"Mandy Monroe" works relentlessly to reach out to customers of Lee Kia of Greenville in North Carolina to schedule service appointments. A consistent revenue generator, Mandy doesn't complain, gossip, make personal phone calls on company time or pop chewing gum. Mandy doesn't even take bathroom breaks. That's because Mandy is a cyberstaffer driven by artificial intelligence. The virtual assistant, created by the software provider Conversica, conducts email conversations with dealership service customers.

Ford will pour $1 billion over the next five years into an artificial intelligence company tasked with developing the technology that will one day drive its autonomous vehicles. The technology could also be licensed to other automakers in the future, executives said. Pittsburgh-based Argo AI was founded late last year by Bryan Salesky and Peter Rander, who previously worked on self-driving car initiatives at Google and Uber, respectively. The company will include the staff inside Ford that has been developing its virtual driver system for the past several years. In a phone call last week, CEO Mark Fields said the investment will help Ford bring its self-driving cars to market by its previously stated goal of 2021.

Recent breakthroughs in machine learning and artificial intelligence mean AI-enabled technologies are gaining traction. The billion-dollar cybersecurity industry is no exception, as vendors begin to scale and automate their processes intelligently - all while locked into the early stages of a security arms race with professional hackers. A recent report from analyst firm ABI Research estimates that machine learning in cybersecurity will enormously bolster spending in big data, intelligence and analytics, reaching as much as $96 billion (£71.9 billion) by 2021. Vendors are likely to find buyers in large enterprises, and more than likely, across industries that are especially prone to attack: think government and defence, banking, and across the technology sector. At the moment, ABI's report says, User and Entity Behavioural Analytics - using machine learning for threat detection by analysing data at scale - is the driving force. "Using static machine learning models to detect previously unknown malware is the only use case I'm aware of that offers clear evidence of effective results," says cybersecurity analyst at 451 Research, Adrian Sanabria.

Will artificial intelligence get more aggressive and selfish the more intelligent it becomes? A new report out of Google's DeepMind AI division suggests this is possible based on the outcome of millions of video game sessions it monitored. The results of the two games indicate that as artificial intelligence becomes more complex, it is more likely to take extreme measures to ensure victory, including sabotage and greed. The first game, Gathering, is a simple one that involves gathering digital fruit. Two DeepMind AI agents were pitted against each other after being trained in the ways of deep reinforcement learning.

Everyday, most people around the world are using artificial intelligence (AI) in their day-to-day lives. That is the suggestion from Japp Zuiderveld, VP of EMEA at NVIDIA. "It is already out there, people are already using it, or you are already using it, everybody is using it without knowing it and it facilitates the services you have today." In the interview he referred to Google Translate as the very simplest example of AI that people use on a daily basis. See also: Automation will transform marketing but brands need to allay'consumer fears' Despite this, however, he explained that it is still in its infancy and that common preconceptions of the technology are wrong.

As Maurice Conti has said in one of his presentations, we have arrived to the augmented era, in which Artificial Intelligence gains a new role. Until now all our tools were passive: we told them what to do and they did it. But the future holds a new era where artificial intelligence will come up with its own designs, its own ideas, its own products. Many tasks could soon be executed with the cooperation of robots, AI and humans, robots providing perfect execution, AI delivering the design the design and humans making the necessary decisions. But to get to this point it is crucial to build a nervous system for robots through sensors.

Episode Summary: There's been lot of hype around AI and ML in business over the past five years. Even among investors exist a lot of misconceptions about using ML in a business context, and how to get up to speed on and learn machine learning as it applies to utility in industry. Recently, I talked with Benjamin Levy of BootstrapLabs in San Francisco, whom I met through an investment banking friend in Boston. BootstrapLabs invests in Bay area companies, and Levy also travels around the world speaking about investing in AI companies and raising funds for new ventures. In this episode, Levy gives his perspective on what investors and executives get wrong about ML and and AI, and discusses how they can get up to speed and leverage the applications for these technologies and related expertise to really make a difference (i.e.

After decades on every sci-fi fan's wish list, personal robots are on the cusp of entering our homes. Now it's time to put them to work. Everyone knows Pepper, the child-sized humanoid robot launched back in 2014 who was created to welcome visitors to SoftBank Mobile stores in Japan. Now Pepper has scored a few jobs in the US, from giving directions in a shopping mall in San Francisco to pouring beer at Oakland International Airport's Pyramid Taproom. The diminutive Pepper is not alone, not even at airports.

An Artificial Intelligence (AI) program developed by Google has demonstrated human-like aggression during simulations. Google's Deep Mind AI was tested playing several different games to see what kind of behavior would emerge. In one particular game, the AI was tasked with attempting to collect more'apples' within a 2D environment than another'player'. The AI also had the ability to hit a player with a beam which would remove them from the game. After running the game through millions of simulations, Deep Mind's'deep reinforcing learning' algorithm showed human-like emergent behavior.

Artificial Intelligence is a key topic at this year's World Economic Forum Annual Meeting. Artificial intelligence and increasing automation is going to decimate middle class jobs, worsening inequality and risking significant political upheaval, Stephen Hawking has warned. In a column in The Guardian, the world-famous physicist wrote that"the automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining." He adds his voice to a growing chorus of experts concerned about the effects that technology will have on workforce in the coming years and decades. The fear is that while artificial intelligence will bring radical increases in efficiency in industry, for ordinary people this will translate into unemployment and uncertainty, as their human jobs are replaced by machines.