Gigi Peccolo is the Content Manager at OneReach, where she is focused on creating content enabling companies to offer effective, meaningful customer support over text message. Gigi is a skilled writer, having served as News Editor at her college newspaper. Gigi received her BA in Journalism Studies and Spanish from the University of Denver, where she graduated with Distinction in Journalism Studies.

This article published last week at Wired is rather alarmingly titled "Why Can't Anyone Make a Decent Freaking To-do App?" It looks at how the majority of the consumer public is not getting value from the litany of task management software options available out there, and contends that many people are returning to paper to help them: Most of the myriad to-do list apps are fine. Some of them are very good. But none of them has ever solved my problem--your problem--of having too much to do, too little time to do it, and a brain incapable of remembering and prioritizing it all. Which explains why the old ways remain so popular. I'm not sure there I agree that there are "no freaking decent to-do apps," but I take the writer's point. It does seem surprising that, at this late date, we still don't have a clear winner in a software category that seeks to fulfill such a basic, universal human need.

Google's DeepMind artificial intelligence team is making history. Its AlphaGo program is up 2-0 on Lee Sedol, one of the top Go players alive. This is the first time a computer has beat a human champion without a handicap. While there will be three more games between Sedol and AlphaGo, the victory suggests that Go is the latest game that computers are outwitting people in. Checkers fell in 1994, Chess in 1997, and Jeopardy in 2011. "It there's a social component with players playing together, it's not clear," Littman says.

Until recently, Robyn Ewing was a writer in Hollywood, developing TV scripts and pitching pilots to film studios. Now she's applying her creative talents towards building the personality of a different type of character – a virtual assistant, animated by artifical intelligence (AI), that interacts with sick patients. Ewing works with engineers on the software program, called Sophie, which can be downloaded to a smartphone. The virtual nurse gently reminds users to check their medication, asks them how they are feeling or if they are in pain, and sends data to a real doctor. As tech behemoths and a wave of start-ups double down on virtual assistants that can chat with human beings, writing for AI is becoming a hot job in Silicon Valley.

The team of three so-called "suit wranglers" told me to relax as they strapped me into the contraption, but the heart rate monitor attached to my finger gave away the fact that I was a little uncertain as to what I had gotten myself into last week. "Do you normally have a high heart rate?" one technician inquired. During a visit to the Liberty Science Center in Jersey City last Thursday, I had happened across a preview of a new exhibit that was opening to the public the next day, Friday, April 1. The exhibit, The Genworth R70i Aging Experience, featured the just-unveiled Genworth R70i Age Suit – an augmented reality suit that simulates the sensory impairments that come as people age. The high-tech suit I was being strapped into was created by Applied Minds co-founder and inventor Bran Ferren, who partnered with Genworth Financial to create it with the goal of sparking a conversation among young people about aging and senior care.

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Another quite standard technique is called'Cluster Validity Index', Here are the two famous papers, Part1 [3] and Part2 [4]. Basically these methods perform internal evaluation of the quality of clusters, after the clustering is performed. For e.g. one common method called Dunn's method

It currently is an implementation of constrained local models fitted by regularized landmark mean-shift, as described in Jason M. Saragih's paper. The library provides some generic face models that were trained on the MUCT database and some additional self-annotated images. Check out clmtools for building your own models. For tracking in video, it is recommended to use a browser with WebGL support, though the library should work on any modern browser. For some more information about Constrained Local Models, take a look at Xiaoguang Yan's excellent tutorial, which was of great help in implementing this library.

List comprehension is powerful and must know concept in Python. Yet, this remains one of the most challenging topic for beginners. With this post, I intend help each one of you who is facing this trouble in python. Do you know List Comprehensions are 35% faster than FOR loop and 45% faster than map function? I discovered these and many other interesting facts in this post. If you are reading this, I'm sure either you want to learn it from scratch or become better at this concept. Both ways, this post will help you.

This year won't be the year of artificial intelligence (AI). But it's coming and artificial intelligence will be transformational. That summarizes the sentiments of Barry Diller, the chairman and senior executive of both Expedia and IAC/InterActiveCorp, who says that machine learning and artificial intelligence will combine to manage companies' big data troves and there will be layers of innovation "tacked onto distribution systems." He argued that there won't be a single next big thing but there will be several tracks, including mobile, machine learning, artificial intelligence and big data. Examples of artificial intelligence applications to personalize services, such as "Connie" the robot concierge that's being piloted at some Hilton properties, are appearing at a modest pace, and Diller thinks it will take a generation or two before the impact is truly felt with "unimaginable consequences," potentially both positive and negative.