Drawing an accurate sketch of a person's face is an art that is hard for most people to master. But it turns out to be relatively easy for computers. Various programs exist for converting images into line drawings. That often produces a decent start, although these systems can have difficulty with shadows and high contrast. A more promising approach is to use machine-vision algorithms that rely on neural networks to extract features from an image and use these to produce a sketch.

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Product shipments of artificial intelligence (AI) systems for vehicles will grow from 7 million in 2015 to 122 million by 2025, which, according to IHS Technology, is a reflection of the automotive industry's growing appetite for AI.

The most common question asked by prospective data scientists is – "What is the best programming language for Machine Learning?" The answer to this question always results in a debate whether to choose R, Python or MATLAB for Machine Learning. Nobody can, in reality, answer the question as to whether Python or R is best language for Machine Learning. However, the programming language one should choose for machine learning directly depends on the requirements of a given data problem, the likes and preferences of the data scientist and the context of machine learning activities they want to perform. According to a survey on Kaggler's Favourite Tools, the open source R programming language turned out to be the favourite among 543 Kagglers of the 1714 Kaggler's listing their data science tools.

Modern computers are powerful data-processing machines, but they still need a tremendous amount of information to accomplish certain feats of recognition. Researchers at Harvard University are working hard to rectify this situation. Computers have grown from bulky room-size contraptions that could do simple calculations, to supercomputers capable of simulating extremely complex tectonic movements, involving 1 quadrillion floating-point operations (FLOPS) each second. To illustrate the matter even better, here's a great article that explains a 1 trillion-fold increase in computing performance through history. Then again, even though our brains can't compete with the sheer speed with which computers churn out results of even the most complex equations, when it comes to things we take for granted, like creativity, abstract thinking or pattern matching, machines fall way behind.

Tokyo, December 10, 2015 - NEC Corporation (NEC; TSE: 6701) today announced the development of a'system operations-visualization and anomaly-analysis technology' that uses artificial intelligence (AI) to automatically detect unknown cyber-attacks against social infrastructure and enterprise systems. The new technology learns (through machine learning) the normal state of OS-level operations (program start-up, file access, communications, etc.) for entire ICT systems, including PCs and servers. It then carries out real-time comparisons and analysis of current operations in the system's normal state and automatically isolates particular points that deviate from the normal state by using system operation tools and Software-Defined Networking (SDN). Further, a detailed knowledge of the system behavior makes it possible to identify the extent of damage 90% faster than the time required in conventional manual investigation. Accurate anomaly detection and quick specification of damaged areas by the new technology minimize the damage from cyber-attacks and enable recovery without stopping an entire user-system.

A new office manager has been hired on a trial basis at the Transport Systems Catapult in Milton Keyenes in an attempt to determine if artificial intelligence can do the job better than a human can. Betty the Robot will be on staff for a two-month trial period as she acclimates to the office environment and carries out tasks that are normally handled by a human counterpart. Some of the duties that Betty the Robot will be carrying out include regular patrols of the office spaces, keeping track of the number of employees that work after hours, collecting data regarding clutter, regulating the temperature in the office, measuring the noise and humidity levels, as well as ensuring doors are closed and desks are clean of clutter in the absence of workers, according to the Mirror. Betty the Robot may actually be doing more work than her human counterparts, in less time. She will not complain about the workload and she will eagerly work beyond the normal 9-5 shift without worry of being impacted by stress, sickness, or other unexpected personal issues.

The concept of machine learning has been around in the advertising space for some time now. Advertisers are using programmatic technology to create better ads in real-time (Profile Audiences targeting and DCO: dynamic creative optimization), essentially getting the right ad to the right person at the right time. This technology, however, can be and is being drastically improved.

Whereas it may be little more than a minor nuisance if your laptop crashes or gets hacked, it becomes all the more important that an AI system does what you want it to do if it controls your car, your airplane, your pacemaker, your automated trading system or your power grid. Another short-term challenge is preventing a devastating arms race in lethal autonomous weapons. In the long term, an important question is what will happen if the quest for strong AI succeeds and an AI system becomes better than humans at all cognitive tasks. As pointed out by I.J. Good in 1965, designing smarter AI systems is itself a cognitive task.

The area around Hillview Avenue in Palo Alto is dotted with well-known tech innovators: Xerox's PARC, Microsoft's Skype, VMware Inc. and HP Labs, among others. Amid the research centers and campuses of these tech stalwarts is another well-known company, but one whose name might seem somewhat out of place among these Silicon Valley trailblazers. Ford Motor Co. F, 1.32% is hoping to change that. Last year, the auto giant hung its shingle outside what it calls the Ford Research and Innovation Center, Palo Alto, as it seeks to embrace technology's disruption of its 100-plus-year-old business. With personal auto ownership as passe as telephone landlines to a new generation of consumers, electric-car powerhouse Tesla Motors Inc. TSLA, 1.27% -- also based in Palo Alto--upending the industry, and self-driving vehicles predicted in our future, Ford, like most auto makers around the world, is behind the proverbial eight ball. The automotive pioneer that developed the first mass produced, affordable car is experiencing the "innovator's dilemma," a conundrum faced by leading companies when a new, often cheaper, "good enough" technology breaks into its market dominance.