REUTERS/Fabrizio BenschThe humanoid robot AILA (artificial intelligence lightweight android) operates a switchboard during a demonstration by the German research centre for artificial intelligence at the CeBit computer fair in Hanover March, 5, 2013. Last year, an open letter with signatories including Stephen Hawking and Nick Bostrom called for AI to be of demonstrable benefit to humanity, or risk something that exceeds our ability to control it. AI, as conceived of in popular culture, does not yet exist, even if autonomous and expert systems do. Smartphones might not be supercomputers, but they are called "smartphones" for good reason, in terms of how their operating systems function. Equally, we are happy to talk about a computer game's "AI", but gamers quickly learn to take advantage of its limitations and inability to "think" creatively.

The Burning Man vibe was intentional. For Google I/O this year -- its annual developer conference, typically held in San Francisco's antiseptic Moscone convention center -- the company stayed in Mountain View, camping out at Shoreline Amphitheatre, a grassy concert hall just a short bike ride away from its headquarters. The keynote kicked off with a wink to the libertine festival. From control booths in the back of the theater, a woman in a leather vest and a man in a collarless blazer strummed a supersized string instrument made from cords that hung in the air high above the audience -- an Earth Harp that previously made an appearance in Black Rock City. Google parked a massive "art car" shaped like a ship and festooned with Burning Man bumper stickers in the middle of its sandbox playground for new software and hardware.

Alphabet's Google unveiled its answer to Amazon's Alexa virtual assistant along with new messaging and virtual reality products at its annual I/O developer conference on Wednesday, doubling down on artificial intelligence and machine learning as the keys to its future. Google Chief Executive Sundar Pichai introduced Google Assistant, a virtual personal assistant, along with the tabletop speaker appliance Google Home. He also unveiled Allo, a new messaging service that will compete with Facebook's WhatsApp and Messenger products and feature a chatbot powered by the Google Assistant. Allo, such as WhatsApp, will also have end-to-end encryption when it is rolled out this summer. Amazon's Echo, a surprise hit that has other tech giants racing to match it, uses a virtual assistant called Alexa, a cloud-based system that controls the Echo speaker and responds to voice-controlled commands by users.

Overnight on October 14, 2015, Tesla introduced an semi-autonomous driving system for owners of the Model S. Within a day, owners began uploading videos of themselves being driven around. You can see the fear wash over people's faces when cars slow down in front of them or the Model S automatically changes lanes. They brace themselves for impact. You can tell that part of them just wants to throw their hands on the steering wheel and take over. But slowly, as the car makes the right choices over and over, the human drivers slowly relax and enjoy the experience.

Given that the reality of AI may be fast approaching, it's of the utmost importance that we work out what might a future with artificial intelligence might look like. Last year, an open letter with signatories including Stephen Hawking and Nick Bostrom called for AI to be of demonstrable benefit to humanity, or risk something that exceeds our ability to control it. AI, as conceived of in popular culture, does not yet exist, even if autonomous and expert systems do. Smartphones might not be supercomputers, but they are called "smartphones" for good reason, in terms of how their operating systems function. Equally, we are happy to talk about a computer game's "AI", but gamers quickly learn to take advantage of its limitations and inability to "think" creatively.

Jonathan Smithers, Law Society president, talks to Catherine Reed following a thought leadership event on the issue of the application of the law to machine learning and artificial intelligence. Read the transcript (PDF) Can't see the podcast? These issues and more will be explored further on 21 June at the Law Society's first ever conference on this theme "Lawyers and Robots: partnership of the future" as part of London Technology Week. For further information and to book you place visit the booking page or email events@lawsociety.org.uk.

Editor's note: This is the first of two articles exploring the role of the IT channel in robotic process automation. Part one provides an overview of how IT services firms expect to benefit from software robots, while part two examines deployment models, labor issues and the technology's future. This expert handbook explores opportunities in enterprise mobility market, delving into detail on those with the greatest potential return for VARs, systems integrators and IT consultants. This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent.

The machine learning community has coalesced around Google's TensorFlow library. Interestingly, one major holdout was DeepMind, which did most of its research on the Torch7 library. Then, late last month, DeepMind announced it was moving to TensorFlow as well -- it was already using it for portions of AlphaGo. Why does any of this matter? Well, with standardization comes the opportunity for optimization, and Google has gone wild with optimization in this case.

Given that the reality of AI may be fast approaching, it's of the utmost importance that we work out what might a future with artificial intelligence might look like. Last year, an open letter with signatories including Stephen Hawking and Nick Bostrom called for AI to be of demonstrable benefit to humanity, or risk something that exceeds our ability to control it. AI, as conceived of in popular culture, does not yet exist, even if autonomous and expert systems do. Smartphones might not be supercomputers, but they are called "smartphones" for good reason, in terms of how their operating systems function. Equally, we are happy to talk about a computer game's "AI", but gamers quickly learn to take advantage of its limitations and inability to "think" creatively.

It's a known fact that bagging (an ensemble technique) works well on unstable algorithms like decision trees, artificial neural networks and not on stable algorithms like Naive Bayes. The well known ensemble algorithm Random forest thrives on the ability of bagging technique which leverages the'instability' of decisions trees, to help build a better classifier. Even though, random forest attempts to handle the issues caused by highly correlated trees, does it completely solve the issue? Can the decision trees be made more unstable than what random forest does, so that the learner be even more accurate? If trees are sufficiently deep, they have very low bias.