Google announced today that it is expanding its largest non-U.S. The new Machine Learning Research Group will be based in Zurich, Switzerland, which is already Google's largest research center outside the U.S. The company did not say specifically how many positions will be added. But in a blog post, Google executives said machine learning has become critical to the company's development efforts across a wide range of services. "Google's ongoing research in Machine Intelligence is what powers many of the products being used by hundreds of millions of people a day -- from Translate to Photo Search to SmartReply for Inbox," wrote Emmanuel Mogenet, head of Google Research in Europe. Indeed, the Zurich research center has already had a sizable impact on Google.

Irving Wladawsky-Berger is uniquely positioned to answer that question. He spent 37 years with IBM, where he was responsible for identifying emerging technologies and monitoring the marketplace for developments that could affect the future of the IT industry. Since retiring, he acts as a strategic advisor for blue-chip clients, serves as a visiting lecturer at MIT's Sloan School of Management, writes a weekly blog, and contributes regularly to the Wall Street Journal's CIO Journal. Wladawsky-Berger recently sat down with Martin Reeves, a BCG senior partner and the leader of the firm's BCG Henderson Institute. Edited excerpts from that conversation follow.

The new Apple Photos now labels photos based on facial recognition and content such as landscapes and objects so that users can search and sort photos. Apple copied what Google announced last year. This is good news for Apple users. No one wants to deny iPhone users a better experience organizing their photos. But any of them with a lick of sense about scientific research should also be offended. Apple stood on the shoulders of giants to produce Photos.

Have you ever used a voice-activated service such as Apple's Siri only to find it completely missed what you were saying? Or played a game against a computer and felt it didn't even put up a fight? That's about to change with advances in deep learning, which improves computers' ability to process information and make decisions--like people do, and oftentimes even better. Deep-learning techniques allow a computer system to connect the dots from many different areas of knowledge, similar to how the human brain works, to make the best decision possible. Facebook, Google, Microsoft, and other tech companies are in a race to apply deep learning to make machines intelligent without much help from the programmers.

The UK has a wealth of capability in AI techniques and their application, but a future with AI raises many questions. In this 90 minute debate our panel of thought leaders chaired by Will Hutton, author of'How Good We Can Be', will address your questions. They will discuss the safeguards that might be needed to ensure a responsible and ethical approach towards the applications of AI technologies. The debate will be followed by refreshments and networking. This debate launches The Future with AI -- a one year programme jointly run by BIG INNOVATION CENTRE, HACKMASTERS and KTN.

Artificial intelligence, which has been around since the 1950s, has seen ebbs and flows in popularity over the last 60 years. But today, with the recent explosion of big data, high-powered parallel processing, and advanced neural algorithms, we are seeing a renaissance in AI--and companies from Amazon to Facebook to Google are scrambling to take the lead. According to AI expert Roman Yampolskiy, 2016 is the year of "AI on steroids." How the'PayPal Mafia' redefined success in Silicon Valley A decade ago, the PayPal Mafia played a major role in revitalizing the tech industry in Silicon Valley. The story behind this group of leaders proves that their success is more than just luck.

Data imported from other spreadsheets or databases is already separated into fields, using something called a field delimiter--a comma, tab, space, or custom character--to separate one field from another. These databases import easily into Excel and place all the fields in separate columns. If your company pays bills and/or banks online, these sites usually offer copies of the company's records in electronic form. CSV (comma separated values) is the most common data exchange format and, if offered, the best one to use. But what happens when all the data imports into one cell?

Machine learning and algorithms have become so intelligent and complex that they are shaped by forces beyond our control. We use these tools to help us in our everyday lives. They help us make business decisions, they generate accurate search results, they show us articles on Facebook that we actually find interesting, they match us with prospective employers, and even match us with prospective partners. In many ways, they improve our businesses, our health, our education, and our lives. But can these programs and software be discriminatory? Although there is a widespread belief that these computer programs and algorithms are objective, there is no doubt that there is a significant degree of human influence involved.

I'm Julie, Director of Ops, back for a quick tutorial of two awesome new offerings we've built for you. I'm on the non-technical / cat loving side of things so I break it down a bit. I also run the Machine Learning Without a PhD group on LinkedIn where jargon isn't allowed. Feel free to join if you'd like #machinelearning4everyone So today you're getting a 2-for-1 (or as my dad likes to call it a "TooFer"). Today's topic will be the 2016 Tony Awards that aired this past Sunday night. Let's begin by heading to your dashboard.

You can almost hear the whooshing sound as the technology industry is sprinting to the marketplace with new solutions to help the enterprise garner useful and intelligent insights from their data. Analytics, Machine Learning (ML) and Artificial Intelligence (AI) delivered in a simplistic form is what companies are demanding. To meet this mandate, Hewlett Packard Enterprise Co. (HPE) has developed Haven OnDemand, which offers the latest technology in a simplified platform for developers. Jeff Veis, VP of Big Data Platform Solutions, HP Software, at HPE, spoke to John Furrier and Dave Vellante, cohosts of theCUBE, from the SiliconANGLE Media team, during HPE Discover 2016 Las Vegas to discuss Big Data and the needs of the enterprise. Furrier began the interview by asking Veis about the driving force behind the need for machine learning.