This week, telecommunications experts will gather in Barcelona for Mobile World Congress, the industry's premier event and a chance for tech companies to show off their latest innovations in areas as diverse as 5G technology, artificial intelligence, and the cloud. Although the cloud is far from a new idea, its true capabilities are only now beginning to be realized. Here are four ways in which the cloud will shape our lives over the next decade and beyond. Cloud will provide the digital infrastructure of tomorrow's cities, where an estimated 6 billion of the world's population will live by 2045. Smart elevators and parking lots, driverless cars and drone taxis, trains and subways, farms and power plants -- all will be safer and better managed, thanks to the cloud's ability to store and analyze data.

The Linux Foundation launched a deep learning initiative this week designed to create a "neutral space for harmonization and acceleration" of AI, machine learning and deep learning technologies. The initial focus will be an AI standardization effort. The open source project called LF Deep Learning Foundation seeks to make the emerging AI technologies widely available to data scientists and developers, the group said during this week's Open Networking Summit in Los Angeles. Founding members include several Chinese technology giants that are pouring huge sums into AI research as part of a national strategy to dominate AI. They are: China's search giant Baidu; networking giant Huawei (SHE: 002502); Tencent, often referred to as China's Facebook; and telecommunications equipment vendor ZTE (SHE: 000063).

South Korea media outlets are now saying that LG Electronics will likely adopt an advanced type of liquid crystal diode (LCD) display for its upcoming G7 flagship phone. The move is seen as the company's way to make the premium device more affordable and attractive to consumers. Korea Herald reported Monday that the LG G7 is now predicted to feature an advanced LCD panel, called M LCD. The panels will reportedly be manufactured by the tech firm's very own LG Display. An M LCD panel has pixels that are composed of green, red, blue and white colors. The pixels of such an advanced LCD panel are said to emit more light than standard LCD panels, but they consume 40 percent less power.

Residents of Shenzhen don't dare jaywalk. Since April 2017, this city in China's Guangdong province has deployed a rather intense technique to deter jaywalking. Anyone who crosses against the light will find their face, name, and part of their government ID number displayed on a large LED screen above the intersection, thanks to facial recognition devices all over the city. If that feels invasive, you don't even know the half of it. Now, Motherboard reports that a Chinese artificial intelligence company is partnering the system with mobile carriers, so that offenders receive a text message with a fine as soon as they are caught.

As wireless networks evolve towards high mobility and providing better support for connected vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular environments and thus motive rethinking of traditional wireless design methodologies. Future intelligent vehicles, which are at the heart of high mobility networks, are increasingly equipped with multiple advanced onboard sensors and keep generating large volumes of data. Machine learning, as an effective approach to artificial intelligence, can provide a rich set of tools to exploit such data for the benefit of the networks. In this article, we first identify the distinctive characteristics of high mobility vehicular networks and motivate the use of machine learning to address the resulting challenges. After a brief introduction of the major concepts of machine learning, we discuss its applications to learn the dynamics of vehicular networks and make informed decisions to optimize network performance. In particular, we discuss in greater detail the application of reinforcement learning in managing network resources as an alternative to the prevalent optimization approach. Finally, some open issues worth further investigation are highlighted.

The Linux Foundation is aiming to expedite the market for artificial intelligence (AI), machine learning and deep learning with the launch of the LF Deep Learning Foundation at the Open Networking Summit Monday. The LF Deep Learning Foundation is designed to be a neutral space for developers and data scientists in the open source community to work together on projects related to deep learning technologies. At launch, members of the group include Amdocs, AT&T, B.Yond, Baidu, Huawei, Nokia, Tech Mahindra, Tencent, Univa and ZTE. As part of the DL Foundation, the Linux Foundation is also launching the Acumos AI Project designed specifically for AI model discovery, development and sharing. AT&T Inc. (NYSE: T) and Tech Mahindra Ltd. are contributing the initial code to the project -- available today -- as part of a program they announced back in October.

The field of multi-agent system (MAS) is an active area of research within artificial intelligence, with an increasingly important impact in industrial and other real-world applications. In a MAS, autonomous agents interact to pursue personal interests and/or to achieve common objectives. Distributed Constraint Optimization Problems (DCOPs) have emerged as a prominent agent model to govern the agents' autonomous behavior, where both algorithms and communication models are driven by the structure of the specific problem. During the last decade, several extensions to the DCOP model have been proposed to enable support of MAS in complex, real-time, and uncertain environments. This survey provides an overview of the DCOP model, offering a classification of its multiple extensions and addressing both resolution methods and applications that find a natural mapping within each class of DCOPs. The proposed classification suggests several future perspectives for DCOP extensions and identifies challenges in the design of efficient resolution algorithms, possibly through the adaptation of strategies from different areas.

The research on improving Artificial Intelligence (A.I.) has been ongoing for decades. However, it wasn't until recently that developers were finally able to create smart systems that closely resemble the A.I. capabilities of humans. The research on improving Artificial Intelligence (A.I.) has been ongoing for decades. However, it wasn't until recently that developers were finally able to create smart systems that closely resemble the A.I. capabilities of humans. The main reason for this breakthrough in technology is advancements in Big Data.

There's been a significant increase in enterprise investment on technologies that analyse, organise, access, and provide advisory services that are based on use cases for unstructured data. In fact, worldwide spending on cognitive and artificial intelligence (AI) systems will reach $19.1 billion in 2018 - that's an increase of 54.2 percent over the amount spent in 2017. With industries investing aggressively in projects that utilise cognitive and AI software capabilities, International Data Corporation (IDC) now forecasts cognitive and AI spending will grow to $52.2 billion in 2021 and achieve a compound annual growth rate (CAGR) of 46.2 percent over the 2016-2021 forecast period. "Interest and awareness of AI is at a fever pitch. Every industry and every organisation should be evaluating AI to see how it will affect their business processes and go-to-market efficiencies," said David Schubmehl, research director at IDC. IDC has estimated that by 2019, 40 percent of digital transformation initiatives will use AI services and by 2021, 75 percent of enterprise applications will use AI.

Huawei has unveiled the world's first triple rear camera system on a smartphone, which will use artificial intelligence (AI) to help users take photos. The Chinese firm said the new £800 ($1,130) P20 Pro uses AI to identify objects and scenes in the camera's view and adjust its settings accordingly. The smartphone can snap photos in near-dark conditions without using its flash or a tripod by taking exposures lasting up to six seconds to get enough light. Its AI system adjusts the camera's settings to avoid the blurring and smearing that often plagues photographers employing this technique handheld. The P20 Pro is the flagship device among three new phones the company announced at an event in Paris, where the P20 and P20 Lite were also introduced.