'Biscuit' responds to touch and speech and has quickly become a favourite at Templeman House, Bournemouth.

At its Think 2018 conference in Las Vegas on Tuesday, IBM rolled out its Deep Learning as a Service (DLaaS) program for artificial intelligence (AI) developers. The service is available through Watson Studio, and is aimed at helping developers run hundreds of deep learning training models at the same time while building out their neural networks, according to a press release. The firm has been working on the service since at least the middle of last year, according to a white paper from IBM researchers. By using the power of the cloud to deliver AI capabilities like deep learning, IBM and other vendors that have similar services are democratizing access to these tools. Since companies won't have to build and maintain costly hardware to experiment with deep learning, it could mean more companies are able to leverage the power of AI in their own products and services.

Artificial intelligence is suddenly in people's homes, driving their cars, and running their security systems. Users interact with chatbots, sometimes unaware they're not talking to live people. Designers and marketing agencies trust computer-generated insights and machine learning over human input in making business decisions. Artificial intelligence development seemed to happen overnight, but it has been a series of developments that stretches back hundreds of years. It's hard to imagine that, 381 years ago, anyone could have conceived of artificial intelligence.

Frédéric Durand, the Founder and CEO of Diabolocom, argues that it is not a question of if businesses should utilise AI, but how they use it. Artificial Intelligence (AI) is a much discussed and debated subject in 2018. From newspapers to world leaders, everyone is talking about what machine intelligence and robotics could and might do for businesses. With all the buzz it is generating, AI is rapidly emerging as a lucrative technology. By 2035, global consulting firm Accenture has suggested that AI could add an estimated £654 billion to the UK economy.

Despite all the hype to date AI's usage in advertising has been confined to very niche areas, from re-organising data more efficiently to tagging and organising inventory. AI's massive potential has only slowly built momentum, however, we have finally reached a tipping point where AI is starting to come in to its own. The trigger occurred as Reach lost its pole position as the ultimate metric, being sidestepped by a need for higher and more accurate engagement. Little wonder really, an overwhelming 2.5 quintillion bytes of data is collected every day turning it from marketers' gold dust to their nemesis. It can no longer be properly scrutinised for meaning and in some instances it can even be misleading.

An academic who created an app which harvested data from 50 million Facebook users says he has been made "a scapegoat" for Facebook and UK firm Cambridge Analytica. Dr Aleksandr Kogan completed work for Cambridge Analytica in 2014, but said he had no idea the data would be used to benefit Donald Trump's US presidential campaign. Facebook says Dr Kogan violated the site's policies. Last night, Alexander Nix, the chief executive of Cambridge Analytica, was suspended, having been secretly filmed by Channel 4 News appearing to suggest the company could use tactics to discredit politicians online. The company says the programme "grossly misrepresented" Mr Nix's conversation.

An academic who created an app which harvested data from 50 million users says he has been made "a scapegoat" for Facebook and Cambridge Analytica. Dr Aleksandr Kogan completed work for Cambridge Analytica in 2014, but said he had no idea the data would be used to benefit Donald Trump's campaign. The psychology academic said he wanted the data so he could model human behaviour through social media. Facebook says Dr Kogan violated the site's policies. The Cambridge University researcher developed a personality survey called This is Your Digital Life.

If European Central Bank chief Mario Draghi appears slightly more downbeat at his regular news conference than before, it could foreshadow a possible move by the bank to trim its monetary policy stimulus. That's the conclusion of two Japanese researchers who have used artificial intelligence software to analyze split-second changes in Draghi's facial expressions at his news conferences following policy meetings. The findings follow a similar analysis by the same researchers of Draghi's Japanese counterpart, Haruhiko Kuroda, last year, which claimed to have identified a correlation between patterns in his facial expressions and subsequent policy changes. Yoshiyuki Suimon and Daichi Isami, the paper's authors, think that subtle changes in Draghi's facial expressions could reflect a sense of frustration Draghi might have been feeling before making policy adjustments. Their study covered Draghi's news conference from June 2016 to December 2017 and found signs of "sadness" preceding two recent major policy changes -- when the central bank announced a dovish tapering in December 2016 and another quantitative easing cutback in October last year.

I generally expect better from the American Interest than this article. The fact of the matter is we've heard this argument re-emerge every few decades and it's always been wrong. Our modern fear that robots/AI/automation will steal all the jobs fits a classic script. Nearly 500 years ago, Queen Elizabeth I cited the same fear when she denied an English inventor named William Lee a patent for an automated knitting contraption. Did you know that Keynes predicted that automation would result in a 15 hours/week work week back in the 1930s?

In the natural world, many species can walk over slopes and irregular surfaces, reaching places inaccessible even to the most advanced rover robots. It remains a mystery how complex movements are handled so seamlessly by even the tiniest creatures. What we do know is that even the simplest brains contain pattern-generator circuits (CPGs)[1], which are wired up specifically for generating walking patterns. Attempts to replicate such circuits artificially have so far had limited success, due poor flexibility. Now, researchers in Japan and Italy propose a new approach to walking pattern generation, based on a hierarchical network of electronic oscillators arranged over two levels, which they have demonstrated using an ant-like hexapod robot.