As a long-time sponsorship partner of the U.S. Open, IBM is out with a new artificial intelligence technology to help coaches train the next generation of tennis players called Coach Advisor. Yahoo Finance's Julia La Roche joins YFi AM from the U.S. Open grounds to share more.

Smart Homes were in the past viewed as a luxury, with their primary purpose being to serve as a show piece for the owners. This reality has changed substantially, both because of the development of newer technologies like Internet of Things (IoT) and Artificial Intelligence (AI), and also because of simultaneously occurring social changes that are occurring in our everyday lives. The confluence of many socio-economic factors in conjunction with the evolving technologies may serve as the break out recipe, for Smart Living to significantly increase their presence and get integrated into our daily lives. IoT stands for'Internet of Things' and refers to the technology that enables devices to communicate over the internet, so that they can either be controlled remotely or can send information about their status to a remote user. These are usually electrical devices that range from simple lighting, fans, ACs, Washing Machines, Refrigerators etc. within homes to more heavy electrical devices that exist in buildings such as Pumps or Fire panels.

Inside a sunny conference room on the Microsoft campus in Redmond, Wash., a small team of employees is describing how technology can save the world. Microsoft's Digital Diplomacy unit consists of two dozen policy experts who work on everything from the ethical use of artificial intelligence to protecting the 2020 presidential election from foreign cyberinterference. Brad Smith, Microsoft's president, sits in the middle of the table, sipping coffee from a mug bearing the name of his hometown, Appleton, Wis. The group updates Smith on a tech-industry initiative co-founded by Microsoft to combat terrorist messaging on the Internet. Smith pushes for more ideas. "We need something that will create a new mold," he says.

As Manchester City's players returned to the home dressing room after January's exhilarating, exhausting 2-1 win over Liverpool, music shuddered from speakers. A house remix of Gregory Porter's Liquid Spirit mixed with gleeful shouts as the celebrations began. But in one corner, three men huddled quietly together. Ederson and John Stones stared at a big screen as Harry Dunn, a member of manager Pep Guardiola's backroom staff, zipped through a timeline of the match action to show a replay of Stones clearing the ball off his own goalline, with just 11mm to spare. By the time they were showered, changed and back in the tinted privacy of their cars, Ederson, Stones or any of their team-mates could open the Hudl app on their phone and watch that moment, along with every other involvement they had in the game.

The impact of Artificial Intelligence (AI) is increasing more day by day in our lives. AI has invaded almost in every field, improvising it with new inventions and solutions benefiting our society to a significant extent. Where, on the one hand people are getting more addicted to the technology, industries, on the other hand, are involving AI-based technologies to promote their ideas. Industries have grown to provide solutions for such troublesome situations. AI is now being used widely in an array of fields, increasing its significance in more than one way.

In one event, an electronics shop close to her university was completely destroyed a few minutes after she left her laptop for repairment. This of one of many events that did not stop Munira from following her vision to improve her skills, empower other women in STEM, and use technologies such as Machine Learning to solve problems in her country and beyond. I want to solve community problems like droughts and also improve many industries in my country using Deep Learning and Computer Vision in the near future. Munira works among 40 other Collaborators in our AI for Good challenge with the UN Refugee Agency to predict forced displacement and climate change in Somalia. Read on your own what extraordinary mindset she has.

In the same month it was announced that computer pioneer, codebreaker and the father of Artificial Intelligence (AI), Alan Turing, will feature on the new design of the Bank of England's £50 note, a report from IDC suggests that spending across Europe will hit $5.2 billion in 2019 up from 2018 by 49 percent and expected to rise to $13.5bn by 2022. The race to build machines capable of matching and beating human vision, language understanding, intelligence, and movement is on. Change management and business transformation is one area of business operations where AI could make an exciting impact. In this article, three experts share their thoughts to help to better understand what AI is, how much of what we know is real, what it can and should do, and, most importantly, how it might affect business transformation programs around the world. BN: We often see the terms AI mixed with automation, deep learning and machine learning, what do they all mean?

The cumulative view provided by the confluence of machine learning and decision making in conjunction with third-party data all hosted in the cloud, has given rise to artificial intelligence (AI) in agriculture. The ability of agricultural equipment to think, predict and even advise farmers presents Africa with an historic opportunity to meet the continent's own food requirements. AI also presents Africa with the capability to integrate its agricultural sector into global agricultural value chains. According to GeoFarm South Africa, farms in the United States are 27% more productive than South African farms compared across the same area, moisture levels and soil types. While, superficially, this is because farms in the United States are more mechanised, a closer examination of what these agricultural machines are doing shows just how fundamentally AI has changed the way humans farm, and how dramatically these changes have increased agricultural yields.

There might be disadvantages to using tried and trusted methods.Credit: Science Photo Library Like most research fields, materials science has embraced'big data', including machine-learning models and techniques. These are being used to predict new materials and properties, and devise routes to existing drugs and chemicals. But machine learning requires training data, such as those on reagents, conditions and starting materials. These are usually gleaned from the literature, and are human-generated. The choice of reagents that researchers use could come, for example, from experience or from previously published work. It might be based on a recommendation passed from supervisor to graduate student, or simply on how easy reagents are to find or buy.

CatBoost is based on gradient boosting. A new machine learning technique developed by Yandex that outperforms many existing boosting algorithms like XGBoost, Light GBM. While deep learning algorithms requires lots of data and computational power, boosting algorithms are still in need for most of the business problems. However boosting algorithms like XGBoost takes hours to train and sometimes you'll get frustrated while tuning hyper-parameters. On the other hand, CatBoost is easy to implement and very powerful.