This week in AI & Machine Learning: AI for playing bridge, diagnosing ocular conditions, and diversifying Wikipedia’s content library.
Obviously, fashion got upstaged at this year’s Oscars ceremony. Even still, I’ve enjoyed introducing our red carpet fashion classification model to this year’s looks. Our model included Jessica Chastain, Ariana Debose, and Lily James on this year’s Best Dressed list and reserved spots on the Worst Dress list for Kirsten Dunst, Kristen Stewart, and Timothee Chalamet. Personally, I thought all of these stars looked great!
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Demand for takeout is down from its early-pandemic heights, but customers still have an appetite for the speed and convenience of the drive-thru. Check out a recording of our recent webinar to learn more about how computer vision is helping quick service restaurants capitalize on high demand and transform their approach to customer service.
Artificial Intelligence News
AI Bests Bridge Champions
NukkAI, a French startup, has reached a major milestone by developing AI capable of beating champion bridge players at their own game.
While chess-playing computers have been around for a long time, and excelling at chess requires know-how, it’s relatively simple for AI to learn: Chess players have just one opponent, and both participants have all the information they need to compete displayed on the board. In bridge, on the other hand, an AI must mimic human thinking more closely by making decisions based on limited information and reacting to several opponents at once.
Learn more about how NukkAI’s model used a hybrid rules-based and deep learning system to defeat eight bridge world champions.
Using AI to Diagnose Eye Conditions
At Plainsight, we often discuss the impressive ways vision AI can extend and enhance the capabilities of the human eye. In the hands of gifted engineers and doctors, AI can not only mimic sight, but help diagnose conditions of the eye and improve patient outcomes.
A team of scientists affiliated with Google Health recently published a report on their efforts to create AI-powered technology capable of non-invasively pre-screening for conditions like diabetic retinal disease and elevated lipid levels. Read up on this exciting work and check out some additional vision AI use cases for the healthcare industry.
AI for a More Inclusive Wikipedia
One of the most popular sites on the web, Wikipedia offers a broad catalog of articles covering just about everything. Though Wikipedia’s library is undoubtedly diverse, it’s not without its gaps. Just 20% of the English site’s biographical content focuses on women and it is likely that a much smaller portion focuses on women from minority groups.
Writing for Meta’s AI blog, research scientist Angela Fan describes her PhD project: an effort to create an AI capable of automatically generating biographies for Wikipedia to address its many content imbalances. Find out more about how the model operates and the work ahead to help it improve.
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About the Author & Plainsight
Bennett Glace is a B2B technology content writer and cinephile from Philadelphia. He helps Plainsight in its mission to make vision AI accessible to entire enterprise teams–the ML power users, as well as the subject matter experts and non-technical users.
Plainsight’s vision AI platform streamlines and optimizes the full computer vision lifecycle. From data annotation through deployment, customers can quickly create and successfully operationalize their own vision AI applications to solve highly diverse business challenges.