When we think about Artificial Intelligence, we often consider its potential in relation to the realms of our possibility – what will it be able to do that we can do? To my mind, that is entirely missing the point of an artificial "neural" network that is infinitely more powerful than the percentage of our brains that we are able to access at any one time. What will A.I. be able to do that we can't even dream of? I'll give the simplest example that I can. Way back in the early 1980s, there was a computer game called Breakout, where a horizontal paddle (bat) could be moved at the bottom of the screen, bouncing a ball up at tiles every time.

Do you think you can tell a piece of music composed by artificial intelligence (AI) from one created by a human composer? Before you read any further, let's find out. The following audio consists of two fragments, one written by AI, the other by a human. If you didn't get it right the first time, no worries--we'll have a couple more mini-quizzes like this below. The AI that wrote the fragment above has been programmed by Jukedeck, a UK-based startup working on machine-made music that won the competition at TechCrunch Disrupt London in 2015.

The European Union is currently considering the need to redefine the legal status of robots, with a draft report last week suggesting that autonomous bots might, in the future, be granted the status of "electronic persons" -- a legal definition that confers certain "rights and obligations." It sounds like science fiction and that's because it is: any engineer will tell you we're a long way from seeing robot marches for civil rights. For a start, this is only a draft report. It's not actual legislation, and is only a series of recommendations for the EU's law-making body -- they could always ignore it completely. And although parts of the report are a bit odd (Frankenstein's monster, the Greek myth of Pygmalion, and the Golem of Prague are all referenced in the first paragraph alone), at its core it's interested in the rights of people, not the rights of robots.

Christina is audience development editor. After graduating from the University of Nottingham reading philosophy and theology in 2013, Christina joined a tech start-up specialising in mobile apps. She has a keen interest in the mobile platform and innovative tech. In recent years AI has brought us some pretty impressive and widely used tech, from the image recognition being used by Facebook to speech recognition technology at work in Amazon's Alexa or Apple's Siri. It's these breakthroughs in deep learning and neural networks that have led to some of the most exciting yet also worrying times in tech. Stephen Hawking, Elon Musk and Bill Gates (to name a few) have all warned us about the dangers of unregulated AI development.

Persistence Market Research delivers pertinent insights on the growth of the Cognitive Computing Market and identifies key market dynamics impacting this growth. New York City, NY -- (SBWIRE) -- 01/27/2017 -- In the ever changing world of information technology, business organizations are left with humongous amount of data with them. This data includes very critical information for business use, but business organizations are only able to utilize 20% of whole data available with them with the use of traditional data analytics technology. To process and interpret the reaming 80% of the data that is in the form of videos, images, and human voice (also called as dark data), there is a need of cognitive computing systems. Cognitive computing systems are typical combination of hardware and software that constitute natural language processing (NLP) and machine language, and have capability to collect, process, and interpret the dark data available with business organizations.

Most people don't buy a jar of relish every week. But when they decide to buy one from Ocado--the world's largest online-only grocery retailer--they don't have to scrabble at the back of the store. Instead, they call on robots and artificial intelligence to have it delivered to their door. Ocado claims that its 350,000-square-foot warehouse in Dordon, near the U.K.'s second city of Birmingham, is more heavily automated than Amazon's warehouse facilities. The company's task is certainly more challenging in many respects: most of the 48,000 lines of goods that it sells are perishable, and many must be chilled or frozen.

Reports are out that a Chinese robot has written and published its first newspaper article. The news comes the same month as a Japanese insurance company announced it was replacing 34 workers with an artificial intelligence system. "This is absolutely a wake-up call," said Zeus Kerravala, an analyst with ZK Research, who added that it's time for people to think about their careers and if a robot or A.I. system could easily replace them. "We are the beginning of robots taking jobs," he added. But the fact is, we've had other revolutions -- like the birth of the assembly line."

A typical viral marketing model identifies influential users in a social network to maximize a single product adoption assuming unlimited user attention, campaign budgets, and time. In reality, multiple products need campaigns, users have limited attention, convincing users incurs costs, and advertisers have limited budgets and expect the adoptions to be maximized soon. Facing these user, monetary, and timing constraints, we formulate the problem as a submodular maximization task in a continuous-time diffusion model under the intersection of a matroid and multiple knapsack constraints. We propose a randomized algorithm estimating the user influence in a network ($|\mathcal{V}|$ nodes, $|\mathcal{E}|$ edges) to an accuracy of $\epsilon$ with $n=\mathcal{O}(1/\epsilon^2)$ randomizations and $\tilde{\mathcal{O}}(n|\mathcal{E}|+n|\mathcal{V}|)$ computations. By exploiting the influence estimation algorithm as a subroutine, we develop an adaptive threshold greedy algorithm achieving an approximation factor $k_a/(2+2 k)$ of the optimal when $k_a$ out of the $k$ knapsack constraints are active. Extensive experiments on networks of millions of nodes demonstrate that the proposed algorithms achieve the state-of-the-art in terms of effectiveness and scalability.

Classrooms are noticeably more hi-tech these days - interactive boards, laptops and online learning plans proliferate, but has the curriculum actually changed or are children simply learning the same thing on different devices? Some argue that the education this generation of children is receiving is little different from that their parents or even their grandparents had. But, in a world where artificial intelligence and robots threaten jobs, the skills that this generation of children need to learn are likely to be radically different to the three Rs that have for so long been the mainstay of education. The BBC went along to the Bett conference in London in search of different ways of teaching and learning. A stone's throw from the Excel, where Bett is held, stands a new school that is, according to its head Geoffrey Fowler, currently little more than a Portakabin.

Artificial intelligence that is as accurate as human specialists at identifying skin cancer has been developed by computer scientists and dermatologists. The breakthrough was made by a team at Stanford University, who trained a deep-learning algorithm to diagnose skin cancer using a database of around 130,000 skin disease images. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," said Sebastian Thrun, a professor at the Stanford Artificial Intelligence Laboratory. A woman covers herself in suncream to stress the point that people should protect themselves from the sun as part of a Cancer Research Campaign, April 8, 1998. Researchers have developed an Artificial Intelligence program that can diagnose skin lesions as accurately as any specialist.