Huawei (pronounced "Wah-way") is the world's largest telecommunications company. A member of the Fortune Global 100, it is also the world's third-largest seller of smartphones. Just one day after its launch of the world's first Artificial Intelligence embedded smartphone, the Mate 10, in Munich, Germany, Huawei hosted the Ultra Broadband Forum in Hangzhou, China. It attracted attendees from over sixty-five countries. I was invited to the conference as a key opinion leader and Huawei partner.

What are they actually good for? In the recent months we've heard a lot about specialized silicon being used for machine learning in mobile devices. Apple's new iPhones have their "neural engine"; Huawei's Mate 10 comes with a "neural processing unit"; and companies that manufacture and design chips (like Qualcomm and ARM) are gearing up to supply AI-optimized hardware to the rest of the industry. What's not clear, is how much all this benefits the consumer. When you're buying your phone, should an "AI chip" be on your wish list?

Microsoft is delivering the world's first fully neural on device translations in the Microsoft Translator app for Android, customized for the Huawei Mate 10 series. Microsoft achieved this breakthrough by partnering with Huawei to customize Microsoft's new neural technology for Huawei's new NPU (Neural Processing Unit) hardware. This results in dramatically better and faster offline translations as compared to existing offline packs. The Microsoft Translator app with these capabilities comes pre-installed on Huawei Mate 10 devices allowing every Mate 10 user to have native access to online quality level translations even when they are not connected to the Internet. Until now, due to the computational requirements of neural machine translation, it was not possible to do full Neural Machine Translation (NMT) on-device.

Their joint research will focus on developing the fifth-generation wireless technology known as 5G, which could deliver data at a much faster speed than the current wireless technology and is seen as crucial for autonomous vehicles. They will also research other wireless technologies needed for the safety of connected cars, LG said in a statement.

Artificial intelligence is all the rage these days. There's broad consensus that AI is the next game-changing technology, poised to impact virtually every aspect of our lives in the coming years, from transportation to medical care to financial services. Gartner predicts that by 2020, AI will be pervasive in almost every new software product and service and the technology will be a top five investment priority for more than 30 percent of CIOs. An area where AI is already showing enormous value is wireless networking. The use of machine learning can transform WLANs into neural networks that simplify operations, expedite troubleshooting and provide unprecedented visibility into the user experience.

Artificial intelligence (AI) is the next technology to enter the hype cycle, and while it will most certainly have an effect on IT operations, the details as to how it will be implemented and how to generate a maximum return on investment are still unknown. At the moment, of course, the key challenge is overcoming the significant barriers to deployment, which include not only disruption to legacy architectures but to long-established business cultures as well. According to a recent study by Vanson Bourne on behalf of Teradata, a good 80 percent of enterprises are currently investing in AI, with telecommunications firms, professional and customer service providers and financial institutions leading the charge. While most outfits believe that the technology will produce significant ROI over the next decade, only about one-third see the need for additional investment over the next three years in order to remain competitive. At the same time, issues like the lack of advanced IT infrastructure and the need for AI-related skillsets in the workforce are seen as major barriers, as are the ever-present budgetary concerns.

Qualcomm is continuing to place emphasis on the wearables segment, with senior director of Product Management for Qualcomm Atheros Pankaj Kedia telling media that the chip giant will be "doubling" its play in the market. "We have seen public announcements from some of our competitors that they are exiting the wearables space; Qualcomm is doubling our investment, because we are winning today and we intend to continue," Kedia said during the Qualcomm 4G/5G Summit in Hong Kong. Over the next two to three years, you will really see growth around all of this." Kedia said Qualcomm has a cyclical relationship in wearables market growth, increasing its investments alongside growth while in return driving the market with these investments. "Because we are investing in wearable-specific chipsets, we are able to drive market growth, and we are able to do that in a leadership fashion where a majority of wearables shipping today are based on Qualcomm," he said.

From The Terminator to Blade Runner, pop culture has always leaned towards a chilling depiction of artificial intelligence (AI) and our future with AI at the helm. Recent headlines about Facebook panicking because their AI bots developed a language of their own have us hitting the alarm button once again. Should we really feel unsettled with an AI future? News flash: that future is here. If you ask Siri, the helpful assistant who magically lives inside your phone, to read text messages and emails to you, find the nearest pizza place or call your mother for you, then you've made AI a part of your everyday life.

Recently, our team of data consultants had an awesome opportunity to present to a class of future data scientists at Galvanize Seattle. One student who came to hear our talk was Rebecca Njeri. Below, she shares tips on how to design a Data Science project. To Begin, Brainstorm Data Project Ideas To begin your data science project, you will need an idea to work on. To get started, brainstorm possible ideas that might interest you.

The Huawei Mate 10 Porsche Design Edition smartphone could be one of the sleekest yet. Featuring a dedicated Artificial Intelligence processor with machine learning, 6GB of RAM, 256GB of internal storage, a rear dual camera setup consisting of a 12-megapixel RGB and 20-megapixel monochrome modules offering f/1.6 aperture dual lenses. "Powered by AI technology, the camera takes photography to the next level, from artistic to intelligent, identifying different scenes in real time. It automatically adjusts the color, contrast, brightness and exposure to produce vibrant, sharp, perfectly framed photographs. It delivers AI-powered'bokeh' effect by shifting the focal point onto the subject of the photograph for picture-perfect portraits and selfies, and is even capable of capturing clear and sharp pictures of objects in motion," according to Design Boom.