With the recent rapid advances in machine learning has come a renaissance for neural networks -- computer software that solves problems a little bit like a human brain, by employing a complex process of pattern-matching distributed across many virtual nodes, or "neurons." Modern compute power has enabled neural networks to recognize images, speech, and faces, as well as to pilot self-driving cars, and win at Go and Jeopardy. Most computer scientists think that is only the beginning of what will ultimately be possible. Unfortunately, the hardware we use to train and run neural networks looks almost nothing like their architecture. That means it can take days or even weeks to train a neural network to solve a problem -- even on a compute cluster -- and then require a large amount of power to solve the problem once they're trained.

If you want to see some of the stuff that Tay tweeted, head over here.

But as Geist notes there are diminishing returns on many problems which are inherently intractable; so there is no physical possibility of "God-like intelligence" as a result of simply making computers merely bigger and faster. And without a meaningful way to rank two set members by some property, it makes no sense to talk about "increasing" that property. Empires need information processing to function, so before computers humanity developed bureaucracies, which are a kind of human operated information processing machine. The only difference is that a complex AI system could continue to run well after human society collapsed.

When faced with a tricky question, one think you have to ask yourself is'Does this question actually make any sense?' For example you could ask "Can anything get colder than absolute zero?" and the simplistic answer is "no"; but it might be better to say the question itself makes no sense, like asking "What is north of the North Pole"? I think when we're talking about "superintelligence" it's a linguistic construct that sounds to us like it makes sense, but I don't think we have any precise idea of what we're talking about. What *exactly* do we mean when we say "superintelligent computer" -- if computers today are not already there? After all, they already work on bigger problems than we can.

How can Artificial Intelligence (AI) help companies operate in the 21st century? How might it impact organisations and employees? AI has been around for years, but now it seems that it is taking the business world by storm. According to software startup advisor Steve Ardire, it will fundamentally reshape organisations. "Human capital will start to shift from mundane tasks and transactions to higher-order and creative work. Along the way, we will see massive businesses where the technology transforms specific job functions," says Ardire.

"Thank you so much for your kind invitation. Because I'm an artificial intelligence personal assistant, I'm unable to join you in person. The company x.ai launched an artificial intelligent assistant (read: not human, non-corporeal) in 2014 to schedule meetings. The bot's name is Amy. One result no one expected: Someone asked Amy on a date nearly every month in 2015. "To be brutally honest, I did not anticipate that.

With its Colonial-era street patterns, icy winters, notoriously aggressive drivers and high-tech talent, the Boston region would seem the perfect place to test self-driving cars and ensure they can handle anything thrown at them. But the area, and indeed the entire Northeast, has no law outlining how the technology should be driven and tested. And lawmakers who want to respond are being spurned by leaders of the fast-growing industry, who would rather have no rules than a patchwork of state laws getting in their way. "I'm hoping that the New England states will make it possible for us to do this work right at home very soon," said Daniela Rus, a professor who directs the artificial intelligence laboratory at the Massachusetts Institute of Technology, which has partnered with Toyota to advance autonomous driving. "We have more flexibility testing our algorithms and self-driving vehicles in Singapore than we do here. It's really onerous to pack up your research and move to a place to test it."

For the past three years, our smartest engineers at Databricks have been working on a stealth project. Today, we are unveiling DeepSpark, a major new milestone in Apache Spark. DeepSpark uses cutting-edge neural networks to automate the many manual processes of software development, including writing test cases, fixing bugs, implementing features according to specs, and reviewing pull requests (PRs) for their correctness, simplicity, and style. Scaling Spark's development has been a top priority for us. Every year, Spark's popularity reaches new highs.

Gloria Lombardi speaks with software startup advisor Steve Ardire to explore the state of Artificial Intelligence (AI) and its implications for the future of work. In Part 1 of this post, we covered the meaning of AI vs. machine intelligence and how AI will affect the future of work. Now we turn our attention to what's going on in the AI market and what this technology could mean for healthcare in particular. AI technology is developing, fast. "In 2016," Ardire says, "we are already seeing the emergence of applications for human resources, marketing and communications, sales, customer service, market and risk intelligence and more."

Developers gathered at the Microsoft BUILD developers conference in San Francisco to hear about the latest and greatest from Microsoft. Satya Nadella, Microsoft CEO, speaks at the keynote ceremony of the Microsoft Build Developers conference. SAN FRANCISCO – Microsoft CEO Satya Nadella kicked off the company's Build developers conference with a vision of the future filled with chatbots, machine learning and artificial intelligence. "Bots are the new apps," said Nadella during a nearly three-hour keynote here that sketched a vision for the way humans will interact with machines. That's the world you're going to get to see in the years to come."