The kidnapping of Tennessee teen Elizabeth Thomas allegedly by his ex-teacher Tad Cummins will be the point of discussion at Friday's 20/20 show. The show will focus on Cummins' months on the run and what will happen next to the 50-year-old, who was arrested mid-April. The 15-year-old former student of Cummins went missing in March and was found in a remote part of northern California, more than a month after her disappearance. Elizabeth was reunited with her family, while Cummins was arrested. He has been charged with kidnapping and transporting a minor across state lines with the intention to engage in sexual activity.

XPRIZE, a 501(c)(3) nonprofit, is the global leader in designing and implementing innovative competition models to solve the world's grandest challenges. XPRIZE utilizes a unique combination of gamification, crowd-sourcing, incentive prize theory, and exponential technologies as a formula to create exponential impact in the grand challenge domains facing our world.

Amazon said on Thursday it would open a 60,000 square foot development center later this year in the U.K. focused on artificial intelligence (A.I.) and drone delivery research. The site in Cambridge, which is just north of the capital London, will have a capacity for 400 people but the U.S. e-commerce giant did not say how many people it was hiring. Amazon's announcement comes after it pledged in February to hire 5,000 full-time staff in the U.K. this year, which would bring its headcount in the country to 24,000 from the previous 19,000 figure. The company announced separately on Thursday that it has invested £6.4 billion ($8.26 billion) across the U.K. since 2010. "By the end of this year, we will have more than 1,500 innovation related roles here in Britain, working on everything from machine learning and drone technology to streaming video technology and Amazon Web Services," Doug Gurr, U.K. country manager for Amazon, said in a press release on Thursday.

Google's offering voice assistants to your next DIY computing project, we review the new BlackBerry phone (yes, it is 2017), and test-ride an electric dirt bike. Raspberry Pi has teamed up with Google to bring voice integration to the Pi with a clever combination of hardware and software. Packed with the same tech that powers Google Home, the companies have released a kit that transforms a regular Raspberry Pi 3 into your very own virtual assistant. The collaboration marks the first time that Google has produced something for hobbyists. The initiative is called "Artificial Intelligence Yourself" (AIY), and Google's project director said that he wants to create more hobbyist uses for Google software.

After reading the press releases for this batch of 24 research reports, although they vary widely in their forecasts, they almost all agree that most segments of the robotics industry are expected to grow at a double-digit pace at least through 2022. Drone Identification System Market April 2017, Markets and Markets, $5,650 The drone identification market is estimated to grow from $801.8 Million in 2016 to $16 billion by 2022, at a CAGR 64.64% during the forecast period. Automated Guided Vehicle Market April 2017, Markets and Markets, $5,650 The automated guided vehicle market is expected to reach $2.68 billion by 2022, at a CAGR of 9.34% between 2017 and 2022. The growth of this market is propelled by advancements in automation, emphasis on workplace safety, and the growing need to cut down operational cost and increase productivity. Global smart robots market January 2017, 84 pages, TechNavio, $2,500 Forecasts the global smart robots market to grow at a CAGR of 20.65% during the period 2016-2020.

It's been a long time since I did a coding demonstrations so I thought I'd put one up to provide you a logistic regression example in Python! Admittedly, this is a cliff notes version, but I hope you'll get enough from what I have put up here to at least feel comfortable with the mechanics of doing logistic regression in Python (more specifically; using scikit-learn, pandas, etc…). This logistic regression example in Python will be to predict passenger survival using the titanic dataset from Kaggle. Before launching into the code though, let me give you a tiny bit of theory behind logistic regression. The logistic regression formula is derived from the standard linear equation for a straight line.

Researchers are using AI and other deep learning methods to create an algorithm that's capable of detecting DR with an accuracy rate of 94 percent When we talk about artificial intelligence here at RTInsights, we typically cover topics like recommendation engines, such as selling houses on Trulia, or implementing some kind of predictive analysis to make CRM or marketing more effective. But artificial intelligence can be used for actually improving the lives of ordinary people--according to a new study conducted by researchers from the Byers Eye Institute at Stanford University, AI could soon be used to fight vision loss due to a complication that stems from diabetes. Diabetic retinopathy (DR) affects the blood vessels at the back of the eye while a patient has diabetes, and it's known to cause preventable blindness. The researchers are using AI and other deep learning methods to create an algorithm that's capable of detecting DR with an accuracy rate of 94 percent. That number applies to all the disease stages--mild to severe--so it's not only beneficial to those who are dealing with severe vision issues due to DR.

The Drum has launched a survey of its readers to explore how brands are investing in artificial intelligence (AI). The research survey, in partnership with Sysomos, will explore how AI is set to make a huge impact in the marketing industry and will form the basis of The Drum Market Insight Report - Artificial Intelligence Edition. Brand investment in AI is starting to pick up. Forrester has predicted there will be a 300% increase in investment in AI in 2017. According to a study by researchers at Oxford University and Deloitte, the likelihood of a robot taking a marketer's job is 33%.

My name is Michelle and I will be your conference moderator for today. At this time, all participants are in a listen-only mode. We will conduct a question-and-answer session towards the end of this conference. We will expect the call to conclude in an hour. As a reminder, this call is being recorded for replay purposes. I would now like to turn the call over to Roger Sachs, Head of Investor Relations at Genpact. Good afternoon, everyone, and welcome to Genpact's first quarter earnings call to discuss our results for quarter ended March 31, 2017. We hope you have had a chance to review our earnings release which was posted to the IR section of our website, genpact.com. With me in New York today are Tiger Tyagarajan, our President and Chief Executive Officer; and Ed Fitzpatrick, our Chief Financial Officer. Our agenda today will be as follows: Tiger will provide a high level overview of our results, as well as update you on some of our strategic initiatives. Ed will then discuss our financial performance for the quarter in greater detail. Tiger will then come back for some closing comments and then we will take your questions. And as Michelle just said, we expect the call to last about an hour. Please note, the year-over-year growth rates discussed today include the impact of the reclassifications of the divested GE Capital businesses to Global Client revenue as if these transactions occurred on January 1, 2016. This was done to provide a consistent view of the underlying growth trends of our business. The actual results without these adjustments are included in our earnings release. Some of the matters we will discuss in today's call are forward-looking. These forward-looking statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially from those in such forward-looking statements. Such risks and uncertainties are set forth in our press release. In addition, during our call today we will refer to certain non-GAAP financial measures which we believe provide additional information to investors and better reflect the way management views the operating performance of the business. You can find a reconciliation of these measures to GAAP in our earnings release in the IR section of our website.

Machine learning features in X-Pack let you automate the task of detecting anomalies in time series data. In the first video in this tutorial series, we show you how to detect anomalies in single univariate time series via a single metric job type. Download the example from GitHub to try this out on your machine.