: IBM, Axel Springer, Bluefocus Intelligent Communications Group Co.).

A good article series by Rob Girling from Artefact. He looks at skills that can be automated and tries to predict the future of design as s profession.

O’Reilly published a great mini-book by Patrick Hebron with machine learning basics and design examples. He also has a great vision about new design tools.

A great visual overview of machine learning basics by Stephanie Yee and Tony Chu.

A terrific article by Fabien Girardin. He shows how designers can work together with big data analysts to benefit from machine learning.