The market research firm expects the attach rate of AI-based systems in new vehicles to increase from 8 percent in 2015 (the vast majority of today's AI systems in cars are focused on speech recognition) to 109% in 2025. IHS sees multiple AI systems of various types to be installed in many cars. In the human-machine interface in vehicles, IHS believes AI will play a role in speech and gesture recognition, eye-tracking, driver monitoring and natural language interfaces. In the autonomous car, AI will advance machine vision systems, while it will also migrate in sensor fusion electronic control units (ECU). In a phone interview with EE Times, Luca De Ambroggi, principal analyst, automotive semiconductors at IHS told us, "AI is viewed as a key enabler for real autonomous vehicles. Everyone in the automotive supply chain is getting pretty bullish."

As the Director of Data Science for an advanced analytics company, Sean brings machine learning automation into business applications to help organizations build core strategies around data. Having worked across diverse industries, and alongside many talented professionals, Sean has seen the blend of approaches required to successfully convert raw data into real world value. Sean holds his doctorate in scientific computing where he used advanced mathematics, parallel computing and optimization to solve challenges in nanotechnology, chemistry and renewable energy. After completing his Ph.D. Sean started his own Data Science consulting practice, helping companies automate decision-making and uncover the underlying patterns that drive business environments. Sean has since worked for global consulting firms and silicon valley startups to help bring the advances in machine learning to business applications.

If you write marketing or advertising text for a living, you may want to get a second job skill. That's because software that writes text is here, and it is tackling a growing list of assignments. Several companies offer software that regularly churns out thousands of stories and reports based on structured data, like financial results. Ads that literally write themselves emerged last week, as IBM announced a new service based on its Watson supercomputer. A program called Quakebot has generated earthquake stories for the LA Times.

Akihiro Kishimoto is a research staff member at IBM Research – Ireland working on a range of projects in artificial intelligence, parallel and distributed computing and search. His interest in these technical fields grew from his passion for board games. And while a student at the University of Tokyo, he and three of his fellow classmates designed ISshogi, a program to play the incredibly complex (and ancient) Japanese board game, Shogi. ISshogi won the World Computer Shogi Championships four times from 1997-2005. While studying AI at the University of Alberta, Akihiro was a member of the GAMES group (Game-playing, Analytical methods, Minimax search and Empirical Studies) in the Department of Computing Science, and worked with Jonathan Schaeffer and others to solve Checkers.

DVDs were first launched in Japan, Travelocity opened up as the first online booking agent, eBay, Ask Jeeves also opened their online doors and the Spice Girls had their first UK number-one. You get the point (well except the Spice Girls bit) – it was an inflection point with technology, and 20 years later we are that same point again with AI, sometimes referred to as cognitive technologies. At the time I was fortunate to work for a very innovative company who had developed the first generation of SaaS solution for managing supply chains. So as you can imagine I spent a lot of my time sat in meetings trying to convince executives the internet was going to change the world and they needed to innovate. What we forget (which seems silly now) is many of these execs either dismissed the technology, or worse, had convinced themselves they get it and have a solid plan.

London: An intelligent and highly sophisticated robot developed by a research team of University of Birmingham in the UK is joining the world of work as a trainee office manager. The robot, named Betty, will greet guests at reception and carry out tasks at the Transport Systems Catapult, based in Milton Keynes, in the UK, for a two-month trial period. Betty's duties will include patrolling the offices, assessing how many staff members are in the office outside working hours and monitoring the environment by collating data on clutter, office temperature, humidity and noise. She will also check fire doors are closed and desks are clear. A highly sophisticated robot, Betty runs Artificial Intelligence-driven software developed by an international research team led by the University of Birmingham.

Apple CEO Tim Cook opened up the company's WWDC week by noting that his keynote would focus on the company's four device platforms: Apple Watch, Mac, iPhone/iPad, and TV. The operating systems that power these products have been the foundation of Apple's enviable technology ecosystem--its collection of hardware, software, and services that complement each other and enhance the value of the aggregate even more than each component. Microsoft has finally brought the same version of Windows to desktop and phone, and Google has allowed Android apps to invade Chrome OS. By contrast, Apple remains committed to a unique user experience on each of its devices. It has, for example, refused to bring touch screens to the Mac or allow iOS apps to run on the Mac.

Japan's electronics makers are beefing up efforts to recruit hard-to-find artificial intelligence experts -- a critical resource as connected technologies and services loom large on the industry's path forward. Growth in the number of college graduates with AI expertise -- typically math whizzes or engineers with additional knowledge of programming languages and data analysis -- has failed to keep pace with rising demand for such talent. The global supply is only in the tens of thousands, pitting companies expanding AI research operations against each other in the search for top recruits. Sony will next spring begin bulking up its ranks of such new graduates with a specialized recruiting framework for research and development in AI and machine learning. No limit will be set on the number of staff that can be hired, unlike under the company's normal recruiting system.

In Machine learning and statistics, a common task is to fit a model to a set of training data. This model can be used later to make predictions or classify new data points. When the model fits the training data but does not have a good predicting performance and generalization power, we have an overfitting problem. Regularization is a technique used to avoid this overfitting problem. The idea behind regularization is that models that overfit the data are complex models that have for example too many parameters.

The team at Facebook discusses DeepText, their engine that analyses posts and comments on Facebook, to make a better product. Just imagine what the equivalent at Google does with all your phone conversations. "Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people's experiences with our products, whether we're surfacing more of the content that people want to see or filtering out undesirable content like spam. With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages. DeepText leverages several deep neural network architectures, including convolutional and recurrent neural nets, and can perform word-level and character-level based learning. We use FbLearner Flow and Torch for model training. Trained models are served with a click of a button through the FBLearner Predictor platform, which provides a scalable and reliable model distribution infrastructure. Facebook engineers can easily build new DeepText models through the self-serve architecture that DeepText provides."