I am sure by now, you have heard the phrase that has been thrown around quite a lot by mostly, venture capitalists: "Artificial Intelligence (AI) is the new mobile." The reason why this phrase has been echoed in the tech industry is to emphasize that AI is not a short-lived fad, rather a revolution like mobile. More importantly, they seem to be right as in the last five years, giant tech companies have been pouring money into this technology. In fact, over 200 private companies using AI algorithms across different verticals have been acquired since 2012, with over 30 acquisitions taking place in Q1'17 alone. The acquisitions of AI startups are getting feisty, too.

By the way, you can listen to a neuron fire here (what you're actually hearing is the electro-chemical firing of a neuron, converted to audio). Some electrodes want to take the relationship to the next level and will go for a technique called the patch clamp, whereby it'll get rid of its electrode tip, leaving just a tiny little tube called a glass pipette,21 and it'll actually directly assault a neuron by sucking a "patch" of its membrane into the tube, allowing for even finer measurements:39 A patch clamp also has the benefit that, unlike all the other methods we've discussed, because it's physically touching the neuron, it can not only record but stimulate the neuron,22 injecting current or holding voltage at a set level to do specific tests (other methods can stimulate neurons, but only entire groups together). Finally, electrodes can fully defile the neuron and actually penetrate through the membrane, which is called sharp electrode recording. If the tip is sharp enough, this won't destroy the cell--the membrane will actually seal around the electrode, making it very easy to stimulate the neuron or record the voltage difference between the inside and outside of the neuron. But this is a short-term technique--a punctured neuron won't survive long.

Cormac McCarthy is best known to the world as a writer of novels. These include Blood Meridian, All the Pretty Horses, No Country for Old Men, and The Road. At the Santa Fe Institute (SFI) he is a research colleague and thought of in complementary terms. At SFI we have been searching for the expression of these scientific interests in his novels and we maintain a furtive tally of their covert manifestations and demonstrations in his prose. Over the last two decades Cormac and I have been discussing the puzzles and paradoxes of the unconscious mind. Foremost among them, the fact that the very recent and "uniquely" human capability of near infinite expressive power arising through a combinatorial grammar is built on the foundations of a far more ancient animal brain. How have these two evolutionary systems become reconciled? Cormac expresses this tension as the deep suspicion, perhaps even contempt, that the primeval unconscious feels toward the upstart, conscious language. In this article Cormac explores this idea through processes of dream and infection. It is a discerning and wide-ranging exploration of ideas and challenges that our research community has only recently dared to start addressing through complexity science. I call it the Kekulé Problem because among the myriad instances of scientific problems solved in the sleep of the inquirer Kekulé's is probably the best known.

Chances are, if you are searching for a tutorial on artificial neural networks (ANN) you already have some idea of what they are, and what they are capable of doing. But did you know that neural networks are the foundation of the new and exciting field of deep learning? Deep learning is the field of machine learning that is making many state-of-the-art advancements, from beating players at Go and Poker, to speeding up drug discovery and assisting self-driving cars. If these types of cutting edge applications excite you like they excite me, then you will be interesting in learning as much as you can about deep learning. However, that requires you to know quite a bit about how neural networks work. This tutorial article is designed to help you get up to speed in neural networks as quickly as possible. In this tutorial I'll be presenting some concepts, code and maths that will enable you to build and understand a simple neural network. Some tutorials focus only on the code and skip the maths – but this impedes understanding. I'll take things as slowly as possible, but it might help to brush up on your matrices and differentiation if you need to. The code will be in Python, so it will be beneficial if you have a basic understanding of how Python works. You'll pretty much get away with knowing about Python functions, loops and the basics of the numpy library. By the end of this neural networks tutorial you'll be able to build an ANN in Python that will correctly classify handwritten digits in images with a fair degree of accuracy. Once you're done with this tutorial, you can dive a little deeper with the following posts: All of the relevant code in this tutorial can be found here. Here's an outline of the tutorial, with links, so you can easily navigate to the parts you want: Artificial neural networks (ANNs) are software implementations of the neuronal structure of our brains. We don't need to talk about the complex biology of our brain structures, but suffice to say, the brain contains neurons which are kind of like organic switches. These can change their output state depending on the strength of their electrical or chemical input. The neural network in a person's brain is a hugely interconnected network of neurons, where the output of any given neuron may be the input to thousands of other neurons.

