Links for December 5, 2021

📱 Springboard: The Secret History of the First Real Smartphone — The Verge

Though the iPhone is widely considered the first modern smartphone, one company had many of the ideas that would eventually come to life in our pocket computers . . . ten years too early.

This 30 minute documentary is a fascinating exploration of the company that was once one of the fastest growing businesses in American history.

A decade before Steve Jobs introduced the iPhone, a tiny team of renegades imagined and tried to build the modern smartphone. Nearly forgotten by history, a little startup called Handspring tried to make the future before it was ready. In Springboard: the secret history of the first real smartphone, The Verge’s Dieter Bohn talks to the visionaries at Handspring and dives into their early successes and eventual failures.

🦠 Could Covid Lead to Progress? — NY Times

It’s important to remember that mRNA vaccines were a promising, if unproven, line of inquiry for years before the pandemic hit; no one could say for sure that they even worked. But now BioNTech has announced that it’s ramping up development of a malaria vaccine using messenger RNA as the delivery mechanism, and Moderna and partners announced that they’re beginning trials of two mRNA candidate vaccines against H.I.V. Malaria kills roughly 400,000 people a year, H.I.V. nearly a million, and both diseases disproportionately affect the young. If the successful mass rollout of the Covid vaccines winds up accelerating the timeline for these other vaccines, the impact on human life will be enormous.

🧁 The Pastry A.I. That Learned to Fight Cancer — New Yorker

A Japanese system for identifying pastries in 2012 paved the way for much more. Computers have only recently learned how to see, and their ability to do so is really based on their ability to learn from large data sets:

AlexNet was a neural network, “deep” because its simulated neurons were arranged in many layers. As the network was shown new images, it guessed what was in them; inevitably, it was wrong, but after each guess it was made to adjust the connections between its layers of neurons, until it learned to output a label matching the one that researchers provided.

[. . .]

Deep learning had been around for years, but was thought impractical. AlexNet showed that the technique could be used to solve real-world problems, while still running quickly on cheap computers. Today, virtually every A.I. system you’ve heard of—Siri, AlphaGo, Google Translate—depends on the technique.

🐦 A Mindblowing Tweet

Via @EmmaGZRoberts


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