We analyze the associations between top Data Science tools, Commercial vs Free/Open Source, rank tools on R vs Python bias, find tools more associated with Big Data, those more associated with Deep Learning, and uncover strong regional differences.

Ronny Kohavi is a Microsoft Distinguished Engineer and the General Manager for Microsoft's Analysis and Experimentation team at Microsoft's Applications and Services Group. He was previously Partner Architect at Bing, part of the Online Services Division at Microsoft. He joined Microsoft in 2005 and founded the Experimentation Platform team in 2006. His papers have over 27,000 citations and three of his papers are in the top 1,000 most-cited papers in Computer Science. In short, Ronny is the big kahuna of experimentation and I am very happy he took time to have this discussion with me.

There's been a lot written the past couple days about Microsoft acquiring LinkedIn, the business focused social network. The business rationale is focused on Microsoft combining its Office products together with the information available on LinkedIn to create new services for its users. For example, as you head into a meeting that's on your Outlook calendar, Microsoft's Cortana (its digital assistant) can provide you background on each of the attendees that it has gleaned from their LinkedIn profiles. Another example used is the potential opportunity to embed Office tools into the LinkedIn platform to make collaboration on Word documents, spreadsheets, Powerpoint presentations, and so on, easier. On another front, Facebook has recently announced partnerships with POS solution providers to gain access to transaction data which it is combining with location services to understand what stores a shopper goes to and creating a link between Facebook advertising and products purchased.

Hawking, Berners-Lee and Zuckerberg have all given their warnings. The fear is of a future where artificial intelligence (AI) drives the decisions in major corporations, and machines become so competent and clever that they take up our jobs. Already we're seeing how AI is impacting several businesses including IBM, Google, Amazon and Apple - through image recognition, speech understanding and the mining of large data sets. The sophistication of AI is even being leveraged to make decisions on what messages to show consumers, and creating bespoke messaging depending on what it thinks will be interesting, relevant and useful. Clearly the next frontier of brand and consumer interaction is upon us.

Every job has its more boring components. In libraries, one of those jobs is scanning the shelves, looking for missing and misplaced books, and taking stock of what's available. For human workers, this is time-consuming, repetitive and boring, all of which can contribute to wandering attention. The autonomous robotic shelf-scanning platform, or AuRoSS, is in development by the Institute for Infocomm Research of Singapore's Agency for Science, Technology and Research. It uses laser mapping to navigate a library, and RFID tags placed on books to scan the collection.

My own research into ways dangerous AI systems might emerge suggests that the science fiction trope of AIs and robots becoming self-aware and rebelling against humanity is perhaps the least likely type of this problem. Much more likely causes are deliberate actions of not-so-ethical people (on purpose), side effects of poor design (engineering mistakes) and, finally, miscellaneous cases related to the impact of the surroundings of the system (environment). Because purposeful design of dangerous AI is just as likely to include all other types of safety problems and will probably have the direst consequences, that is the most dangerous type of AI, and the one most difficult to defend against.

Welcome to Mossberg, a weekly commentary and reviews column on The Verge and Recode by veteran tech journalist Walt Mossberg, now an Executive Editor at The Verge and Editor at Large of Recode. As usual, there were scores of feature changes and announcements to Apple's four software platforms -- iOS, watchOS, tvOS, and the newly renamed macOS -- at this year's Worldwide Developer's Conference. Just listing them all here would tax the patience of all but the most Apple-obsessed readers. But there were two big themes, and a few significant moves consistent with them, that I believe stood out in the cascade of slides and demos the company showed at WWDC. They show how stubbornly Apple clings to both its principles and its profit centers.

Do you remember JARVIS, the computerized personal assistant who helps Tony Stark manage his complex super hero affairs in the Iron Man movies? With the rise of conversational Artificial Intelligence (AI) like Google Home or Amazon Echo, or the smartphone-based Viv, Siri, Cortana, etc., similar JARVIS-like services may be available in the not-so-distant future. Yet to date, the impact of conversational technology – and popular discussion about its use – often remain limited to modern conveniences like ordering household supplies or receiving restaurant recommendations, reminders and hands-free directions. While it's helpful for everyday tasks, the technology that underlies these services can be put to more ambitious uses. Indeed, it can amplify existing impacts and overcome significant technical barriers to unlocking commercial, educational and connectivity services for the next four billion emerging mobile users in developing markets – people who will soon access the internet for the first time.

This fear is as old as Luddites. Arguably, repetitive jobs are the most exposed, but inevitably, "knowledge workers" will also not be spared. Difficult as it may be to put a number to it, but in all likelihood the number of jobs lost will be in be tens of thousands, remarked George. To cite an example – Wealth Advisors in US. These jobs are increasingly getting automated and machines are able to do what humans can.

Qloo Inc. closed a 4.5 million Series A round of venture funding to support the growth of its cultural recommendation engine. Investors included: Academy Award-winning actor Leonardo DiCaprio; Starwood Hotels founder Barry Sternlicht; Pierre Lagrange of GLG Partners; and Adriaan Ligtenberg's AllMobile Fund, along with other individual angel investors. According to the startup's co-founder and CEO Alex Elias, New York City-based Qloo combs through proprietary and open source data online to learn about consumers' preferences, and how their tastes correlate across eight major categories: music, film, television, dining, nightlife, fashion, books and travel. The cultural correlations can sometimes surprise marketers. Tomorrow, the Cleveland Cavaliers will face off against the Golden State Warriors in game 6 of the NBA Finals in Ohio.