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The Man Who Invented Intelligent Traffic Control a Century Too Early

With traffic accidents soaring, Charles Adler imagined an intelligent transportation system that was ahead of its time

12 min read
Adler demonstrates one of his automated safety systems.
Sound Off: Adler demonstrates one of his automated safety systems, which triggered a light when a car passed over a sound detector in the road.
Photo: Charles Adler, Jr. Collection/Archives Center/National Museum of American History, Smithsonian Institution

On a cool December day in 1925, Charles Adler Jr. stood beside Falls Road, a state highway on Baltimore’s north side. He was there to test his latest invention: an electromagnetic apparatus that would automatically slow cars traveling at unsafe speeds. Adler had embedded magnetic plates in the road where it led into a precarious curve, and he was now waiting for a specially prepared car to drive over the magnets. The magnets would activate a speed governor connected to the vehicle’s engine, slowing it to 24 kilometers per hour.

Adler had developed this automatic speed-control system for railroad crossings, the scene of many deadly accidents at the time. But he soon came to imagine all sorts of applications for it: “Dangerous road intersections, streets on which schools are located, bad curves, and even steep down grades,” according to an article in the Baltimore News.

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GPT Protein Models Speak Fluent Biology

Deep learning language models design artificial proteins for tricky chemical reactions

3 min read
Two protein structures labelled ProGen Generated and 25% Mutation.

By learning the "language" of functional proteins, the AI learned to prioritize its most structurally important segments.

SalesForce

Artificial intelligence has already shaved years off research into protein engineering. Now, for the first time, scientists have synthesized proteins predicted by an AI model in the lab, and found them to work just as well as their natural counterparts.

The research used a deep learning language model for protein engineering called ProGen, which was developed by the company Salesforce AI Research in 2020. ProGen was trained, on 280 million raw protein sequences from publicly available databases of sequenced natural proteins, to generate artificial protein sequences from scratch.

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