Machine-learning algorithms accomplish tasks by training on a set of data, rather than being programmed by humans. Armed with the knowledge of what worked before, the system instructs the implant to stimulate users' brains to interrupt a seizure at its onset. The innovation is part of a larger phenomenon that has big implications for how we identify and treat disease: the introduction of artificial intelligence to consumer and clinical electronics. As machines learn from at times millions of humans, doctors are gaining the ability to better identify disease and even predict it before it becomes catastrophic. As in every other area of human endeavor, the introduction of AI to medicine comes with challenges.

French President Emmanuel Macron's recent visit to Washington highlighted how differently our two nations are thinking about the future. In March, the French government unveiled a national strategy for artificial intelligence technology that has a clear goal: make France a global leader in AI. In the last year, China and the European Union have taken similar steps. If we're serious about having a prosperous economy for decades to come, the United States should do the same. US Representative John K. Delaney (D-MD) (@RepJohnDelaney) is the founder of the AI Caucus and is the only former CEO of a publicly traded company in the House of Representatives.

A drone carrying a package sails through the air, touching down to make a delivery right on a customer's doorstep. Inc. wowed the world in 2013 with a video purporting to show what the future of the delivery industry would look like. But are we any closer to that now? The answer seems to be no -- at least in Japan. The nation is set to take a step forward in the sector this year as the government prepares to deregulate aviation rules so delivery firms can use drones in rural areas.

Researchers at the University of Washington have produced a photorealistic former US President Barack Obama. Artificial intelligence was used to precisely model how Mr Obama moves his mouth when he speaks. Their technique allows them to put any words into their synthetic Barack Obama's mouth.

Have you ever stopped to ask this introspective question on how Artificial Intelligence might impact your career or organisation? I try to do this often because I have come to realise that a number of businesses will become extinct either because AI will affect them negatively or they fail to proactively anticipate the future. A McKinsey report after analysing some cases states, "Artificial intelligence impact will most likely be substantial in marketing and sales as well as supply-chain management and manufacturing." The same report states that "AI has the potential to create trillions of dollars of value across the economy, if business leaders work to understand what it can and cannot do." Looking at this critically, one would wonder how Nigeria's manufacturing industries would be able to compete with their counterparts abroad who are massively adding AI-powered tools and solutions to their production lines.

An explorative data analysis system should be aware of what the user already knows and what the user wants to know of the data: otherwise the system cannot provide the user with the most informative and useful views of the data. We propose a principled way to do explorative data analysis, where the user's background knowledge is modeled by a distribution parametrised by subsets of rows and columns in the data, called tiles. The user can also use tiles to describe his or her interests concerning relations in the data. We provide a computationally efficient implementation of this concept based on constrained randomisation. This is used to model both the background knowledge and the user's information request and is a necessary prerequisite for any interactive system. Furthermore, we describe a novel linear projection pursuit method to find and show the views most informative to the user, which at the limit of no background knowledge and with generic objective reduces to PCA. We show that our method is robust under noise and fast enough for interactive use. We also show that the method gives understandable and useful results when analysing real-world data sets. We will release, under an open source license, a software library implementing the idea, including the experiments presented in this paper. We show that our method can outperform standard projection pursuit visualisation methods in exploration tasks. Our framework makes it possible to construct human-guided data exploration systems which are fast, powerful, and give results that are easy to comprehend.

Two words you'll have heard a lot of over the past year or so. It's been such a popular term that it even made Word of the Year for 2017. But there is a much more to it than being a large part of Trump's vocabulary. This is a'uge problem that needs to be addressed and tackled. So, what is it then?

Canadian computer scientists helped pioneer the field of artificial intelligence before it was a buzzword, and now Prime Minister Justin Trudeau is hoping to capitalize on their intellectual lead. "We've been investing massively in AI," Trudeau told a conference of tech entrepreneurs Friday at the Massachusetts Institute of Technology, before name-dropping several of the Canadian academics he said provided the "modern underpinnings" of the technology during an "AI winter" when most weren't paying it much notice. Trudeau has become a kind of marketer-in-chief for Canada's tech economy ambitions, explaining the basics of machine learning as he promotes a national plan and government investments to "secure Canada's foothold" in AI research and education. He said Friday that Canada is making a "deliberate choice," but not an easy choice, to embrace change at a time when new technology is disrupting workplaces and leading to anxiety and fear about the future. He said leaders also have a responsibility to shape the rules and principles to guide the development of artificial intelligence.

Yet the four-year-old firm has become Japan's most valuable startup, with a venture capital funding that priced it at more than $2 billion, according to people familiar with the matter. Toyota Motor Corp., its biggest backer, handed over $110 million on a bet its algorithms will help them compete with Google in driverless cars. Last February, Prime Minister Shinzo Abe posed for pictures with the firm's two young founders at his office, where they were awarded a prize for promising new ventures.

Google's quantum computing researchers have been planning a party--but new results from a competing team at China's Alibaba may have postponed it. The China-America corporate rivalry on an obscure frontier of physics illustrates a growing contest between nations and companies hoping to create a new form of improbably powerful computer. In March, Google unveiled a chip called Bristlecone intended to set a computing milestone. It could, Google said, become the first quantum computing system to perform a calculation beyond the power of any conventional computer--a marker known as quantum supremacy. The group's leader, John Martinis, suggested it could reach supremacy this year, updating an earlier prediction that his team might do so in 2017.