Jul 28, 2021

6 Posts

Cartoon about data
Jul 28, 2021

The Batch: Face Recognition Audit, Gamers Cheat with AI, Who Rules the Smart City?, Language Learning Generalizes to Other Domains

In earlier letters, I discussed some differences between developing traditional software and AI products, including the challenges of unclear technical feasibility, complex product specification, and need for data to start development.
Video showing AI working on a video-game to blast virtual enemies at superhuman speed
Jul 28, 2021

Fake Aim: Gamers cheat with AI-powered aim assist.

Gamers looking to cheat in first-person shooters can’t miss with AI-assisted marksmanship. A video-game hack uses computer vision to blast virtual enemies at superhuman speed, Ars Technica reported.
Frozen Pretrained Transformer (FPT) explained
Jul 28, 2021

Transformers Are Smarter Than You Think: Language transformers can do math, vision, and logic.

The transformer architecture has shown an uncanny ability to model not only language but also images and proteins. New research found that it can apply what it learns from the first domain to the others.
Series of images related to face recognition protocols for federal agencies
Jul 28, 2021

U.S. Lax on Face Recognition: U.S. agency calls for stricter face recognition controls.

A U.S. government watchdog agency called for stronger face recognition protocols for federal agencies. An audit found that, while many employ face recognition, they may not know where it came from, how it’s being used, or the hazards involved.
AI system monitoring urban traffic
Jul 28, 2021

Meet the New Smart-Cities Champ: Chinese researchers win prizes for AI traffic safety.

Chinese researchers for the first time swept a competition to develop AI systems that monitor urban traffic. Chinese universities and companies won first and second place place in all five categories of the 2021 AI City Challenge.
Cartoon about data
Jul 28, 2021

Developing AI Products Part 5: Data Drift, Concept Drift, and Other Maintenance Issues

In earlier letters, I discussed some differences between developing traditional software and AI products, including the challenges of unclear technical feasibility, complex product specification, and need for data to start development.

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