As artificial intelligence (AI) makes deeper inroads to improve our daily life, a group of Land Rover engineers have helped the British Land Rover BAR team by building a faster boat so that they could win the sailing competition America's Cup. Using AI, the engineers worked for more than a year to find patterns in the boat's performance data which could be used to make it go faster, the company said in a statement on Thursday. Land Rover BAR is second in America's Cup World Series rankings, following a podium finish in Chicago in the US recently. The next leg is in the island city of Portsmouth from July 21-24 when the team will try to close the 10-point gap to series leader Emirates Team New Zealand. "Land Rover's AI could prove the difference in its bid to win the America's Cup for the first time for Britain," said Sir Ben Ainslie, Land Rover BAR Team's principal and skipper.

Though Google is pushing hard on cloud, competition is fierce, with AWS and Microsoft showing strong growth in the space this year. But the company has renewed its cloud business efforts this year, led by Diane Greene, Google's head of cloud computing. Greene has argued that Google's cloud platform is ready to compete with cloud industry leaders. Amazon, Microsoft and IBM all also offer machine-learning programs with their cloud services, but Google is publicizing how companies can rent its computer servers for AI initiatives to help it stand out among the competition. The new tools Google introduced, for example, makes it so "digital marketers can analyze online product reviews or service centers can determine sentiment from transcribed customer calls," according to a company blog.

Machine learning has made a significant practical impact in a vast array of disciplines, ranging from healthcare to defense to finance. This presentation will be focused on healthcare and will describe how machine learning techniques may be applied to improve patient outcomes in three different clinical applications, including: the reduction of false cardiac arrhythmia alarms in the intensive care unit (ICU), the prediction of acute hypotensive episodes in the ICU, and the automated classification of heart sounds using phonocardiography. Each of these research topics presents its own unique challenges that influence the selection of optimal machine learning algorithms. Machine learning techniques have been shown to enhance patient outcomes in not only these three applications, but also in a wide variety of additional clinical scenarios. The results underscore the value of data in making more informed patient care decisions and also help to demonstrate the wide applicability of machine learning algorithms.

Disease risk estimates can be used as prognostic information and support for treating CVDs. The commonly used Framingham risk score (FRS) for CVD prediction is outdated for the modern population, so FRS may not be accurate enough. In this paper, a novel CVD prediction system based on machine learning is proposed. Methods: This study has been conducted with the data of 689 patients showing symptoms of CVD. Furthermore, the dataset of 5,209 CVD patients of the famous Framingham study has been used for validation purposes.

As a Stanford student, Zeshan Hussain found many ways to take part in public service projects near and far – on campus, at a high school on the other side of San Francisco Bay and at a tropical disease hospital in India. In January 2016, along with other members of the Muslim Student Union (MSU) and other student groups, Hussain helped organize Syrian Refugee Awareness Week, which included a teach-in about the crisis, a benefit dinner to raise funds for the charity United Muslim Relief and a clothing collection drive in student residence halls. The organization brought in Sana Khatib, a Syrian-American activist whose father is a former political prisoner and whose family fled Syria and the Assad regime when she was young. Through a clothing drive the MSU also collected 500 pounds of clothing just on campus from students and faculty, an accomplishment Hussain described as "very heartening." "We wanted to raise awareness about the crisis and its history, and about the personal struggles of students who may be refugees, or students who have families that are refugees," he said.

Just weeks ago, Google announced that it would be releasing improvements to its Dynamic Search Ads, making its targeting even more precise and relevant than before. The advertiser provides the website that they want to drive traffic to, and Google then analyzes the pages and creates an ad campaign based on the perceived content on those pages. In thinking about the ways in which the use of negative keywords will impact RankBrain's machine learning, the potential feedback from millions of advertisers with millions of pages of content should vastly improve the AI's ability to provide more precise ad targeting. Changes to Google's search results pages ... read more What metric is the best way to approximate the future success of your conversion rate optimization (CRO) efforts.

Developed by a pair of former Google project leads, Candid (the company) has developed a natural language processing system that analyzes every piece of posted content and flags inflammatory items for removal -- things like hate speech, threats and slander. Off-topic posts are moved to more appropriate sections, so you won't have to dig through political discussions to read about NASA's mission to Mars. Candid (the app) is available free on both iOS and Android. Similar to Yik Yak's location-based function, each Candid user will see a personalized feed of posts and content based on their "education, employment, interests and neighborhood," according to the company's press release. Interestingly, you can even sign up using your Facebook account to seed the app's Group suggestions.

For those suffering depression, PTSD, or other mental health challenges, a breakdown can be a slow burn, developing over days or weeks in between doctor visits. Delay in treatment can have lasting consequences. "Very likely, every single episode of depression or mania is going to damage your brain a little more," says Thilo Deckersbach, a Harvard psychology professor who practices at Massachusetts General Hospital. The hospital's online MoodNetwork recruits patients with major depression and bipolar disorder for clinical studies, including a new one with the Boston-based artificial intelligence company Cogito. They are testing the ability of a mobile app called "Companion" to flag early signs of trouble by monitoring activities like patients' movement, calling and texting behavior, and the way they speak.

"Mellanox's smart Switch-IB 2 switches enable the University of Tokyo to leverage new in-network computing capabilities, allowing data algorithms to be managed and executed by the network devices," said Gilad Shainer, vice president, marketing at Mellanox Technologies. "EDR 100G InfiniBand offers world-leading performance, scalability and efficiency enabling the University of Tokyo to be at the forefront of research, and scientific discovery." "We are pleased to have installed Mellanox's InfiniBand high-performance solutions to drive our new integrated supercomputer system," said Professor Hiroshi Nakamura, Director of the Information Technology Center, The University of Tokyo. "Our new system is key to advancing ongoing research and expanding the exciting work being carried out that is leveraging computational science and engineering, computer science, data analysis, and machine learning." Mellanox InfiniBand adapters provide the highest performing interconnect solution for High-Performance Computing, Enterprise Data Centers, Web 2.0, Cloud Computing, and embedded environments.

Researchers from the Michigan State University are using GPU-powered artificial intelligence and fingerprints to help keep kids healthy. Many children living in developing countries lack any form of identification, making it hard to know what babies have received which vaccine or booster shot. "We want to make sure there's complete coverage, that every child is given the right vaccinations," research lead Prof. Anil Jain says. "With fingerprint-based health records, we can track this." Apart from keeping track of vaccination shots, fingerprint scans can also help authorities identify missing children or resolve cases in which newborns are swapped at birth.