As a business buzzword, "machine learning" doesn't measure up to some of its more popular cousins – big data and transformation being two of the standouts – but this may not be the case for much longer. What was once something only used by people working in fields like software engineering, statistical modeling, and artificial intelligence, is now being used in many more recognizable and consumable forms. Online services such as Google, Netflix, Amazon, and Spotify all use machine learning to improve the customer experience. For example, if you've been streaming Barry White all week, Spotify's "Discover Weekly" playlist will begin suggesting other similar artists. Listeners may start seeing Luther Vandross pop up in their playlist, for example.

Perhaps Google thinks that the chips available in the market are unable to handle the needs of its machine learning algorithms because Google today announced at its I/O developer conference that the search giant has been building its own specialized chips to power the machine learning algorithms. Google has been using the Tensor Processing Units (TPU) custom-built chips to power its data centers according to Google's senior VP for its technical infrastructure Urs Holzle. Now it wants TPU to power its machine learning algorithms. Google says it's getting "an order of magnitude better-optimized performance per watt for machine learning" and argues that this is "roughly equivalent to fast-forwarding technology about seven years into the future." Google said that it has managed to speed up the machine learning algorithms with the TPUs because it doesn't need the high-precision of standard CPUs and GPUs.

Perhaps Google thinks that the chips available in the market are unable to handle the needs of its machine learning algorithms because Google today announced at its I/O developer conference that the search giant has been building its own specialized chips to power the machine learning algorithms. Google has been using the Tensor Processing Units (TPU) custom-built chips to power its data centers according to Google's senior VP for its technical infrastructure Urs Holzle. Now it wants TPU to power its machine learning algorithms. Google says it's getting "an order of magnitude better-optimized performance per watt for machine learning" and argues that this is "roughly equivalent to fast-forwarding technology about seven years into the future." Google said that it has managed to speed up the machine learning algorithms with the TPUs because it doesn't need the high-precision of standard CPUs and GPUs.

Like many buzzwords, 'digital transformation' can mean different things to different people. Yet, essentially, it is always about using digital technology such as the cloud, mobile, big data, and analytics to enable large scale organisational change. In this way, businesses can quickly adapt to shifting customer demands while keeping up with fluctuating competition from both old and new rivals in their market. Increasingly, previously unknown companies are making a huge impact on established markets, companies and brands. The key to their success is the way they exploit the'digital transformation' phenomenon, disrupting entire markets in today's digital world. By throwing away the rulebook and fully embracing digital technology, iconic disrupters such as AirBnB and Uber are providing customers with the services they want – without being forced to simultaneously make huge capital investments.

The training is broken up into two modules, an introductory machine learning module and a grid search / model selection module. The slides that accompany this tutorial are available here. R users can use RStudio or the R console to execute the R scripts. Python users can use a Jupyter/IPython notebook to execute the scripts. To execute the cells in the notebook simply highlight the cell and press Shift Enter.

Dr. Kuansan Wang is the Managing Director for Microsoft Research Outreach, responsible for overseeing research and innovation in the area of academic services. Progress in AI research and applications is exploding, and that explosion extends to our own team working on academic services. Continuing our work supercharging Bing and Cortana, we are also applying new technologies to Microsoft Academic, which serves the research community. If you're not familiar with Microsoft Academic, this online destination helps researchers connect with the papers, conferences, people, and ideas that are most relevant, using bots that read, understand, and deliver the scientific news and papers researchers need to further their work. Designed by and for researchers like myself, the site puts the broadest and deepest set of scientific information at your fingertips, with the ability to go beyond keywords to the contextual meaning of the content.

Google announced something for everyone yesterday at its 10th annual I/O developer conference. There were more details of a new version of Android; new messaging and video-calling apps; a built-in new VR platform for Android; and a good-looking Amazon-Echo-like smart speaker called Google Home. There was even a cool new research project that will let users run portions of apps from the web without installing them first. But the biggest theme stressed by Google CEO Sundar Pichai and his lieutenants, over and over again throughout the two-hour keynote, was that Google is doubling down on artificial intelligence as the next great phase of computing. And they believe Google can do it better than anyone else.

Rumors of a Xiaomi drone have swirled for some time, with early reports suggesting that the UAV may use the company's Mi Band as a beacon for a possible "follow me" feature. Xiaomi has confirmed "something wonderful and cool is flying to us very soon," but is keeping quiet on any possible features before next week. May marks a big month for Xiaomi. It's already unveiled its huge 6.44-inch Mi Max smartphone and earlier this week announced the US release of its 4K-ready Mi Box streamer. The company also confirmed at Google I/O that it will work with search giant to build a VR phone that will support the new Android Daydream virtual reality technology.

The Chinese government produces 488 million'fake' social media posts a year to distract citizens from news critical of the Communist Party, a new study has revealed. According to the study, written by Harvard University professor Gary King, the goal of the secretive army of commenters is to "distract the public and change the subject" in online discussions which paint the government in a negative light. The study is reportedly the first of its kind to show concrete evidence of the existence of the '50 Cent Party', a name which references the 50 cents each worker is thought to be paid for a post. During the study, co-authored by Stanford University's Jennifer Pan and UC San Diego's Margaret E. Roberts, machine learning techniques were used to analyse millions of social media posts, based on leaked emails and databases which detail the work of the group. The research revealed co-ordinated commenting efforts, usually timed to coincide with government announcements or patriotic public holidays.

An entire sector of the federal government is held hostage by the last century. The death spiral of the gas tax, and the other broken user-fees, demand we reform federal transportation funding, harness emerging technology, and guide the autonomous vehicle revolution. The powerful disruptive force of car sharing services like Uber and Lyft will rapidly be joined by autonomous vehicle technology. A huge part of our economy and culture--the American way of life designed around the automobile for the last century--will change. Our challenge is to use that change to solve problems rather than create new ones, and maintain and tailor our existing infrastructure for the future.