Patterns of mobile phone communications, coupled with the information of the social network graph and financial behavior, allow us to make inferences of users' socio-economic attributes such as their income level. We present here several methods to extract features from mobile phone usage (calls and messages), and compare different combinations of supervised machine learning techniques and sets of features used as input for the inference of users' income. Our experimental results show that the Bayesian method based on the communication graph outperforms standard machine learning algorithms using node-based features.

We now live in the world of AI and there's plenty of talk about what the future holds. With doubts about the future everywhere, one can predict that AI is soon going to be a key part of our lives. Considering the likely future impact of AI, there's a need to ensure that the right AI talent develops and rises to the top to lead this wave of change. According to several key leaders from Huawei, this can only be achieved by changing certain approaches. As a Huawei partner and a member of Huawei's Key Opinion Leader Program, I joined three other experts in conducting keynotes at Huawei Connect in Shanghai, all related to the question of how to develop talent in the AI era: Dr. Hao Lu, Chief Innovation Officer at Yitu, Huang Weiwei, Senior Management Consultant for Huawei, and Qian Wang, the Co-Founder of Mai Mai.

Chinese phone company Xiaomi has finally launched its phones in the UK, ready to take on companies like Apple and Samsung. As well as its Mi 8 Pro flagship phone – which is now on sale, the first time the phone is available outside of China – the company is selling a wristband and a scooter as it attempts to spread across the world. The company is already the fourth biggest phone company in the world, after Samsung, Huawei and Apple. But it has mostly sold its products in China, and is now seeking to spread into more countries. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

On October 10, 2018, Huawei officially released a full-stack all-scenario AI solution. 'Full-stack' means the solution provides powerful and cost-effective computing power, as well as low-barrier application development platforms that make AI data modeling, model training, and application development simpler, more agile, and more efficient. As an'all-scenario' solution, it is able to drive pervasive intelligence across various device, edge, and cloud scenarios. Ascend 310 is the industry's most powerful AI SoC chip for edge computing scenarios. Currently, the most typical edge computing scenarios are security and protection, autonomous driving, and smart manufacturing.

Ask someone to list life's essentials without which they can't survive, and chances are that their phone will feature near the top. With the increasing use of smartphones, the telecommunication & media industry has become an increasingly critical player in our lives, arguably representing the backbone of digital disruption. Yet service providers still have much to learn. Imagine driving to work and your navigation app prompts you to change routes to avoid a traffic buildup. The source of this information is a combination of artificial intelligence (AI) and machine learning (ML).

At trade fairs like the Mobile World Congress and IFA, Huawei, Samsung and Qualcomm are the main companies that focus on AI. You can also throw in Apple's new bionic processor and Google's Pixel Visual Core into that mix. Of course, this is only the current state of AI functions. AI is growing rapidly in the world of smartphones, and in the future we'll see many more applications. Development is progressing and we're still just at the beginning. Yet, even today there are exciting AI functions you can enjoy, if you have the right smartphone.

The digital telecommunications receiver is an important context for inference methodology, the key objective being to minimize the expected loss function in recovering the transmitted information. For that criterion, the optimal decision is the Bayesian minimum-risk estimator. However, the computational load of the Bayesian estimator is often prohibitive and, hence, efficient computational schemes are required. The design of novel schemes, striking new balances between accuracy and computational load, is the primary concern of this thesis. Two popular techniques, one exact and one approximate, will be studied. The exact scheme is a recursive one, namely the generalized distributive law (GDL), whose purpose is to distribute all operators across the conditionally independent (CI) factors of the joint model, so as to reduce the total number of operators required. In a novel theorem derived in this thesis, GDL, if applicable, will be shown to guarantee such a reduction in all cases. An associated lemma also quantifies this reduction. For practical use, two novel algorithms, namely the no-longer-needed (NLN) algorithm and the generalized form of the Markovian Forward-Backward (FB) algorithm, recursively factorizes and computes the CI factors of an arbitrary model, respectively. The approximate scheme is an iterative one, namely the Variational Bayes (VB) approximation, whose purpose is to find the independent (i.e. zero-order Markov) model closest to the true joint model in the minimum Kullback-Leibler divergence (KLD) sense. Despite being computationally efficient, this naive mean field approximation confers only modest performance for highly correlated models. A novel approximation, namely Transformed Variational Bayes (TVB), will be designed in the thesis in order to relax the zero-order constraint in the VB approximation, further reducing the KLD of the optimal approximation.

Palm helped popularize the idea of a modern smartphone with its Palm Treo, but after failing to keep up with the iPhone and Android the company has been reborn. Its new product: A 3.3-inch companion device to work alongside those phones, not replace it. And yet Palm's past found me wanting to embrace the newly reborn Palm, an adorable and, yes, palm-sized $349 smartphone stand-in on sale Friday as a Verizon Wireless exclusive. I have fond memories for the original PalmPilot, the first truly successful personal digital assistant. I was even a fan of the Palm Pre, a phone with software that was, in hindsight, ahead of its time but couldn't escape the iPhone's shadow.

Pascal Weinberger in conversation with his team at Telefonica's "moonshots" division Alpha, where he heads AI research and development. Flying cars, augmented reality glasses and contact lenses that can detect diabetes: They're all innovations born out of Google X, the skunkworks division of Alphabet. Three years ago Spanish telco giant Telefónica established Alpha, a lab in Barcelona staffed by around 100 people, working in stealth on innovative technology that holds the promise of a potential new revenue streams. The person running all things AI at the lab is Pascal Weinberger, 21. Weinberger is originally from Germany and like many other computer programmers is self-taught.

If a recent demonstration in Canada is any indication, the digital vineyard of the future might very well receive scientific data in real-time gathered by drones and transferred via a cell network. Global UAV Technologies Ltd., Jöst Vineyards, VineView (Scientific Aerial Imaging Inc.) and a major Canadian telecommunications company recently completed a 4G proof-of-concept mission in in Malagash, Nova Scotia, to demonstrate a real-word application of drone technology for a project called the "Digital Vineyard of the Future." "Fine wine making is in the growing of grapes with specific qualities, where many variables have to be taken into consideration," said Jonathan Rodwell, director of viticulture and winemaking for Jöst Vineyards. "We see these emerging technologies offering excellent opportunities for integrated measurement and management of our vineyards and focus on precision viticulture." Global UAV provided a 4G-enabled, Procyon 800E helicopter drone platform with a specialized multi-spectral imaging payload.