Have you ever used the Shop T-Mobile chatbot? There are several features that I consider a big advantage to have in a chatbot and would like to share them with you. If you like them, feel free to implement the same in your own chatbots and let me know how it worked. How can you use these features? Have you ever come across Facebook ads with the Shop T-Mobile offers in your newsfeed?

We propose a method for practical downlink coordinated multipoint (DL CoMP) implementation in 4G LTE/LTE-A systems using supervised machine learning. Contributions of this paper are: 1) demonstrating that a support vector machine classifier can learn the optimal conditions at which DL CoMP can be dynamically triggered, 2) improving user throughput in DL CoMP as a result of learning the optimal triggering conditions of DL CoMP, and 3) showing that the machine learning approach is scalable to more than a single macro. The simulation results show an improvement in the pico cell average and edge throughputs and a reduction in the downlink block error rate due to the informed triggering of the multiple radio streams as part of DL CoMP as learned from the support vector machine.

A version of this article appeared in the Autumn 2017 issue of strategy business. But just such a change appears to be happening now. In a great wave of technological change, sensors are spreading through factories and warehouses, software is predicting the need for maintenance before a machine breaks down, power grids and loading docks are becoming intelligent, and custom-designed parts are being produced on demand. The leaders of the next industrial revolution are companies making advances in fields such as robotics, machine learning, digital fabrication (including 3D printing), the Industrial Internet, the Internet of Things (IoT), data analytics and blockchain (a system of decentralized, automated transaction verification). Because these technologies all reinforce the others' impact, they are leading to a new level of proficiency, and to new types of opportunities and challenges for business and for society at large. One key indicator is that conventional boundaries between industries are eroding. It's getting harder to tell the difference between, say, a telecommunications company and an entertainment producer, or between a retail bank and a retail store. The relationships among suppliers, producers, and consumers are also blurring, more rapidly than many business decision makers are prepared for. The foundation of business strategy has long been the classic value chain, which links together raw materials producers, manufacturers, distributors, and (in the end) consumers through a well-established commercial infrastructure characterized by a stable set of transactions. But the rise of digital technology enables individuals to connect outside the value chain and deliver more efficient, effective products and services. This will reduce the importance of economies of scale and conventional divisions of labor.

Just before the Mobile World Congress (MWC) confab, where techies meet to enjoy tapas in Barcelona while learning about all things mobile, Qualcomm announced a new software suite. These new offerings seek to enable AI capabilities on existing Snapdragon mobile platforms. While most training of Deep Neural Networks is done in the cloud on NVIDIA GPUs, the use of these AI networks can often be done (calculated) on a mobile CPU--especially if that CPU is more than just a CPU. For Qualcomm, this is a statement of the company's intent to compete with Apple on smarter apps and smarter phones. First, Qualcomm announced the AI Engine, libraries and tools that will enable smart AI apps to use the CPU, DSP, and GPU across the company's Snapdragon chips.

In a stifling room at Mobile World Congress in Barcelona on Tuesday, Chris Reece discussed what artificial intelligence could do for the telecommunications industry. Reece, a technologist for Award Solutions, explained that AI, which telecos have already leveraged in some situations, could help solve some of communications service providers' (CSPs) most complicated problems. CSPs have been slow to adopt artificial intelligence, Reece explained, in part because the initial problems AI was developed to address didn't really affect them. When he asked the crowd for examples of problems they'd heard of AI solving, one person suggested chess, and another mentioned image recognition. Reece agreed, saying, "I don't know a lot of teleco operators who really need a computer to tell the difference between a cat and a dog." "There's a lot of opportunity to use AI in the telecom space, and we're just starting to scratch the surface," Reece added.

As IT environments become more complex, organisations must prepare efficiently. Ericsson has turned to machine learning and AI to do just that. Mobile World Congress has focused a lot around 5G and the Internet of Things (IoT), but Ericsson has shifted the focus back to artificial intelligence (AI). The telecommunications company has announced incorporating machine learning and AI within its entire organisation and customer operations. The aim of the introduction is to enable networks across the company to self-optimize, improve efficiency and deliver better user experiences.

A drone taxi using 5G technology is displayed at the Mobile World Congress on Feb. 27, 2018. Visitors try out Virtual 5G technology during the Mobile World Congress on Feb. 27, 2018. A 5G antenna is displayed at the Deutsche Telekom stand on the first day of the Mobile World Congress. Docomo 5G Robot remote humanoid assistant draws some'sumi-e' style drawings on the first day of the Mobile World Congress. Visitors look at a US company Qualcomm stand announcing '5G' technology at the Mobile World Congress (MWC) in Barcelona, Spain, 26 February 2018 (Photo: EPA-EFE/ALBERTO ESTEVEZ) People walk by a 5G stand at the Mobile World Congress (MWC), the world's biggest mobile fair, on February 26, 2018 in Barcelona.

Charlie Ryan says: "I don't think it will come as much of a surprise to us that there is now AI which can assess and judge our suitability from an uploaded video interaction. I think this will save a lot of time in the recruitment process and have some advantage, however it is still only one stage in the process and it is also an individual interacting with a camera, as opposed to another individual. There are so many areas that will not be assessed at this stage in the process, for example, the interaction with another human being and responding to the unexpected question or scenario. AI definitely has it's part to play in saving us a lot of time and money during some of those basic stages in recruitment and it will contribute to the objectivity of the process overall. What is important to note is that it will never replace the whole process and you need to understand what is being assessed via the AI process to get past it. As with all recruitment do your research, so as you know what you need to do to secure your position in the face to face or final part of the process."

Complex network data may be analyzed by constructing statistical models that accurately reproduce structural properties that may be of theoretical relevance or empirical interest. In the context of the efficient fitting of models for large network data, we propose a very efficient algorithm for the maximum likelihood estimation (MLE) of the parameters of complex statistical models. The proposed algorithm is similar to the famous Metropolis algorithm but allows a Monte Carlo simulation to be performed while constraining the desired network properties. We demonstrate the algorithm in the context of exponential random graph models (ERGMs) - a family of statistical models for network data. Thus far, the lack of efficient computational methods has limited the empirical scope of ERGMs to relatively small networks with a few thousand nodes. The proposed approach allows a dramatic increase in the size of networks that may be analyzed using ERGMs. This is illustrated in an analysis of several biological networks and one social network with 104,103 nodes.

Huawei unveiled in November 2017 the world's first smartphone-driven car using the Mate 10 Pro handset that takes control of the car using an artificial intelligence chip. The MWC presents the latests advances in mobile technologies and will be held from 26 February to 01 March 2018.