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Posts Tagged ‘DeepMind’

Demis Hassabis on AI’s potential

Posted by hkarner - 8. Januar 2020

Date: 06‑01‑2020

Source: The Economist 2020 VISIONS

Artificial intelligence could accelerate research in a range of fields,

says Demis Hassabis, co‑founder and CEO, DeepMind

THE SCIENTIFIC method was perhaps the single most important development in modern history. It established a way to validate truth at a time when misinformation was the norm, allowing natural philosophers to navigate the unknown. From predicting the motions of the planets to discovering the principles of electricity, scientists have honed the ability to distil facts about the universe by generating theories, then using experimentation to qualify those theories. Looking at how far civilisation has come since the Enlightenment, one can’t help being awestruck by all that humanity has achieved using this approach. I believe artificial intelligence (AI) could usher in a new renaissance of discovery, acting as a multiplier for human ingenuity, opening up entirely new areas of inquiry and spurring humanity to realise its full potential.

The promise of AI is that it could serve as an extension of our minds and become a meta‑solution. In the same way that the telescope revealed the planetary dynamics that inspired new physics, insights from AI could help scientists solve some of the complex challenges facing society today—from superbugs to climate change to inequality. My hope is to build smarter tools that expand humans’ capacity to identify the root causes and potential solutions to core scientific problems.

Traditional AI programs operate according to hard‑coded rules, which restrict them to working within the confines of what is already known. But a new wave of AI systems, inspired by neuroscience, are capable of learning on their own from first principles. They can uncover patterns and structures that are difficult for humans to deduce unaided, opening up new and innovative approaches. For example, our AlphaGo system mastered the ancient game of Go just by competing against itself and learning from its own mistakes, resulting in original, aesthetically beautiful moves that overturned thousands of years of received wisdom. Now, players of all levels study its strategies to improve their own game. Den Rest des Beitrags lesen »

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Google’s AI program DeepMind learns human navigation skills

Posted by hkarner - 10. Mai 2018

Date: 10-05-2018
Source: The Guardian

Google’s AI beat humans at a game that involved racing around an unfamiliar virtual environment

Notch up another win for the robots: the latest program from Google’s artificial intelligence group, DeepMind, has trounced experts at a maze game after it learned to find its way around like a human.

Scientists noticed that when they trained the AI to move through a landscape, it spontaneously developed electrical activity akin to that seen in the specialised brain cells that underpin human navigational skills. So-called ‘grid cells’ were only identified in animals in 2005 in work that earned researchers a Nobel prize.

The latest breakthrough reveals the potential for human brain-like activity to emerge from scratch in AI systems. Beyond making smarter programs, it paves the way for computer engineers to build models that help neuroscientists better understand the human brain.
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How quickly will machines sweep man aside?

Posted by hkarner - 22. November 2017

Date: 21-11-2017
Source: The Economist
Subject: Human obsolescence?

Predictions about artificial intelligence (AI) have a patchy record. Any greybeard in the field will tell you tales of previous hype cycles in the 1970s and 1980s that crashed when their fabulous promises were not fulfilled. 

Now, though, times are good again. A spurt of progress in machine learning, a sub-field of AI, has companies piling in. The technology is being used for everything from working out how best to aim advertisements at web-surfers to how to develop self-driving cars. A landmark was working out how to beat humans at Go, an East Asian strategy game that computers have historically found hard. An AI created by DeepMind, a British sub­sidiary of Google, beat a human champion of the game in 2015.

Can such progress continue? A group of researchers at the universities of Oxford and Yale decided to poll hundreds of attendees at two well-regarded AI conferences. First, the good news. The researchers believed that it would be around 125 years before computers were sufficiently advanced to be better than humans at all the suggested tasks. Those who worry about an AI “explosion”, in which clever computers design ones that are cleverer still, and do so far faster than humans can follow, can rest easy as well. The AI researchers reckoned that one of the last jobs to be automated would be “AI researcher” (although that might just suggest AI researchers are as prone to wishful thinking as anybody else). Den Rest des Beitrags lesen »

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Google’s AI Guru Says That Great Artificial Intelligence Must Build on Neuroscience

Posted by hkarner - 21. Juli 2017

Date: 21-07-2017
Source: Technology Review

Inquisitiveness and imagination will be hard to create any other way.

Demis Hassabis knows a thing or two about artificial intelligence: he founded the London-based AI startup DeepMind, which was purchased by Google for $650 million back in 2014. Since then, his company has wiped the floor with humans at the complex game of Go and begun making steps towards crafting more general AIs.

But now he’s come out and said that be believes the only way for artificial intelligence to realize its true potential is with a dose of inspiration from human intellect.

Currently, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. But different types of machine learning, such as speech recognition or identifying objects in an image, require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks.

Building AI that can perform general tasks, rather than niche ones, is a long-held desire in the world of machine learning. But the truth is that expanding those specialized algorithms to something more versatile remains an incredibly difficult problem, in part because human traits like inquisitiveness, imagination, and memory don’t exist or are only in their infancy in the world of AI. Den Rest des Beitrags lesen »

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