Earlier than Oct-11-2017

Pharmacist reportedly drugged woman on date, charged by police

FOX News

Robert Woods, a pharmacist in Tampa Florida, was charged with sexual battery after he allegedly drugged a woman he met on Tinder. A Florida man who works as a hospital pharmacist was arrested Saturday and charged with sexual battery after he reportedly drugged his Tinder date. According to a police affidavit, Robert Woods, 27, met the woman on the dating app Tinder and the pair agreed to meet at a bar in downtown Tampa, Fox 35 reported. The woman reportedly had one beer at the restaurant before Woods suggested they leave and go to his apartment, where he claimed his friends were having a party. When they arrived, there was reportedly no party.

The Artificial Intelligence Gap Is Getting Narrower


One of the most widely known practitioners of artificial intelligence never used a computer or built what we'd think of as a robot. Mary Shelley's Dr. Victor Frankenstein, the creator of a "modern Prometheus" capable of thinking and acting on his own, captivated readers from the moment the novel Frankenstein first appeared on shelves. But that success belies the fact that Shelley was still ahead of her time. What once seemed like a bizarre fantasy--the notion that man could create a being who could think as we do--is, today, a fascination. It helps that we've grown closer, in our world, to making Dr. Frankenstein's Promethean dream a reality.

These archival images show the women scientists and coders who made history


A link has been posted to your Facebook feed. Antonia Novello was the first woman and first Hispanic to serve as U.S. surgeon general. Women-led breakthroughs in science, technology, engineering and mathematics have often been lost or overlooked. Getty Images has released a set of historical images, in honor of Ada Lovelace Day, to remind viewers that these women existed -- and should be a source of inspiration. Lovelace, born in 1815 London, is credited as the first computer programmer after she translated complicated algorithms into simple English, years before the first computer.

Behold, Donald Trump's completed IQ test (your move Tillerson)


The president challenged the secretary of state to an IQ test today. President Trump, hot under the collar about recent news that Secretary of State Rex Tillerson called him a moron in front of several cabinet members, has decided to settle the score with an old fashioned IQ-test-off. In an interview with Forbes Tuesday, Trump called the reports of Tillerson's comment "fake news" but added that if the news were true the two would "have to compare IQ tests." We are so thrilled to announce that President Trump has sent us his IQ test, and now we need simply to wait for Secretary Tillerson's results to determine who is the One True Moron of America. The ball is in your court now, Secretary Tillerson!


The Japan Times

Astronaut Mark Vande Hei made fast work of greasing the big robot arm's new hand. Vande Hei and station commander Randy Bresnik replaced the latching mechanism on one end of the 58-foot robot arm last Thursday. "I finish six months on the space station," Vande Hei replied. As the space station approached Italy early in the spacewalk, Mission Control urged Bresnik and Vande Hei to take some photos for their crewmate, Paolo Nespoli.

Why Every Business Should Care About Machine Learning


Recent advancements in machine learning are reaching a level of sophistication that are exceeding the expectations of industry analysts and executives alike. We're familiar with Google DeepMind's AlphaGo that bested the greatest masters of the ancient Chinese game "Go" 10 years earlier than expected. More recently, a new exhibition at the New York Gallery Metro Pictures depicts machine-made images to people using algorithms. Retailers are redefining customer experiences with real-time personalization and convenience. Even most stock trades are governed by automated analysis of market outcomes and determination of future trends faster and more accurately than humans alone.

Why Personal Finance needs Artificial Intelligence


In the financial industry, adapt or become a dinosaur is truer than ever. The industry is changing rapidly and external catalysts are overwhelming its business models. Mobile payments, robo advisors and blockchain have led financial services firms to redefine their views of the future. The acceptance of these ideas is more about'when'- not'how' or'if. As we consider the future of financial services, one area that isn't discussed as much is the future of personal finance and planning.

Machine Learning for Investors: A Primer -


If you are out to describe the truth, leave elegance to the tailor. Machine learning is everywhere now, from self-driving cars to Siri and Google Translate, to news recommendation systems and, of course, trading. In the investing world, machine learning is at an inflection point. What was bleeding edge is rapidly going mainstream. It's being incorporated into mainstream tools, news recommendation engines, sentiment analysis, stock screeners. And the software frameworks are increasingly commoditized, so you don't need to be a machine learning specialist to make your own models and predictions. If you're an old-school quant investor, you may have been trained in traditional statistics paradigms and want to see if machine learning can improve your models and predictions. If so, then this primer is for you! Even if you're not planning to build your own models, AI tools are proliferating, and investors who use them will want to know the concepts behind them. And machine learning is transforming society with huge investing implications, so investors should know basically how it works. In school, when we studied modeling and forecasting, we were probably studying statistical methods. Those methods were created by geniuses like Pascal, Gauss, and Bernoulli.

Data Scientist job in Pleasanton, CA - October 2017


Will perform complex modeling and algorithm development on large data sets to resolve disparate data into single real-world entities (persons, companies, products, etc.) and develop relationship structures among these entities. Typical solutions will use probabilistic matching, machine learning and graph theory on very large scale structured and unstructured data sets. Some of these entity resolution techniques will also be used for fraud detection. NLP experience helpful, but not required this time. This role is more focused on entity resolution techniques used for fraud detection- does involve Machine Learning but not extensive into NLP.

The Secrets of Google's Moonshot Factory

The Atlantic

The journalist turns to the assembled crowd and asks: Should we build houses on the ocean? Listen to the audio version of this article:Feature stories, read aloud: download the Audm app for your iPhone. The setting is X, the so-called moonshot factory at Alphabet, the parent company of Google. And the scene is not the beginning of some elaborate joke. The people in this room have a particular talent: They dream up far-out answers to crucial problems.