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The Silicon Dioxide Solution

How physicist Jean Hoerni built the bridge from the transistor to the integrated circuit

16 min read
Photo of physicist Jean Hoerni.
Practical Theorist: On 1 December 1957, physicist Jean Hoerni conceived the planar process, a technique used to manufacture essentially all silicon transistors and micro- chips today.
Photo: Hoerni: Wayne MIller/Magnum Photos; Photo-IllustratIon: Brandon Palacio

Not plastic bags, nor metal screws, nor cigarette butts. No, the commonest human artifact today is the transistor—invented 60 years ago this month by Bell Labs physicists John Bardeen and Walter Brattain. Millions of these subminiature switches populate computers, cellphones, toys, domestic appliances, and anything else that carries a microchip. Exactly how many transistors are around is hard to know, but several years ago Gordon Moore, a founder of Intel Corp. and author of the famed Moore’s Law, made an educated guess: more than 1018—that’s one quintillion—transistors are produced annually. “We make more transistors per year than the number of printed characters in all the newspapers, magazines, books, photocopies, and computer printouts,” Moore told me recently. “And we sell these transistors for less than the cost of a character in the Sunday New York Times.”

Behind the explosive growth that transistor production has seen since 1960 is a major technological achievement. Today, chipmakers essentially print transistors on silicon wafers. It’s a manufacturing method rooted in the mechanical printing process originated by Johannes Gutenberg more than 500 years ago—though far more complex, of course. Moore himself played a lead role in developing transistor-fabrication technology during the 1960s when he was research director at Fairchild Semiconductor Corp., in Palo Alto, Calif. But much of the credit for that revolutionary advance belongs to a lesser-known semiconductor pioneer and Fairchild cofounder. The unsung hero of this pivotal chapter in the history of electronics—the invention of the planar transistor—is Jean Hoerni.

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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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