Amazon's Alexa was showered with attention at last month's CES tech show in Las Vegas, as dozens of companies invited the voice assistant to live in their cars, washing machines and set-top boxes. Yet, behind all that luster is a somewhat uncomfortable question about Amazon's 2-year-old artificial intelligence platform: Does Alexa make Amazon any money? The answer, say several analysts: No, but it will. And when it does, it'll be huge. As part of Amazon's fourth-quarter earnings report on Thursday, the company mentioned that Alexa-powered devices were Amazon's top-selling products this holiday season.

Consumers and companies are all-too familiar with the consequences of financial fraud, having been victims of massive data breaches and orchestrated campaigns of payment fraud across all channels. What's less clear is how financial institutions and merchants can stay one step ahead of the risk and fraud, while reducing their regulatory burden. In the most recent episode of the Real Machine Podcast, Feedzai's Ajit Ghuman hosts a fascinating exploration of the potential of AI and machine learning with one of the risk management profession's foremost practitioners, Peter Mockenheim, prior Chief Operational Risk Officer for Santander Consumer. Peter has had a storied career leading the risk and compliance departments of a variety of financial institutions. Peter was a founding member of Nationwide Bank, and then went on to become Chief Control Officer for the operations of Chase's Consumer And Community Bank, where he achieved the highest possible internal audit rating, firm-wide.

If you play video games, imagine how much you sometimes empathize with the character you're controlling. You may even forget the separation between the two of you, experiencing the world as that character. Consider whether your control in these moments is different, both at a high level and in tiny movements, than what the character would do if you had simply written down a set of rules for it to act by. In that difference lies the promise of this method for developing character AI. In psychology research methodology, there's a broad consensus that if you want to know what someone would do in a situation, you don't ask them what they would do.

As the World Economic Forum unraveled last week in Davos, Switzerland, many leaders highlighted areas of future growth and how to shape the global economy – to promote an economy that will only serve to help improve our lives. Ginni Rometty, CEO of IBM, was also there discussing how IBM can contribute to this starting with artificial intelligence – or augmented intelligence/cognitive as we say at IBM. Why does IBM choose to use "augmented intelligence" or "cognitive" over "artificial intelligence"? What we've witnessed during each of these stages is some form of mechanics or machinery developed to augment our performance, thereby improving our outcome. Automotive – The assembly line was created to help workers produce more cars and simultaneously made the car more affordable to the masses. Communication – telephone / telex / fax – Gives one the ability to transfer information faster rather than having a messenger or a trained bird fly there.

Maybe you enjoy sketching as a hobby, but you're not so crazy about the work that goes into colouring in your work, or you're just lacking in the talent department when it comes to that side of the digital art equation. Check out this tool based on Chainer, a flexible neural network framework that can support a number of different uses. The so-called PaintsChainer project can take your basic line art, created using whatever drawing program you happen to use, in a number of ordinary file formats, including JPG, PNG, GIF or even TIFF, and then automatically apply color, in a dreamy watercolor/colored pencil style that's a pretty popular style among digital artists. Left to its own devices, the tool comes up with interesting color choices. If you want, you can just let the tool decide itself what colors to use and where to apply them, but you can also use an in-browser toolbar to give the system hints, as I did with the example with more accurate colors on the Adventure Time crew and Pikachu below.

You're responsible if your dog does something wrong, why not for your AI? Who is accountable for an artificial intelligence or robot which performs an action that brings harm to people? That action might be accidental but it's one of many questions society might need to ask itself about the autonomy and accountability of AI when more advanced forms of it such as driverless vehicles -- likely to be the first robots we learn to trust -- drones, and even military weapons become more widely deployed. AI and legal experts are attempting to figure it out, but there's no simple answer. Google's next big step for AI: Getting robots to teach each other new skills Robots haven't reached human intelligence yet, but Google's researchers are showing how they're closing the gap using downloadable intelligence. Speaking on a British Academy panel about robots and the law at The Royal Society, one expert suggested that the answer could be right under our noses.

Sick of diets that only tell you what you can't eat. Suggestic reverses this trend by focusing on telling you what you can have. Starting a diet is a piece of cake. Well … did someone say cake? Even if you don't have the willpower to stick to your culinary resolutions, a new app may be able to help.

Initially used to improve the experience for visually impaired members of the Facebook community, the company's Lumos computer vision platform is now powering image content search for all users. This means you can now search for images on Facebook with key words that describe the contents of a photo, rather than being limited by tags and captions. To accomplish the task, Facebook trained an ever-fashionable deep neural network on tens of millions of photos. Facebook's fortunate in this respect because its platform is already host to billions of captioned images. The model essentially matches search descriptors to features pulled from photos with some degree of probability.

These days it seems like you can't open a newspaper (OK, web browser) without coming across an article on artificial intelligence (AI). Publicized breakthroughs -- like Google AlphaGo's unprecedented victories over human Go champions -- have heralded the promise of a new golden age for AI. Add to that the personification of personal assistants in Apple's Siri and Amazon's Alexa, coupled with Salesforce's "resurrection" of Albert Einstein and the rampant proliferation of AI-related startups, and the AI buzz becomes more of a cacophonous clamor. To put it mildly, this is confusing for businesses, as leaders are trying to determine what is real and what is mere snake oil. Will AI achieve its transformational promise, or will it join the trash heap of over-hyped technologies?

"Fake News" vexed the media classes greatly in 2016, but the tech world perfected the art long ago. With "the internet" no longer a credible vehicle for Silicon Valley's wild fantasies and intellectual bullying of other industries – the internet clearly isn't working for people – "AI" has taken its place. But almost everything you read about AI is Fake News. The AI coverage comes from a media willing itself into a mind of a three year old child, in order to be impressed. For example, how many human jobs did AI replace in 2016? If you gave professional pundits a multiple choice question listing these three answers: 3 million, 300,000 and none, I suspect very few would choose the correct answer, which is of course "none".