IBM Corp. has tried to democratize artificial intelligence for enterprises with the IBM machine learning platform. Now, with its Digital Business Assistant, the company aims to do the same for pretty much anyone with a computer. "How do we make Watson [IBM's cognitive platform] tailorable and put it in the hands of every knowledge worker in every company?" said Michael Gilfix, vice president of process transformation at IBM. That is the question that started wheels turning at IBM to produce the assistant, he explained. The tool is geared toward average nontechnical users to analyze and manage data, email, spreadsheets and more.

On a daily basis, he takes a close look at automotive bonds and, until now, has gathered information from different sources. Recently, he decided to use a tool that includes all automotive companies with their market rate, company news, proportion of equities and much more. The vendor of the tool explained to him that, based on artificial intelligence, the tool was able to make excellent and incredibly fast predictions. He opens the program and immediately finds a list of all companies and specific forecasts. On the basis of sentiment analyses, the algorithm recognizes the public opinion about the company.

Whether the displacement of human labour by automation is, as is often depicted, another nail in the manual coffin seems a moot assertion. But what cannot be denied is its increasing role across the financial services (FS) sector, with some players even seeing automated environments as a panacea. Universal remedy or not, what does seem clear is that the FS sector is ripe for automation. Supporting this assertion is a 2017 report by Infosys – 'Amplifying Human Potential: Towards Purposeful Artificial Intelligence' – which found that FS companies across the globe (based on a poll of 1600 senior business decision makers at some of the world's largest organisations) are looking to automation, and its subset, artificial intelligence (AI), to boost revenues and streamline structures. "Financial institutions (FIs) are looking at automation across a fairly wide spectrum of activities," says Tom Kimner, head of global risk marketing and operations at SAS. "One recent area of interest has been an investigation of current processes around governance and compliance. With many of these processes stabilising to some degree, FIs are looking at improving and streamlining them with some form of automation to not only reduce costs but to make them more robust and repeatable."

Machine learning is shaping up to be the next major evolution in the transformation of finance. While the algorithms that enable machine learning have been around for decades, today's increased computing power is pushing machine learning to the forefront. How can you prepare for what comes next? Here are four ways to guide the evolution and unlock the value machine learning has to offer. Businesses must continually make choices about how they allocate resources. There's always internal competition for funding to pursue new business opportunities.

Like a lot of people, we've been pretty interested in TensorFlow, the Google neural network software. If you want to experiment with using it for speech recognition, you'll want to check out [Silicon Valley Data Science's] GitHub repository which promises you a fast setup for a speech recognition demo. It even covers which items you need to install if you are using a CUDA GPU to accelerate processing or if you aren't. Another interesting thing is the use of TensorBoard to visualize the resulting neural network. This tool offers up a page in your browser that lets you visualize what's really going on inside the neural network.

Libratus, an artificial intelligence, just beat the world's top poker players by a margin of $1.7 million. This is the second time a system from his lab has won a poker world championship, and the first time in the most difficult "heads up / no limit" version of the imperfect information game. This isn't Sandholm's first time building a system that beats the market. His background includes founding CombineNet. He's also proud that his algorithms run the UNOS kidney exchange, which covers 2/3 of the U.S. market for kidney transplants.

Artificial intelligence (AI) is set to hit the road in an alternative fashion to driverless cars, thanks to an AI powered concept tyre from Goodyear. The tyre maker debuted the Eagle 360 Urban, a 3D printed sensor-leaden spherical tyre with feeds back road data into an AI'brain' allowing for the tyre to by dynamically adjusted to suit changing road conditions. Covered in a super-elastic polymer that acts as a form of bionic skin for the tyre, and a morphing tread, the Eagle 360 Urban can use actuators to dynamically change the tread design of the tyre without compromising its support of the vehicles it is connected to. This allows the tyre to be adjusted for different driving conditions on the fly, for example in wet conditions dimples can be added to the treads to provide extra grip, while in dry conditions the tyre can be smoothed out to allow for smoother driving. If the bionic skin is damaged, the tyre's sensors will detect the problem and prompt the tyre to rotate to avoid contact of the damaged section with the road, thereby reducing pressure on that section of the tyre and allowing a self-healing process to start through the use of material that react physically and chemically together to form monocular bonds to repair punctures.

Newswire) Artificial Intelligence (AI) is one of the next big growth areas for the mobile industry according to a white paper released by IHS Markit (Nasdaq: INFO), a world leader in critical information, analytics and solutions, ahead of Mobile World Congress. "Smartphones will both be the interface for consumer AI and deliver the vast amount of data technology companies need to train AI systems" "We see AI making smart devices even smarter with improved user experiences," said Ian Fogg, director of mobile and telecom analysis at IHS Markit. "Existing AI agents like Apple's Siri and Google Assistant will expand across the industry, complemented by embedded AI in all parts of mobile devices from cameras, to audio, to machine." "Smartphones will both be the interface for consumer AI and deliver the vast amount of data technology companies need to train AI systems," Fogg said. Software investments and partnerships are critical for hardware companies to create smarter AI-enabled experiences, said the IHS Markit white paper.

Registration for the O'Reilly Artificial Intelligence conference is now open--best price ends April 7, 2017. Subscribe to the O'Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. This week, I sit down with Aman Naimat, senior vice president of technology at Demandbase, and co-founder and CTO of Spiderbook. We talk about his project to build a knowledge graph of the entire business world using natural language processing and deep learning.

Mnuchin went on to clarify his comment a bit, noting that he doesn't think self-driving cars use artificial intelligence because "that's computers and using real technology we have today." It's a comment that shows his understanding of machine learning and AI to be rather short-sighted and outdated. Mnuchin said that he is thinking more about robots taking people's jobs, invoking the R2-D2 droid from Star Wars, saying that a self-driving car network is "very different from artificial, you know, R2-D2 taking over your job." Overall, he said he's "not at all" worried about robots or AI displacing jobs in the short term. "in fact, I'm optimistic," he said, referring to the potential of technology to help "create productivity."