" A revolution will happen when tools like Siri can truly serve as your personal assistant and you start relying on such an assistant throughout your day. To get there, these systems need more knowledge about your life and preferences, more knowledge about the world, better conversational interfaces and at least basic commonsense reasoning capabilities. I have interviewed Alon Halevy, Executive Director at Recruit Institute of Technology. What is the mission of the Recruit Institute of Technology? Alon Halevy: Before I describe the mission, I should introduce our parent company Recruit Holdings to those who may not be familiar with it.

One of the striking things about Blizzard, the superstar developer behind some of gaming's biggest hits, including World of Warcraft, Diablo and Starcraft, is how little it actually does. That's not to say the company's employees aren't constantly at work, although the Kendo lessons taking place on the lawn outside its headquarters in Irvine, California, on the sunny spring day I visit could give that impression. The HQ is a hive of industry, even if most of that industry is hidden behind doors marked Secret: No Visitors. But that list of smash hits above constitutes fully half of the franchises Blizzard is developing. Those three are stalwarts at the company: World of Warcraft is celebrating its 10th anniversary, Starcraft II is six years old and two expansion packs into its life, and Diablo III is enjoying a second wind as an acclaimed couch co-op game four years after it first launched.

GCP (Google Cloud Platform) Next 2016 conference was held in San Francisco, which gave some insights into the upcoming GCP roadmap, and acted as a reminder that Google needs to be taken seriously in the Public Cloud Provider space. The geographic expansion raised probably the most excitement: Google has committed to add two additional data centers this year to the current 3, following by yet another 10 new datacenters in 2017. This will be an impressive geographical coverage ramp up in two years, and will act as genuine competition against the other big providers. It looks like Google has a well cooked "recipe" for building cloud data centers, and in fact they have not kept this as a secret to themselves, but released it for public consumption with all the standard best practises, along with other papers such as its highly scalable network load balancer design. While the platform is geographically expanding, the focus is also on technology innovations and the Google team are releasing Machine Learning and Big Data offerings one after the other at a fast pace. Nowadays, Machine Learning (ML) is playing a key role in all aspects of IT, including the operating data centers (according to Google).

Dr. Quoc Viet Le is a research scientist at Google Brain known for his path-breaking work on deep neural networks (DNN). He is especially famous for his Ph.D work in image processing under Andrew Ng, one of the pioneers of the DNN revolution. Le's and Ng's work demonstrated how computers could be used to learn complicated features and patterns in a way similar to how the mammalian brain learns. This revolutionized the interest in DNNs, and got the current giants of the computer industry such as Google, Facebook and Microsoft in a race to incorporate AI techniques into their software. DNNs perform effectively in tasks such as image processing, handwriting recognition and game-playing, and are being explored for solutions to other problems such as self-driving cars, robotics, medical diagnosis and environmental and social problems.

Access to data is one thing. Moving from data to insight is another entirely. Jane Zavalishina, CEO of the Yandex Data Factory wants to make it easier for businesses to gain real insight from their data. Built on the real time personalization and predictive analytics technology of Russia's largest Internet business Yandex- Yandex Data Factory helps clients improve their business through the exploitation of their own data by machine learning. Disproportionate growth of figures suggesting that 90% of the world's data was generated over the course of the past two years has led Zavalishina to be of the opinion that "we should not really care about data anymore," rather, we should see it as a thing of the past.

From Facebook to Amazon to Microsoft to Apple, big tech companies are racing to improve speech-synthesis systems. And the systems, which have become increasingly realistic-sounding, have a lot of potential benefits--from serving the blind, to helping people who are illiterate access information online, to assisting the elderly. TechRepublic spoke to Alan Black, a Carnegie Mellon University (CMU) researcher who studies speech-synthesis systems. Black explained what's new in voice-recognition, the current challenges, and what we should be concerned about. What is the current technology behind speech-recognition?

We recently ran some fresh benchmarks for Spark v1.1 and v1.2 and Graphlab clusters, and included some updated numbers from other recent published benchmarks. RCV1-v2 (Reuters news data, LYR2004 distribution) benchmarks are for OAA (One Against All) classification, since RCV1-v2 has 103 independent topic labels. RCV1-v2 is a small dataset (0.5 GB). BIDMach was run on a single Amazon g2.xlarge instance, while Spark was run on a cluster of m3.2xlarge high-memory instances. The other systems were run on an 8-code Intel E-2660 system.

A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here--it's about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines' backs. It is surprisingly warm inside, as if the cluster were alive. Today's Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred "instances" of the AI at once. Like all things cloudy, Watson is served to simultaneous customers anywhere in the world, who can access it using their phones, their desktops, or their own data servers. This kind of AI can be scaled up or down on demand.

In recent years however, information technology has entered the field of international politics gaming and made some major contributions. The most successful international politics games at present are concerned with the personalities of political adversaries. An interesting international politics game could define personality in several variables including concepts like aggressiveness, nastiness, and paranoia. Computer programs would allow then the international politics gamer to vary personalities by ascribing a different numerical value to each of these variables. In this way, an infinite number of different "artificial" personalities can be created by means of using concepts like heuristics, algorithms, fuzzy logic, statistics, neural networks, and virtual reality.

It's not crazy to think investors and drivers will witness more innovation and change in the automotive industry over the next two decades than what took place over the last century. Technology and smartphones are enabling businesses like Uber to thrive seemingly overnight. Young people moving back into an urban lifestyle are creating opportunities for companies to think differently about how people travel on a daily basis. But perhaps the most intriguing storyline of all is the future of driverless cars. Here are three analysts with the reasons they believe driverless cars are here to stay.