The offer will be available in France for Orange employees from mid-May and for the general public from 6 July 2017. Customers can subscribe directly from the mobile application, online or in one of Orange's 140 certified stores. Innovative and specifically designed for mobile uses, the offer will provide customers from launch with a bank account, a debit card, overdraft protection and an interest-bearing savings account. Additional services, such as credit and insurance, will gradually be included in the offer. Right from the outset, the service will integrate a number of cutting-edge, digital and banking innovations including contactless mobile payments, sending money by SMS, instant bank balances, temporary freezing of the debit card and 24/7 access to a bank advisory service.

Artificial intelligence (AI) will "significantly transform" the insurance industry in the next three years, with insurers investing in AI to empower agents, brokers and employees to enhance the customer experience with automated personalized services, faster claims handling and individual risk-based underwriting processes, according to a new report from Accenture. The Technology Vision for Insurance 2017 report, called Technology for People, released on Wednesday by the global professional services company, found that while the technology will be empowering, insurers face challenges integrating AI into their existing technology. Insurers cite issues such as data quality, privacy and infrastructure compatibility. The report is based on the insights of a technology advisory board, interviews with industry technologists and a survey of more than 550 insurance executives across 31 countries in North America, Europe, Asia-Pacific, Africa and South America, Accenture noted in a press release. The goal of the survey was to identify the key issues and priorities for technology adoption and investment.

How many virtual assistants can you fit in one smartphone? European network operator Orange is hoping there's room to squeeze in one more. With the right apps, you can already talk to Alexa, Cortana and Google through your smartphone -- and maybe also to Siri or Bixby if you went with one of the big brands. Djingo will be able to answer questions, send text messages, place calls, play music and video from Orange's set-top box, and control smart home devices. It draws on the company's research into linguistics and artificial intelligence, and will even offer financial advice in conjunction with a new banking service Orange is launching, the company said.

Amazon is the exception to nearly every rule in business. Rising from humble beginnings as a Seattle-based internet bookstore, Amazon has grown into a propulsive force in at least five different giant industries: retail, logistics, consumer technology, cloud computing, and most recently, media and entertainment. The company has had its share of missteps -- the expensive Fire phone flop comes to mind -- but is also rightly known for strokes of strategic genius that have put it ahead of competitors in promising new industries. This was the case with the launch of cloud business AWS in the mid-2000s, and more recently the surprising consumer hit in the Echo device and its Alexa AI assistant. Today's Amazon is far more than just an "everything store," it's a leader in consumer-facing AI and enterprise cloud services. And its insatiable appetite for new markets mean competitors must always be on guard against its next moves.

When most people think about artificial intelligence, their minds turn to glorified fights to save the human race from rogue robots, a familiar story played out on Hollywood screens in decades gone by. While machine intelligence is still far from resembling human consciousness, an AI fight is playing out in real life, not between robots and humans, but rather among the businesses vying to lead an increasingly lucrative market. The origins of AI stretch back to 1950, when computer science pioneer Alan Turing published a paper speculating that machines could one day think like humans. Last year, research firm IDC valued the market at $8 billion, forecasting a rise to $47 billion in 2020. Between Turing's landmark paper 67 years ago and today's wild market valuations, most major AI developments have either fallen in the realms of research and academia or involved computers beating people at human games.

A device that can read people's minds by detecting their brainwaves has been developed in a breakthrough that could eventually enable people with "locked-in syndrome" to communicate. The system was only partially effective with a 90 per cent success rate when trying to recognise numbers from zero to nine and a 61 per cent rate for single syllables in Japanese, the researchers said. But, nonetheless, a statement about the research issued by the Toyohashi University of Technology in Japan said it showed that an effective device to read people's thoughts and relay them to others was possible in the "near future". They even suggested an "easily operated" device with a smartphone app could be ready in just five years. An electroencephalogram (EEG) was used to monitor people's brain waves while they spoke.