Banks are working to meet digital disruption head-on as they look to meet customer demands with technologies such as beacon technology and Artificial Intelligence. Citi Bank is deploying beacon technology across a number of its Smart Banking branches in Manhattan. The trial, which will see Bluetooth Smart Beacons give customers cardless entry into ATM lobbies after hours, comes as part of an on-going drive to bring in new technologies. Citi is hoping to use the technology from Gimblar to let customers use their iPhone or iWatch to access the bank even when it is not open. The bank has also recently launched a voice biometrics solution to verify a customer's identify within the first few seconds of call.

For anyone that thinks artificial intelligence (AI) belongs firmly in the future, it's worth taking a moment to remember that the technology has its roots squarely in the past; 60 years in the past to be precise. Six decades ago, delegates gathered at the first Dartmouth Conference to hear about an exciting new world of "artificial intelligence". It's said amongst IT historians that this was the first time the term was ever used. Today there are a lot of practical applications for AI but many people can't imagine a real world example that doesn't end with a group of crazy megalomaniac robots taking over the planet and wiping out humanity. But, as with many scientific advances, the reality is a lot simpler, modest and, dare we say, down-to-earth. Take Facebook's recent announcement about launching a range of chatbots.

Joi Ito/Flickr (CC)/Index VenturesSaul Klein (left) and Robin Klein (right.) Saul and Robin Klein are a father and son team who have invested in some of Europe's biggest technology startups. Saul Klein also cofounded LoveFilm and startup accelerator Seedcamp, and was one of Skype's original executives. Now the pair are joining forces for their own venture capital fund: LocalGlobe, which they say will invest in startups at the seed stage across Europe. So far the fund has announced investments in online mortgage advisor Trussle and also Estonian job search app Jobbatical. Business Insider met with the Kleins at LocalGlobe's office in London to talk about Europe's technology potential, whether we're in a tech bubble, overvalued startups, artificial intelligence and Brexit. Robin Klein: The number of new companies being formed just keeps growing and growing and growing. We think seed capital of a kind that we provide is just fundamental to this ecosystem. It's what we've done for years, it's what we think we know, what we think we're good at. But it's never going to meet the aspirations of thousands of founders who are creating great companies. Saul Klein: On the UK/Europe side, as my Dad said, we've both been involved in the industry now for [a long time.] I started doing this in October 1993, so well over 20 years since we put The Telegraph online. You add innovations, the first e-commerce transaction in the UK was 1995. I then went off to the US and spent 1995 to 2002 in the US so I saw the US bubble burst. I didn't see the UK bubble burst. But we did invest in about eight companies at the time, including lastminute.com. In the US when we saw the bubble burst there, our fortunate seed investment in the US was a company called Pyro Labs which was Blogger which got sold to Google before the IPO. The bottom line is that we've both lived and worked through at least three or four very significant cycles where things have been amazing then things have been terrible and'no tech company will ever get funded again,' 'no company will ever go public.' 'Everyone's crazy, what are they're thinking?' 'This whole internet thing is just these stupid kids.' 'It's going to go away.' We've seen here in Europe and in the US these very, very significant cycles where the sentiment, whether it's media sentiment, investor sentiment, public market sentiment, corporate sentiment, [they] have all gone through massive crashes.

Graduate recruitment at auditors and accountants could fall by as much as 50% by 2020 due to the impact of artificial intelligence, according to a top executive of "Big Four" accountant EY. Steve Varley, chairman and managing partner for the UK and Ireland at EY, told the Financial Times: "Over time our graduate needs are coming down." The "Big Four" -- EY, PwC, KPMG and Deloitte -- are between them one of the biggest graduate employers in the UK. Globally, the auditing and accounting industry is also one of the biggest graduate recruiters. If recruitment reduces, thousands of grads will have to find somewhere else to start their careers.

Software services major Infosys has launched an artificial intelligence platform'Mana' that will help clients drive automation and innovation. The company said that the platform, that brings machine learning together with'deep knowledge of an organisation', will enable businesses to continuously reinvent their system landscapes and lower maintenance cost of assets. Coupled with Aikido service offerings, Mana will help clients capture knowledge while delivering new and delightful experiences to their end users, it said. "Over the last 35 years, Infosys has maintained, operated and managed systems with global clients across every industry. Building on this deep experience, Infosys has recognised the need to bring artificial intelligence to the enterprise in a meaningful and purposeful way," Infosys CEO and Managing Director Vishal Sikka said at Infosys Confluence 2016.

When my son was coming to the end of Harry Potter and the Deathly Hallows, having avidly consumed the previous six books in the series, his progress noticeably slowed. He'd go days, weeks even, before finishing a chapter – so much so that we thought that he was going off the story altogether. He was drawing it out. Like millions of other fans, he simply could not face leaving Hogwarts. Harry, Ron and Hermione had become more than characters: they were friends.

Watson, IBM's computer brain, has a lot of talents. It mastered "Jeopardy!," it cooks, and even tries to cure cancer. On Tuesday, IBM Security announced a new cloud-based version of the cognitive technology, dubbed "Watson for Cybersecurity." In the fall, IBM will be partnering with eight universities to help get Watson up to speed by flooding it with security reports and data. The plan as of now is for Watson to process up to 15,000 documents about digital security a month -- including everything from blog posts to videos -- so that it can get a feel for the sometimes esoteric terminology of the cybersecurity world.

It's no secret that much of the wisdom of the world lies in unstructured data, or the kind that's not necessarily quantifiable and tidy. So it is in cybersecurity, and now IBM is putting Watson to work to make that knowledge more accessible. Towards that end, IBM Security on Tuesday announced a new year-long research project through which it will collaborate with eight universities to help train its Watson artificial-intelligence system to tackle cybercrime. Knowledge about threats is often hidden in unstructured sources such as blogs, research reports and documentation, said Kevin Skapinetz, director of strategy for IBM Security. "Let's say tomorrow there's an article about a new type of malware, then a bunch of follow-up blogs," Skapinetz explained.

Over the last few blog posts, I've discussed some of the basics of what machine learning is and why it's important: Throughout those posts, I've been using the following definition of machine learning: creating computational systems that learn from data in order to make predictions and inferences. However, machine learning isn't the only subject in which we use data for prediction and inference. Anyone who's taken an introductory statistics class has heard a similar definition about statistics itself. And if you talk to someone who works in data-mining, you'll hear the same thing: data mining is about using data to make predictions and draw conclusions from data. This raises the question: what is the difference between machine learning, statistics, and data mining? The long answer has a bit of nuance (which we'll discuss soon), but the short answer answer is very simple: machine learning, statistical learning, and data mining are almost exactly the same.

Delhi: In one of the biggest exposes of 2016, it has been revealed that in order to bag tender for biometric facial recognition device, Cryptometrics, a company in Canada, gave kickbacks to officers of Air India. Biometric facial recognition device is used for recognition of faces of passengers. In an exclusive report, Zee Media Corp has learnt that on 24 February 2006, Air India had issued a Request for Proposal for the device and the tender for the same given by 20 companies including Canada's Cryptometrics. Later, it was revealed in order to get the tender, Cryptometrics paid kickbacks to Air India officials through a person named Nazir Karigar. His closeness with Air India officials can be ascertained from the fact that Nazir had the full copy of the tender with him on 28 December 2005 itself. Whereas Air India had issued the tender on 24 February 2006.