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Saudi Arabia signs artificial intelligence agreements

#artificialintelligence

The agreements followed the announcement of Saudi Arabia's National Strategy for Data and Artificial Intelligence, launched during the Global AI Summit Saudi Arabia has signed a series of partnership agreements with international tech companies to advance artifical intelligence (AI) in the kingdom. The agreements, which were rigned at the virtual Global AI Summit held in Riyadh, are underpinned by Saudi Arabia's newly-launched National Strategy for Data and Artificial Intelligence (NSDAI). Saudi Arabia's National Center for Artificial Intelligence (NCAI) announced a memorandum of understanding (MoU) with China's Huawei to enable strategic cooperation on the kingdom's National AI Capability Development Program. Under the MoU, Huawei will support the NCAI to train Saudi AI engineers and students, and to address Arabic language AI-related capabilities. NCAI and Huawei will also explore the creation of an AI Capability Platform to localise technology solutions.


These Factory Robots May Point the Way to 5G's Future

WIRED

Perhaps humans weren't meant to be the early adopters of 5G. At Bosch Rexroth in Bavaria, Germany, wheeled robots that zoom between manufacturing machines and robotic arms that help hoist and connect components come with an unusual new feature--5G modems. The division of Bosch that sells advanced manufacturing equipment sees 5G as a big future trend--and not just for gaming or superfast movie downloads. The company has developed a modular production line where every piece of equipment--plus high-precision power tools--is connected via 5G. The new wireless standard may seem underwhelming so far to smartphone users, but it's gaining followers at some factories, office compounds, and remote workspaces, with good reason.


Domain-specific Knowledge Graphs: A survey

arXiv.org Artificial Intelligence

Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation. This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpreting of knowledge for both human and machine. Therefore, KGs continue to be used as a main driver to tackle a plethora of real-life problems in dissimilar domains. However, there is no consensus on a plausible and inclusive definition to domain KG. Further, in conjunction with several limitations and deficiencies, various domain KG construction approaches are far from perfection. This survey is the first to provide an inclusive definition to the notion of domain KG. Also, a comprehensive review of the state-of-the-art approaches drawn from academic works relevant to seven dissimilar domains of knowledge is provided. The scrutiny of the current approaches reveals a correlated array of limitations and deficiencies. The set of improvements to address the limitations of the current approaches are introduced followed by recommendations and opportunities for future research directions.


Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV

arXiv.org Artificial Intelligence

In this paper, a novel communication framework that uses an unmanned aerial vehicle (UAV)-carried intelligent reflector (IR) is proposed to enhance multi-user downlink transmissions over millimeter wave (mmWave) frequencies. In order to maximize the downlink sum-rate, the optimal precoding matrix (at the base station) and reflection coefficient (at the IR) are jointly derived. Next, to address the uncertainty of mmWave channels and maintain line-of-sight links in a real-time manner, a distributional reinforcement learning approach, based on quantile regression optimization, is proposed to learn the propagation environment of mmWave communications, and, then, optimize the location of the UAV-IR so as to maximize the long-term downlink communication capacity. Simulation results show that the proposed learning-based deployment of the UAV-IR yields a significant advantage, compared to a non-learning UAV-IR, a static IR, and a direct transmission schemes, in terms of the average data rate and the achievable line-of-sight probability of downlink mmWave communications.


Multi-armed Bandits with Cost Subsidy

arXiv.org Artificial Intelligence

In this paper, we consider a novel variant of the multi-armed bandit (MAB) problem, \emph{MAB with cost subsidy}, which models many real-life applications where the learning agent has to pay to select an arm and is concerned about optimizing cumulative costs and rewards. We present two applications, \emph{intelligent SMS routing problem} and \emph{ad audience optimization problem} faced by a number of businesses (especially online platforms) and show how our problem uniquely captures key features of these applications. We show that naive generalizations of existing MAB algorithms like Upper Confidence Bound and Thompson Sampling do not perform well for this problem. We then establish fundamental lower bound of $\Omega(K^{1/3} T^{2/3})$ on the performance of any online learning algorithm for this problem, highlighting the hardness of our problem in comparison to the classical MAB problem (where $T$ is the time horizon and $K$ is the number of arms). We also present a simple variant of \textit{explore-then-commit} and establish near-optimal regret bounds for this algorithm. Lastly, we perform extensive numerical simulations to understand the behavior of a suite of algorithms for various instances and recommend a practical guide to employ different algorithms.


