Tag: Deepmind

Google’s ‘TPU’ chip puts OpenAI on alert and shakes Nvidia investors

The origins of Google’s TPU date back to an internal presentation in 2013 by Jeff Dean, Google’s long-serving chief scientist, following a breakthrough in using deep neural networks to improve its speech recognition systems. 

“The first slide was: Good news! Machine learning finally works,” said Jonathan Ross, a Google hardware engineer at the time. “Slide number two said: “Bad news, we can’t afford it.”

Dean calculated that if Google’s hundreds of millions of consumers used voice search for just three minutes a day, the company would have to double its data-centre footprint just to serve that function — at a cost of tens of billions of dollars. 

→ Financial Times

The Thinking Game

DeepMind’s journey chronicles the chase for AGI, the new fire destined to reshape civilization. From the digital sandboxes of Atari and the ancient silence of Go, its self-taught learning machines rose, proving that true general intelligence could be birthed from scratch.

As the AGI “boulder accelerates down the hill,” the film is an urgent call: the thinking game is won, but the moral stewardship of this boundless new power has just begun.

→ YouTube

In Two Moves, AlphaGo and Lee Sedol Redefined the Future

Poignant documentary about the Lee Sedol versus the machine.

The symmetry of these two moves is more beautiful than anything else. One-in-ten-thousand and one-in-ten-thousand. This is what we should all take away from these astounding seven days. Hassabis and Silver and their fellow researchers have built a machine capable of something super-human. But at the same time, it’s flawed. It can’t do everything we humans can do. In fact, it can’t even come close. It can’t carry on a conversation. It can’t play charades. It can’t pass an eighth grade science test. It can’t account for God’s Touch.

But think about what happens when you put these two things together. Human and machine. Fan Hui will tell you that after five months of playing match after match with AlphaGo, he sees the game completely differently. His world ranking has skyrocketed. And apparently, Lee Sedol feels the same way. Hassabis says that he and the Korean met after Game Four, and that Lee Sedol echoed the words of Fan Hui. Just these few matches with AlphaGo, the Korean told Hassabis, have opened his eyes.

This isn’t human versus machine. It’s human and machine. Move 37 was beyond what any of us could fathom. But then came Move 78. And we have to ask: If Lee Sedol hadn’t played those first three games against AlphaGo, would he have found God’s Touch? The machine that defeated him had also helped him find the way.

→ Wired