Tag Archives: Geoffrey Hinton

Previews: The New Yorker Magazine – Nov 20, 2023

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The New Yorker – November 20, 2023 issue: The new issue features The A.I. Issue – Joshua Rothman on the godfather of A.I., Eyal Press on facial-recognition technology, Anna Wiener on Holly Herndon, and more…

Why the Godfather of A.I. Fears What He’s Built

Geoffrey Hinton has spent a lifetime teaching computers to learn. Now he worries that artificial brains are better than ours.

By Joshua Rothman

In your brain, neurons are arranged in networks big and small. With every action, with every thought, the networks change: neurons are included or excluded, and the connections between them strengthen or fade. This process goes on all the time—it’s happening now, as you read these words—and its scale is beyond imagining. You have some eighty billion neurons sharing a hundred trillion connections or more. Your skull contains a galaxy’s worth of constellations, always shifting.

Does A.I. Lead Police to Ignore Contradictory Evidence?

A profile of a face overlaid with various panels.

Too often, a facial-recognition search represents virtually the entirety of a police investigation.


By Eyal Press

On March 26, 2022, at around 8:20 a.m., a man in light-blue Nike sweatpants boarded a bus near a shopping plaza in Timonium, outside Baltimore. After the bus driver ordered him to observe a rule requiring passengers to wear face masks, he approached the fare box and began arguing with her. “I hit bitches,” he said, leaning over a plastic shield that the driver was sitting behind. When she pulled out her iPhone to call the police, he reached around the shield, snatched the device, and raced off. The bus driver followed the man outside, where he punched her in the face repeatedly. He then stood by the curb, laughing, as his victim wiped blood from her nose.

Personal HistoryA Coder Considers the Waning Days of the Craft

Coding has always felt to me like an endlessly deep and rich domain. Now I find myself wanting to write a eulogy for it.

By James Somers

Politics: The Guardian Weekly – May 12, 2023

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The Guardian Weekly (May 12, 2023) – The name Geof frey Hinton was little known outside the tech industry until last week, when the so-called “godfather of AI” gave an interview after leaving Google in which he warned that machine learning is leading us into uncharted territory.

So is now the time to get properly frightened about the capabilities unleashed by machine learning? Technology writer John Naughton in this week’s big story says an unequivocal yes as he explores a worrying near future, and what prompted Hinton to speak out. 

Britain spent last weekend watching avidly or determinedly avoiding the exuberant display of ancient ceremony around the coronation of King Charles III. Our coverage takes a fondly amused look at all the pageantry, personalities and gold braid with Rachel Cooke, while columnist Nesrine Malik unpicks the game of divide and rule, display and disguise through which the institution hangs on to popular support. We also visit Belize to find out how arguments about reparations for slavery are linked to its relationship to the British crown.

Interview: ‘GENIUS MAKERS’ Author Cade Metz On Artificial Intelligence From A Human Perspective

How Cade got access to the stories behind some of the biggest advancements in AI, and the dynamic playing out between leaders at companies like Google, Microsoft, and Facebook.

Cade Metz is a New York Times reporter covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Previously, he was a senior staff writer with Wired magazine and the U.S. editor of The Register, one of Britain’s leading science and technology news sites. His first book, “Genius Makers”, tells the stories of the pioneers behind AI.

Topics discussed: 0:00​ Sneak peek, intro 3:25​ Who is “Genius Makers” for and about? 7:18​ *Spoiler alert!* Artificial General Intelligence (AGI) 11:01​ How the story continues after the book ends 17:31​ Overinflated claims in AGI 23:12​ Deep Mind, OpenAI, and AGI 29:02​ Outsider perspectives 34:35​ Early adopters of ML 38:34​ Who gets credit for what? 42:45​ Dealing with bias 46:38​ Aligning technology with nee

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