Killer Robots? Lost Jobs?


The recent win of AlphaGo over Lee Sedol--one of the world's highest ranked Go players--has resurfaced concerns about artificial intelligence. We have heard about A.I. stealing jobs, killer robots, algorithms that help diagnose and cure cancer, competent self-driving cars, perfect poker players, and more. It seems that for every mention of A.I. as humanity's top existential risk, there is a mention of its power to solve humanity's biggest challenges. Demis Hassabis--founder of Google DeepMind, the company behind AlphaGo--views A.I. as "potentially a meta-solution to any problem," and Eric Horvitz--director of research at Microsoft's Redmond, Washington, lab--claims that "A.I. will be incredibly empowering to humanity." By contrast, Bill Gates has called A.I. "a huge challenge" and something to "worry about," and Stephen Hawking has warned about A.I. ending humanity.

When AI rules the world: what SF novels tell us about our future overlords


It's only March and already we've seen a computer beat a Go grandmaster and a self-driving car crash into a bus. The world is waking up to the ways in which a combination of "deep learning" artificial intelligence and robotics will take over most jobs. But if we don't want our robot servants to rise up and kill us in our beds, maybe we should delete the video of us beating their grandparents with hockey sticks. Thanks to science fiction, we know that the first thing AI will do is take over the defence grid and nuke us all. In Harlan Ellison's 1967 story I Have No Mouth, and I Must Scream – one of the most brutal depictions of an AI-dominated world – an AI called AM, constructed to fight a nuclear war, kills off most of the human race, keeping five people as playthings.

Artificial Intelligence: Google's DeepMind Creates Neural Network That Can 'Logically Reason' Its Way Around London Underground

International Business Times

This is a problem for scientists working toward the creation of Artificial Intelligence (AI) systems capable of performing complex tasks with minimal human supervision. In a step toward overcoming this hurdle, researchers at Google's DeepMind -- the company that developed the Go-playing computer program AlphaGo -- announced earlier this week the creation of a neural network that can not only learn, but can also use data stored in its memory to "logically reason" and make inferences to answer questions. DeepMind's new system -- called a Differentiable Neural Computer (DNC) -- combines deep learning, wherein it can learn from examples and make sense of complex input it has never received before, with an external memory, which, as the DeepMind researchers Alexander Graves and Greg Wayne explain in a blog post, allows it to "store knowledge quickly and reason about it flexibly." In order to achieve this, the researchers first trained the neural network using randomly generated map-like structures -- a process that allowed the DNC to learn how to store connections between various parts in its external memory. After this, when it was confronted with a new map, the DNC was able to provide answers that were not explicitly stated in the data set.

What Is Deep Learning And How Is It Useful?


Deep learning recently returned to the headlines when Google's AlphaGo program crushed Lee Sedol, one of the highest-ranking Go players in the word. Google has invested heavily in deep learning and AlphaGo is just their latest deep learning project to make the news. Google's search engine, voice recognition system and self-driving cars all rely heavily on deep learning. They've used deep learning networks to build a program that picks out an attractive still from a YouTube video to use as a thumbnail. Late last year Google announced Smart Reply, a deep learning network that writes short email responses for you.

6 Areas of AI and Machine Learning to Watch Closely


It's amazing how much progress the field of AI has achieved over the last 10 years, ranging from self-driving cars to speech recognition and synthesis. Against this backdrop, AI has become a topic of conversation in more and more companies and households who have come to see AI as a technology that isn't another 20 years away, but as something that is impacting their lives today. Indeed, the popular press reports on AI almost everyday and technology giants, one by one, articulate their significant long-term AI strategies. While several investors and incumbents are eager to understand how to capture value in this new world, the majority are still scratching their heads to figure out what this all means. Meanwhile, governments are grappling with the implications of automation in society (see Obama's farewell address).