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Data Becomes Cash Crop for Big Agriculture - Bloomberg
“I can’t tell you how many times I’ve gone to a farmer’s machine shed and all their yield data for the past 15 years is sitting in spiral notebooks on the shelves,” says Mike Stern, who heads Climate Corp. He says Bayer can digitize that material and combine it with historical information, then sell it back to farmers. “Data is the new currency,” Stern says.
startup  business  monetization  science  job 
7 hours ago by fallond
DeepMind and Google: the battle to control artificial intelligence
Hassabis thought DeepMind would be a hybrid: it would have the drive of a startup, the brains of the greatest universities, and the deep pockets of one of the world’s most valuable companies. Every element was in place to hasten the arrival of AGI and solve the causes of human misery.

Demis Hassabis was born in north London in 1976 to a Greek-Cypriot father and a Chinese-Singaporean mother. He was the eldest of three siblings. His mother worked at John Lewis, a British department store, and his father ran a toy shop. He took up chess at the age of four, after watching his father and uncle play. Within weeks he was beating the grown-ups. By 13 he was the second-best chess player in the world for his age. At eight, he taught himself to code on a basic computer.

Hassabis officially founded DeepMind on November 15th 2010. The company’s mission statement was the same then as it is now: to “solve intelligence”, and then use it to solve everything else. As Hassabis told the Singularity Summit attendees, this means translating our understanding of how the brain accomplished tasks into software that could use the same methods to teach itself.

It’s an impressive demo. But Hassabis leaves a few things out. If the virtual paddle were moved even fractionally higher, the program would fail. The skill learned by DeepMind’s program is so restricted that it cannot react even to tiny changes to the environment that a person would take in their stride – at least not without thousands more rounds of reinforcement learning. But the world has jitter like this built into it. For diagnostic intelligence, no two bodily organs are ever the same. For mechanical intelligence, no two engines can be tuned in the same way. So releasing programs perfected in virtual space into the wild is fraught with difficulty.
google  ai  story  uk  game  startup  from instapaper
yesterday by aries1988

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