Responses to a White House request for information about the future of artificial intelligence show a continued... This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time.

Chris Messina Medium "It's a rare moment when it becomes clear that a technological revolution is upon us, and I believe we're in the midst of one such transition right now. Even if you haven't realized it yet, bots are everywhere... With proper forethought and consideration, bots present a new, unpolluted opportunity to build lasting relationships with people." ROBOTICS: Do No Harm, Don't Discriminate: Official Guidance Issued on Robot Ethics Hannah Devlin The Guardian "The BSI document begins with some broad ethical principles: 'Robots should not be designed solely or primarily to kill or harm humans; humans, not robots, are the responsible agents; it should be possible to find out who is responsible for any robot and its behaviour.'...The code suggests designers should aim for transparency, but scientists say this could prove tricky in practice. 'The problem with AI systems right now, especially these deep learning systems, is that it's impossible to know why they make the decisions they do,' said Winfield."

I recently consulted with the US Navy on all things "transhuman." In those conversations about how science and technology can help the human race evolve beyond its natural limits, it was clear that military is keen on replacing human soldiers with both fighting and peacekeeping machines so American military lives never have to come under fire or be in harm's way. However, it's the peacekeeping technology that is particularly interesting for many civilians. While you wouldn't want an armed Terminator in your home, you might like a robot that travels with you and offers personal protection, like a bodyguard. In a survey by Travelzoo of 6,000 participants, nearly 80 percent of people said they expect robots to be a significant part of their lives by 2020 -- and that those robots might even join them on holidays.

Fifty years ago, the first molecular dynamics papers allowed scientists to exhaustively simulate systems with a few dozen atoms for picoseconds. Today, due to tremendous gains in computational capability from Moore's law, and due to significant gains in algorithmic sophisticiation from fifty years of research, modern scientists can simulate systems with hundreds of thousands of atoms for milliseconds at a time. Put another way, scientists today can study systems tens of thousands of times larger, for billion of times longer than they could fifty years go. The effective reach of physical simulation techniques has expanded handleable computational complexity ten-trillion fold. The scope of this achievement should not be underestimated; the advent of these techniques along with the maturation of deep-learning has permitted a host of start-ups (1, 2, 3, etc) to investigate diseases using tools that were hitherto unimaginable. The dramatic progress of computational methods suggests that one day scientists should be able to exhaustively understand complete human cells.

Stanford student Joshua Browder just launched a new "chatbot" service on his website DoNotPay.co.uk that's designed to help tenants force their negligent landlords to fix problems like leaky taps or moldy walls. The new online service launched Friday in the U.K. and follows the highly publicized success of Browder's online parking ticket appeal service, which started in the U.K. but recently expanded to New York and Seattle. Browder estimates he has saved drivers about 5 million through successfully appealing 180,000 parking tickets. CNNMoney was given exclusive access to the new landlord service before the launch. It's not a glamorous website and it's got a few kinks, but it generally works as promised.

Watch out IBM Watson, Google has its own kickass'Show and Tell' AI and it's getting pretty damn good at depicting what it sees in photos – and now everyone can use it. Today, the tech giant announced it's open-sourcing its automatic image-captioning algorithm as a model in TensorFlow for everyone to use. This means anyone can now train the algorithm to recognize various objects in photos with up to 93.9 percent accuracy – a significant improvement to the 89.6 percent that the company touted when the project initially launched back in 2014. Training'Show and Tell' requires feeding it hundreds of thousands of human-captioned images that the machine then uses and re-uses when "presented with scenes similar to what it's seen before." To learn smoother, Google's impressive AI also uses a new vision component that allows for faster training and more detailed captions as it's gotten much better at telling objects apart from each other.

In this special guest feature, Alexander Khaytin, COO for Yandex Data Factory, explains how businesses can introduce "data democracy" and systematic testing and how agility can be introduced into even the most inflexible of organizations, overcoming the barriers prohibiting machine learning adoption and benefit. As Chief Operating Officer at YDF, Alexander oversees projects from concept to completion, alongside contributing to YDF's partnership, sales and technology strategies. Prior to joining Yandex in 2014, Alexander spent over a decade providing consulting and strategic analysis services for businesses in telecom, construction, energy, retail and finance industries. As a Partner at a system integrator, Korus Consulting, from 2011 to 2014, he ran projects for some of Russia's leading brands, including state-owned hi-tech corporation Rostech, Moscow City Telephone Network, mobile broadband services provider and smartphone manufacturer Yota, Bank Saint Petersburg and Russia's largest e-payment system Yandex.Money. Machine learning has come to play an important role for businesses looking to transform the way they work.

Artificial intelligence, machine intelligence, cognitive computing -- whatever you want to call machines that are capable of understanding and acting upon their environment -- is no longer solely the purview of highly credentialed lab directors and deep-thinking computer scientists. It has entered mainstream consciousness, and the public expects IT to play a leadership role as machine learning enters our workplaces, our living spaces and our lives. Chances are that you are not. Most executives, in the opinion of New York Timestechnology columnist John Markoff, are "ill prepared for this new world in the making." People have been thinking about automated work forever.

The more data you have, the more likely you are to hallucinate patterns. Supposedly, the more phone records the NSA looks at, the more likely it is to flag an innocent as a potential terrorist because he accidentally matched a terrorist detection rule. Mining more attributes of the same entities can indeed increase the risk of hallucination, but machine learning experts are very good at keeping it to a minimum. On the other hand, mining more entities with the same set of attributes decreases the risk, because the rules learned from them will have stronger support. And some learning algorithms can find patterns involving multiple entities, which makes them even more robust: a person videotaping the New York City Hall may not be suspicious, and another buying large quantities of ammonium nitrate may not be either; but if the two are in close phone contact, perhaps the FBI should take a look, just to make sure it's not a bomb plot.

Many scientists and futurists agree that the effects of artificial intelligence and automation on society are difficult to predict. While many predicted that the tip of the spear for such technology would play out in areas such as medicine or general computer system markets, the AI revolution is already underway in the financial markets. Nearly all market-making is presently dominated by machines that employ AI techniques, including advanced pattern recognition. The markets evolution from the primordial ooze of computers, networks and massive storage systems to a complex, intelligent and somewhat singular market entity will impact society well beyond finance.