Huawei just unveiled a new smartphone called the Honor V10, and it also announced that it is working on its own version of Apple's Face ID technology. Huawei claims that its new facial recognition technology is better than Apple's and it can also be used for animated emojis. Huawei's new facial recognition technology is made possible with the depth-sensing camera system. The Chinese phone maker says that it uses a combination of infrared and a projector to create a 3D map of a user's face. Although the process is similar to Apple's Face ID technology on the iPhone X, Huawei's camera system can capture 300,000 points of the user's face in 10 seconds.

Huawei has a history of trying to beat Apple at its own game (it unveiled a "Force Touch" phone days before the iPhone 6s launch), and that's truer than ever now that the iPhone X is in town. At the end of a presentation for the Honor V10, the company teased a depth-sensing camera system that's clearly meant to take on Apple's TrueDepth face detection technology. It too uses a combination of infrared and a projector to create a 3D map of your face, but it can capture 300,000 points in 10 seconds -- that's 10 times as many as the iPhone X captures. It's secure enough to be used for payments (unlike the OnePlus 5T), and almost as quick to sign you in as the company's fingerprint readers at 400 milliseconds. Even the silly applications of the tech promise to be better.

Customer churn is a problem that all companies need to monitor, especially those that depend on subscription-based revenue streams. The simple fact is that most organizations have data that can be used to target these individuals and to understand the key drivers of churn, and we now have Keras for Deep Learning available in R (Yes, in R!!), which predicted customer churn with 82% accuracy. We're super excited for this article because we are using the new keras package to produce an Artificial Neural Network (ANN) model on the IBM Watson Telco Customer Churn Data Set! As for most business problems, it's equally important to explain what features drive the model, which is why we'll use the lime package for explainability. In addition, we use three new packages to assist with Machine Learning (ML): recipes for preprocessing, rsample for sampling data and yardstick for model metrics. These are relatively new additions to CRAN developed by Max Kuhn at RStudio (creator of the caret package). It seems that R is quickly developing ML tools that rival Python. Good news if you're interested in applying Deep Learning in R! We are so let's get going!! Customer churn refers to the situation when a customer ends their relationship with a company, and it's a costly problem. Customers are the fuel that powers a business. Further, it's much more difficult and costly to gain new customers than it is to retain existing customers. As a result, organizations need to focus on reducing customer churn. The good news is that machine learning can help. For many businesses that offer subscription based services, it's critical to both predict customer churn and explain what features relate to customer churn.

The International Telecommunications Union (ITU), the United Nations specialised agency for information and communication technologies (ICTs), has launched a new ITU Focus Group to establish a basis for ITU standardisation to assist machine learning (ML) in bringing more automation and intelligence to ICT network design and management. Machine learning algorithms are helping operators to make smarter use of network-generated data. These algorithms enable ICT networks and their components to adapt their behaviour autonomously in the interests of efficiency, security and optimal user experience. Fixed and mobile networks generate a huge amount of data both at the network infrastructure level and at the user/customer level, which contain a lot of useful information such as data on location, mobility and call patterns. New ML methods for big data analytics in communication networks can extract relevant information from the network data, and then leverage this knowledge for autonomic network control and management as well as service provisioning.

LONDON: Chinese technology giant Huawei and the University of Edinburgh, UK, have signed a research cooperation agreement to investigate the potential of artificial intelligence (AI) robotics systems to operate over next generation 5G wireless networks. Researchers at Huawei's Wireless X Labs and University of Edinburgh's new Bayes Centre will investigate together how AI systems can inform and adapt wireless 5G networks to provide optimum wireless support to meet the needs of connected robotics and systems. The areas of initial focus include healthcare robotics and mobile video. "We are delighted to continue working with the world-leading team at the University of Edinburgh to help understand how improvements within mobile broadband can foster innovation within wireless robotics systems," Peter Zhou from Huawei said in a statement. "AI is a key feature of 5G networking, and we are excited to deepen our understanding of how the interaction between applications and networks can create new benefits and enhancements."

BEIJING (Reuters) - Chinese artificial intelligence (AI) startup SenseTime Group said on Wednesday it has sealed an investment from chipmaker Qualcomm Inc as part of a funding round that will close later this year. SenseTime and Qualcomm had announced a strategic tie last month to collaborate on AI, which will see SenseTime's proprietary algorithms deployed in smart devices. Qualcomm, in a statement, confirmed the investment in SenseTime. The two firms did not disclose the size of the investment. Reuters reported earlier in November that SenseTime plans to raise about $500 million in a new funding round, in what would be the biggest ever such fundraising by an AI startup.

The federal government is considering allowing private companies to use its national facial recognition database for a fee, documents released under Freedom of Information laws reveal. The partially redacted documents show that the Attorney General's Department is in discussions with major telecommunications companies about pilot programs for private sector use of the Facial Verification Service in 2018. The documents also indicate strong interest from financial institutions in using the database. The government has argued that the use of facial recognition is necessary for national security and to cut down on crimes such as identity fraud. The Attorney General's Department says private companies could only use the service with the person's consent.

Technology has revolutionized the way our world operates. The pace of its adoption is getting faster in each and every industry. For Example, smartphones have started integrating virtual assistants to make life easier and save valuable time. Similarly, many companies are leveraging artificial intelligence to give the best experience by making smartphones smarter. The technology is set to play a crucial role in driving innovation in the technology space.

Believe it or not, the contributions of small businesses to the global economy of the United States are far better than larger companies. This is why NumberAI, a startup corporation known for helping small businesses, continues to create bold solutions that would help the industry reach its prime. In just a short amount of time, NumberAI has already proved its excellence because of the effort to evolve small and medium businesses. Recently, Draper Fisher Jurvetson (DFJ), a venture capital firm that invests in companies focusing on technology, provided NumberAI a seed funding worth $1.6 million. The raise is going to help the Oakland, California-based company develop additional features to its system, which makes landline numbers smarter.

We are entering a new era of commerce fueled by younger consumers, mobile devices and high demand for more personalized shopping experiences. Millennials are now the largest generation in the U.S. workforce, and their income and buying power are rising. This generation, along with the next tide of digital natives, is putting pressure on enterprises to deliver customer service with the usability and simplicity of consumer apps, and without the inconvenience of phone calls. Companies are investing in artificial intelligence (AI) technology that can provide these experiences through bots, thus ensuring that customers get what they need -- when, how and where they like. Although AI is a solution to customer service problems, intelligent automation is difficult and expensive to develop.