Why the left is ALWAYS a man's best side: Researchers find females really do see the world differently and have a'left side bias' when analysing faces Study finds women focus on the left sided features of a person's face Women also have a strong left eye bias when viewing faces Findings suggest women and men vary in how they maintain eye contact Study finds women focus on the left sided features of a person's face The team from the university used an eye tracking device on 405 participants for over a five week period. Women's health at risk as researchers fail to consider... Does this look like a lizard on Mars? UFO hunter claims to... Why you should never go to bed angry: Bad memories are... Meet your housemates: Incredible images show the PARASITES... Women's health at risk as researchers fail to consider... Does this look like a lizard on Mars? UFO hunter claims to... Why you should never go to bed angry: Bad memories are... Meet your housemates: Incredible images show the PARASITES... Using an eye tracking device, a team of experts discovered women and men perceive faces differently, as females focus more on left sided features and have a strong left eye bias. The views expressed in the contents above are those of our users and do not necessarily reflect the views of MailOnline.

How artificial intelligence is transforming the legal profession The future of the legal profession began 20 years ago. The technology boom was just beginning with the emergence of email and personal computers. Jay Leib was working for Record Technologies Inc. as director of software sales and training in 1999, and the company was scanning documents into databases for clients. At one point the company printed and scanned legal documents related to a lawsuit with Microsoft. Leib thought that was inefficient, a waste of time and paper. So he and his business partner, Dan Roth, decided to create a program that would help lawyers manage electronic documents for litigation. Their idea led them to purchase an e-discovery application. By 2000, Leib and his partner launched their own creation, Discovery Cracker. "We saw a gap in the marketplace," Leib says. Lawyers need tools to keep up with it." Instead of wading through piles of paper, lawyers now deal with terabytes of data and hundreds of ...

Artificial intelligence has become a frequent topic in the news cycle, with reports of breakthroughs in speech recognition, computer vision, and textual understanding that have made their way into a bevy of products and services that are used every day. In contrast, clinical care has yet to reach the much lower bar of automating health care information transactions in the form of electronic health records. Medical leaders in the 1960s and 1970s were already speculating about the opportunities to bring automated inference methods to patient care,1 but the methods and data had not yet reached the critical mass needed to achieve those goals. The intellectual roots of "deep learning," which power the commodity and consumer implementations of present-day artificial intelligence, were planted even earlier in the 1940s and 1950s with the development of "artificial neural network" algorithms.2,3 These algorithms, as their name suggests, are very loosely based on the way in which the brain's web of neurons adaptively becomes rewired in response to external stimuli to perform learning and pattern recognition.

Driving so-called'conversational commerce' is the next phase in the travel company-customer relationship but it's a complicated affair, as Pamela Whitby has been finding out In what Thomson is hailing as an'industry first', last week the holiday group said it would trial a travel search tool using IBM's Watson Technology, which uses natural language processing (NLP) and artificial intelligence to allow computers to think like a human. In a company press release, Jeremy Osborne, Director of Strategic Innovation, TUI UK&I is quoted saying: "We wanted to test whether a conversational search experience would resonate with our customers as a new, fun and easy way to find their ideal holiday". And the response, it seems, was overwhelmingly positive with 77% of participants in the survey saying they would find a virtual assistant useful. The idea is that Thomson customers will be able to interact via a simple chat interface to get responses in real-time to their holiday queries.For the uninitiated, this may sound like Thomson is launching a chat bot. But the group's conversational tool, which is still in beta, is still one step away from this. IBM's Watson Technology, which Thomson is using, is not a chat bot solution in itself, but rather a tool to use for NLP and eventually artificial intelligence that will help make bots smarter.

Technology is really a marvel. So often, as new advances come out that allow us to do things that were thought impossible in the past, we hear the phrase "The future is now." Popular Science and XPRIZE are teaming up to explore and explain technologies like these in a video series called Future First. Episode eleven of Future First is titled "Beyond Self-Driving Cars." In it, we take a look at how the advent of self-driving technology will save lives and lead to new modes of transportation.

This summer, Riva-Melissa Tez was searching online for research that might help her father. He'd gone into a coma after suffering a stroke, and she wondered what the latest recommendations said--whether playing music to him in his native language could keep him connected to this world, or if giving him Prozac could boost his chances of recovery as it had done for mice in a study last year. Doctors are so busy saving lives, she thought, that they couldn't possibly keep up with all the papers published every day. Her concern is shared by doctors, who wonder what they could be missing in the 2.5 million scientific papers published every year. Popular sites like MedCalc and UptoDate are useful tools for doctors to consult diagnostic criteria and double check on treatment guidelines.

This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies such as Hadoop, Scalding and Spark. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Fulfilling the need for both introductory material for undergraduate students of computer science and detailed discussions for software engineering professionals, this book will aid a broad audience to understand the esoteric aspects of practical high performance computing through its use of solved problems, research case studies and working source code. Srinivasa is Professor and Head of the Department of Computer Science and Engineering at M.S. Ramaiah Institute of Technology (MSRIT), Bangalore, India. His other publications include the Springer title Soft Computing for Data Mining Applications.

Want to watch this again later? Report Need to report the video? Report Need to report the video? Need to report the video? This feature is not available right now.

The goal of genome-wide association studies (GWAS) (e.g. the WTCCC study1) is to examine the relationship between genetic markers such as single-nucleotide polymorphisms (SNPs) and individual traits, which are usually complex diseases or behavioral characteristics. Generally, a large number of statistical tests are performed in parallel, each SNP being individually tested for association2,3,4. The standard approach consists of computing individual, SNP-specific p-values corresponding to a statistical association test and comparing these p-values against some given significance threshold (say t*), meaning that precisely those SNPs with p-values smaller than t*are declared to be associated with the trait4,5,6. We refer to this approach as raw p-value thresholding (RPVT) and review some standard methods for choosing t*for the purpose of controlling multiple type I error rates (in particular, the family-wise error rate (FWER) and the expected number of false rejections (ENFR)) in the Methods Section. According to the GWAS catalog7,8 (last accessed 03-07-2015), the more than 1,400 GWAS published so far have led to the identification of more than 11,000 SNPs associated with about 800 human diseases and anthropometric traits with p-values using t* 1 10 5.

If you're new to data science and machine learning, or looking for a simple intro to the Kaggle competitions platform, this is the best place to start. Continue reading below the competition description to discover a number of tutorials, benchmark models, and more. The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.