Google announced the Allo instant messaging app, at this year's Google I/O conference alongside the Duo video chat app. Duo calls are fully encrypted, and Allo also features encryption, however, the company has now confirmed changes to how it stores non-incognito messages. With the launch of the Allo on Wednesday, Google says it will be permanently storing all non-incognito messages. Earlier in May, Google had stated that Allo will keep only temporary message logs. But it turns out that the company requires chats to be logged to provide more data to its machine learning algorithms, with the aim to improve the functionality of its Assistant and Smart reply features.

Words, like people, can achieve a lot more when they work together than when they stand on their own. Words working together make sentences, and sentences can express meanings that are unboundedly rich. How the human brain represents the meanings of sentences has been an unsolved problem in neuroscience, but my colleagues and I recently published work in the journal Cerebral Cortex that casts some light on the question. Here, my aim is to give a bigger-picture overview of what that work was about, and what it told us that we did not know before. To measure people's brain activation, we used fMRI (functional Magnetic Resonance Imaging).

September 21, 2016 -- NEW YORK – LexisNexis Legal & Professional today announced its intent to acquire privately held Intelligize, Inc., provider of the industry standard for U.S. Securities and Exchange Commission (SEC) intelligence. The acquisition would expand the LexisNexis securities and M&A offering with new content, innovative tools and analytics while complementing the capabilities of the company's existing securities solution, Lexis Securities Mosaic . Closing of the transaction is subject to certain customary conditions. Based in Reston, VA, Intelligize provides a leading analytics solution enabling legal, academic and business professionals to efficiently mine data and insights from SEC filings, M&A contracts, transactional agreements and corporate governance documents. This enables customers to streamline compliance processes, benchmark peer disclosures, clearly identify market standards, draft documents based on SEC filed precedent and clear SEC reviews in an efficient manner.

Four years ago an article was written for the Harvard Business Review by both Tom Davenport and DJ Patil entitled "Data Scientist: The Sexiest Job of the 21st century." The article predicted that the demand for skilled people in this area was only set to rise and as a recruitment/staffing specialist within this space, I can only confirm that this has come to pass. With this evolution, I now see the waters have become even harder to navigate, with companies now looking to hire people proficient in an even greater number of disciplines. That is why I wanted to do this post. As with any shortage, you need to get creative but from my perspective, I am often a little surprised at how little flexibility there is when looking to employ people for specialist niche roles.

People use their phones for messaging more than almost anything else. That's why companies like Apple, Facebook, and Snapchat are dumping truckloads into making it easier and more fun to send messages. In May at I/O, Google announced Allo, its latest foray into the brave new world of messaging. Now, the app is finally available on Android and iOS. Allo looks like most of the messaging apps you've probably already used before.

Oracle and Salesforce are both promising artificial intelligence assisted apps with capabilities including machine learning and natural language interaction. Here's what's behind the tech and when it gets real. Oracle and Salesforce both announced "AI" initiatives this week, but there are differences in the scope and scale of what's promised, the pace of their rollouts and even how they're talking about artificial intelligence. For starters, neither vendor is talking about to sort of sentient, general-purpose AI seen in science fiction depictions ranging from "Iron Man" and "Star Trek" to "The Terminator" and "2001 a Space Odyssey." Rather, both vendors are talking about assisting humans with "smart" apps that apply closed-loop machine learning and data science to combinations of customer data and third-party data.

If you believe everything you read, you are probably quite worried about the prospect of a superintelligent, killer AI. The Guardian, a British newspaper, warned recently that "we're like children playing with a bomb," and a recent Newsweek headline reads, "Artificial Intelligence Is Coming, and It Could Wipe Us Out." Numerous such headlines, fueled by comments from the likes of Elon Musk and Stephen Hawking, are strongly influenced by the work of one man: professor Nick Bostrom, author of the philosophical treatise Superintelligence: Paths, Dangers, and Strategies. Bostrom is an Oxford philosopher, but quantitative assessment of risks is the province of actuarial science. He may be dubbed the world's first prominent "actuarial philosopher," though the term seems an oxymoron given that philosophy is an arena for conceptual arguments, and risk assessment is a data-driven statistical exercise. So what do the data say? Bostrom aggregates the results of four different surveys of groups such as participants in a conference called "Philosophy and Theory of AI," held in 2011 in Thessaloniki, Greece, and members of the Greek Association for Artificial Intelligence (he does not provide response rates or the phrasing of questions, and he does not account for the reliance on data collected in Greece).

Machine learning and artificial intelligence already are and will continue to be beneficial in health care. However, serious pitfalls dot the health care landscape -- while failed experiments like Twitter chatbots may be amusing, mistakes in a medical context can have serious consequences. This talk will demystify the basic concepts of machine learning and several of the freely available tools that are making this technology more and more accessible, as well as explore the pros and cons of machine learning's expansion across the health care industry.

It was a heady mix of business and technical sessions on how to take advantage of the power of analytics. Of course there are innumerable applications for analytics, from fraud detection to supply chain optimization to garden variety business intelligence. For this post I'll focus mainly on customer-related applications, and some of the more advanced SAS capabilities discussed at the conference. Let's start with what SAS announced: SAS Viya -- billed as a new open, "cloud-ready" analytics platform. The idea is to bring together the SAS portfolio, built over some 40 years, into one platform that can be used by data scientists and other analytics professionals; business users and IT management; and senior management.

Someone sent me this article by psychology professor Susan Fiske, scheduled to appear in the APS Observer, a magazine of the Association for Psychological Science. The article made me a little bit sad, and I was inclined to just keep my response short and sweet, but then it seemed worth the trouble to give some context. I'll first share the article with you, then give my take on what I see as the larger issues. The title and headings of this post allude to the fact that the replication crisis has redrawn the topography of science, especially in social psychology, and I can see that to people such as Fiske who'd adapted to the earlier lay of the land, these changes can feel catastrophic. I will not be giving any sort of point-by-point refutation of Fiske's piece, because it's pretty much all about internal goings-on within the field of psychology (careers, tenure, smear tactics, people trying to protect their labs, public-speaking sponsors, career-stage vulnerability), and I don't know anything about this, as I'm an outsider to psychology and I've seen very little of this sort of thing in statistics or political science. As I don't know enough about the academic politics of psychology to comment on most of what Fiske writes about, so what I'll mostly be talking about is how her attitudes, distasteful as I find them both in substance and in expression, can be understood in light of the recent history of psychology and its replication crisis. In short, Fiske doesn't like when people use social media to publish negative comments on published research. She's implicitly following what I've sometimes called the research incumbency rule: that, once an article is published in some approved venue, it should be taken as truth.