Under, behind and inside many of the apps we use every day, a revolution is underway. It's a revolution that started decades ago but today is empowering companies to deliver better, smarter services with greater ease and on broader scales than ever before. At Singularity University's inaugural Global Summit, Neil Jacobstein, chair of Artificial Intelligence and Robotics, provided a primer showing how artificial intelligence literally transforms everything it touches. First of all, it's critical to define the scope of artificial intelligence (AI), which can be categorized into four areas: techniques in pattern recognition, software agency (that is, software that acts like real users), an exponential technology that is accelerating other exponential technologies, and a vision of a future superhuman intelligence (that fortunately hasn't happened yet). Anyone who has seen a science fiction film is likely familiar with this last area, but it's the other three areas where AI is making huge strides at a revolutionary pace.

Under, behind and inside many of the apps we use every day, a revolution is underway. It's a revolution that started decades ago but today is empowering companies to deliver better, smarter services with greater ease and on broader scales than ever before. At Singularity University's inaugural Global Summit, Neil Jacobstein, chair of Artificial Intelligence and Robotics, provided a primer showing how artificial intelligence literally transforms everything it touches. First of all, it's critical to define the scope of artificial intelligence (AI), which can be categorized into four areas: techniques in pattern recognition, software agency (that is, software that acts like real users), an exponential technology that is accelerating other exponential technologies, and a vision of a future superhuman intelligence (that fortunately hasn't happened yet). Anyone who has seen a science fiction film is likely familiar with this last area, but it's the other three areas where AI is making huge strides at a revolutionary pace.

Under, behind and inside many of the apps we use every day, a revolution is underway. It's a revolution that started decades ago but today is empowering companies to deliver better, smarter services with greater ease and on broader scales than ever before. At Singularity University's inaugural Global Summit, Neil Jacobstein, chair of Artificial Intelligence and Robotics, provided a primer showing how artificial intelligence literally transforms everything it touches. First of all, it's critical to define the scope of artificial intelligence (AI), which can be categorized into four areas: techniques in pattern recognition, software agency (that is, software that acts like real users), an exponential technology that is accelerating other exponential technologies, and a vision of a future superhuman intelligence (that fortunately hasn't happened yet). Anyone who has seen a science fiction film is likely familiar with this last area, but it's the other three areas where AI is making huge strides at a revolutionary pace.

This is because every auditory neuron is tuned to a certain range of sound, so that each neuron is more sensitive to particular types and levels of sound than others. In a new study, researchers have designed a neuromorphic ("brain-inspired") computing system that mimics this neural selectivity by using artificial level-tuned neurons that preferentially respond to specific types of stimuli. In the future, level-tuned neurons may help enable neuromorphic computing systems to perform tasks that traditional computers cannot, such as learning from their environment, pattern recognition, and knowledge extraction from big data sources. The researchers, Angeliki Pantazi et al., at IBM Research-Zurich and École Polytechnique Fédérale de Lausanne, both in Switzerland, have published a paper on the new neuromorphic architecture in a recent issue of Nanotechnology. Like all neuromorphic computing architectures, the proposed system is based on neurons and their synapses, which are the junctions where neurons send signals to each other.

Facebook announced Thursday that it is open-sourcing some of its latest artificial intelligence vision tools. The company is releasing years' worth of research on computer image recognition and understanding. The tools could be used to create experiences for visually impaired users, better image search on the social networking platform, and interpret live videos in real-time. On Thursday, the social networking giant unveiled several new tools to identify, delineate and label objects in an image. The aim is to help accelerate advancement in the field of machine vision as the company expands on people's interest in sharing and interacting with images and video clips.

Facebook is open sourcing a set of computer vision software tools that can identify both the variety and the shape of objects within photos. The tools, developed by the Facebook AI Research (FAIR) team, are called DeepMask, SharpMask, and MultiPathNet, and all three work in tandem to help break down and contextualize the contents of images. These technologies, though not in active use in consumer Facebook products right now, are similar to the software the company uses to describe photos to blind users, a feature it calls "automatic alternative text" that launched back in April. DeepMask and SharpMask are more experimental research projects and focus on what the FAIR team calls segmentation. While human beings can discern the various elements of a photograph in mere seconds, the process is much harder for computers, which perceive pixels as a series of number values corresponding to changes in color.

LONDON - FEBRUARY 03: (FILE PHOTO) In this photo illustration the facebook logo is reflected in the eye of a girl on February 3, 2008 in London, England. Social networking site'Facebook' reaches it's 5th birthday this month. It was founded in 2004 by Mark Zuckerberg from his dorm room at Harvard University with the aim to help students keep in touch over the internet. Within 24 hours 1,200 Harvard students had signed up. The site now has 150 million active users worldwide. Facebook is opening up its image-recognition artificial intelligence research to the public.

For the past two days, Samsung has been talking about its Galaxy Note 7's iris scanner on its online newsroom, highlighting the reasons why this new mobile security feature could be a big game changer in the mobile industry. Just yesterday, the South Korean-headquartered company discussed how the iris scanning technology is making Samsung Pass even more secure. Samsung Pass is part of Knox, the comprehensive security platform of Samsung's recent handsets. Pass previously centered on fingerprint recognition via the fingerprint scanner as a means of enhancing the identity verification process of the phone itself and certain apps. With the addition of the iris scanner, Samsung claims that the Note 7's security has reached the ultimate level thanks to this advanced biometric authentication that does not require IDs or passwords for identity authentication.

In 1997 a remarkable event caught everybody's attention - the then champion of the world Garry Kasparov lost a tournament to a supercomputer Deep Blue. It was called "a beginning of a new era of computers" by many and now it seems that time keeps justifying those loud statements... Being a sub-set of artificial intelligence, machine learning involves algorithms allowing computers to autonomously learn from input data. A fundamental distinction from "usual" software programs, such as Photoshop or, say, Excel, is that in machine learning computers don't have to be explicitly programmed but can change and improve their algorithms by themselves. The history of machine learning goes back to the 1950th. The first learning program was created by Arthur Samuel in 1952 and it was the game of checkers.

Not to mention, technological disruption that (a) erodes, (b) replaces, or (c) reverses most of the current best practices every 6-12 months. "RankBrain has become the third-most important signal contributing to the result of a search query", according to senior research scientist at Google, Greg Corrado. It's an artificial intelligence engine that uses pattern matching at scale to process millions of search queries daily. And with an 80% accuracy rating, it outperforms engineers by a wide margin. There's no wonder that it's taking over the search giant then. Part of that success comes from the ability to literally guess – based on millions of datapoints in fractions of a second – the searcher's intent behind a few random keystrokes.