T-Mobile for Business BrandVoice: How 5G Could Transform Supply Chains Post-Pandemic

#artificialintelligence

The pandemic has sent shockwaves through global supply chains, forcing business leaders to reexamine and recalibrate their procurement and outsourcing strategies. Manufacturing and logistics will likely be disrupted for many months to come. And in the long term, there will almost certainly be a greater emphasis on supply chain resilience to better withstand future crises. Businesses will be looking to technology, and 5G in particular, to provide some of the answers. One of the trends emerging out of the pandemic is that supply chains will become shorter and more regional, with less demand for suppliers based in hubs like China.


MLDublin goes remote with Huawei

#artificialintelligence

Happy Halloween to everybody, hope people had a good bank holiday weekend and didn't miss us this week. Kicking off the talks we're joined by Ali Karaali who is going to share his research on deep fakes and how to spot them. We're joined by a couple of folks from Huawei who are join tell about their efforts in putting machine at scale on mobile devices. AGENDA: [18:40 - 19:00] Getting Online [19:00 - 19:10] Welcome [19:10 - 19:30] Ali Karaali, Postdoctoral Research@ Sigmedia Group & ADAPT Centre, TCD How to spot fake videos of real people [19:30 - 19:50] Giovanni Laquidara, Developer Advocate @ Huawei Mindspore is an all-scenario deep learning framework optimized for parallel distributed training, easy adaptable for IOT and open source [19:50- 20:10] William Zhang, Product Manager @ Huawei Machine Learning Kit Open machine learning service inspiring your life This event is strictly for Machine Learning professionals, researchers and students only • If you finally can't make it, please RSVP to "NO" as soon as possible so that other people can take your place.


Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning

arXiv.org Machine Learning

We identify an implicit under-parameterization phenomenon in value-based deep RL methods that use bootstrapping: when value functions, approximated using deep neural networks, are trained with gradient descent using iterated regression onto target values generated by previous instances of the value network, more gradient updates decrease the expressivity of the current value network. We characterize this loss of expressivity in terms of a drop in the rank of the learned value network features, and show that this corresponds to a drop in performance. We demonstrate this phenomenon on widely studies domains, including Atari and Gym benchmarks, in both offline and online RL settings. We formally analyze this phenomenon and show that it results from a pathological interaction between bootstrapping and gradient-based optimization. We further show that mitigating implicit under-parameterization by controlling rank collapse improves performance.


Artificial Intelligence And Africa: The Case For Investing In African Telecoms

#artificialintelligence

Rapid advances in technology, connectivity and telecommunications are conspiring to make Africa's large, rapidly growing population a valuable asset for the automation revolution. It is imperative that Africa quickly develop agency in data and artificial intelligence and it will be lucrative for investors who support them by financing Africa's telecom and data backbone. Africa must urgently develop cogent digital strategy. This at first seems fanciful, or even superfluous, given the continent's relative lack of more basic development. Indeed, there are myriad other challenges to which most would assign primacy.


Huawei Launches Petal Search, Petal Maps, HUAWEI Docs and More - Digital Street

#artificialintelligence

Huawei today announced new developments to Huawei Mobile Services ecosystem at the HUAWEI Mate 40 Series launch event, launching Petal Search, Petal Maps, HUAWEI Docs, levelling up global Huawei users' digital experience with other new updates. Huawei's official search engine app, Petal Search now is available in over 170 countries and regions and supports over 50 languages, letting users conveniently and instantly find out the information and services they need. Petal Search offers search capabilities across more than 20 categories, including apps, news, videos, images, shopping, flights, and local business. It also develops and integrates various tools, such as weather, calculator, rate exchange and even paper query to help user easily obtain daily-used information. With the new update, the search experience is now visually richer.