Collaborating Authors


Orange's 'test and learn' approach to AI


C-SON (centralized self-organized network) technology has been in use for a number of years to automate the configuration of a base stations, noted Jarrett's colleague, Emmanuel Lugagne-Delpon, SVP at Orange Labs Networks, and now it is being enhanced in two ways using AI capabilities (see the graphic above). The first is "predicting the evolution of the traffic of a cell and the congestion of the cell. The tool is making decisions to re-route traffic to neighbouring base stations, to help avoid congestion, improve customer service and make better use of network resources," noted Lugagne-Delpon. The second is using real-time traffic predictions to switch modules (such as antennas) off when not needed to reduce power consumption, which can cut base station energy consumption by a few per cent, stated the Orange executive. "In these instances we can close the loop – AI is not only providing data but is also taking decisions and actions and the use case is automated," he added.

Security with AI and Machine Learning - Communal News


Why has there been such a sudden explosion of Machine Learning and Artificial Intelligence in security? The truth is that these technologies have been underpinning many security tools for years. Frankly, both tools are necessary precisely because there has been such a rapid increase in the number and complexity of attacks. These attacks carry a high cost for business. Recent studies predict that global annual cybercrime costs will grow from $3 trillion in 2015 to $6 trillion annually by 2021.

Street Lamps as a Platform

Communications of the ACM

Street lamps constitute the densest electrically operated public infrastructure in urban areas. Their changeover to energy-friendly LED light quickly amortizes and is increasingly leveraged for smart city projects, where LED street lamps double, for example, as wireless networking or sensor infrastructure. We make the case for a new paradigm called SLaaP--street lamps as a platform. SLaaP is proposed as an open, enabling platform, fostering innovative citywide services for the full range of stakeholders and end users--seamlessly extending from everyday use to emergency response. In this article, we first describe the role and potential of street lamps and introduce one novel base service as a running example. We then discuss citywide infrastructure design and operation, followed by addressing the major layers of a SLaaP infrastructure: hardware, distributed software platform, base services, value-added services and applications for users and'things.' Finally, we discuss the crucial roles and participation of major stakeholders: citizens, city, government, and economy. Recent years have seen the emergence of smart street lamps, with very different meanings of'smart'--sometimes related to the original purpose as with usage-dependent lighting, but mostly as add-on capabilities like urban sensing, monitoring, digital signage, WiFi access, or e-vehicle charging.a The future holds even more use cases: for example, after a first wave of 5G mobile network rollouts from 2020 onward, a second wave shall apply mm-wave frequencies for which densely deployed light poles can be appropriate'cell towers.'

The Ten Most Dangerous Roads In The World, And How Self-Driving Cars Would Fare


Will self-driving cars be able to cope with highly dangerous roads? Let's talk about dangerous roads. In a moment, I'll provide you with a recently published list of the presumed Top Ten most dangerous roads in the world. For some of you, the odds are that you'll be happy that you've never had a cause to try and traverse these bad-to-the-bone roads, while others of you are probably going to put these alarming roads on your bucket list of places you have to go and give a whirl someday. Do you prefer roads that are calm, easy to navigate, and present little or no qualms?

AI for IT Operations (AIOps) to Address Pandemic Pressures


Before and even more so now during the pandemic, CIOs and IT leaders are managing new capacity increases, security demands, and, in some cases critical, life-saving applications. It is essential how optimized technological performance enables the digital applications that power daily lives. AppDynamics, a Cisco company, helps companies around the world power their complex multi-cloud environments, through application performance management (APM) and Artificial Intelligence for IT operations (AIOps). I asked Luke Rogers, Area VP, Canada, AppDynamics, how COVID-19 has impacted businesses. "The COVID-19 pandemic has transformed our everyday interactions and how companies operate," replied Rogers.

On The Upcoming Eras Of Self-Driving Cars


You might assume that there are remote forests that are still pristine and untouched by humanity. If you aren't trained as a botanist or biologist or ecologist, you might not be aware that many of these seemingly unspoiled forested lands are actually quite marred by the hands of mankind. In some areas, there is a concerted effort to reinstate the earlier status quo of those lands. This involves not only protecting what is there, but also includes doing a systematic restoration to the wilderness too. There are specialists that refer to this as wildlife reengineering.

'Grand Theft Auto V' free video game giveaway crashes Epic Games online store

USATODAY - Tech Top Stories

Epic Games had an offer PC gamers couldn't refuse: The video game publisher's online store would give away free copies of "Grand Theft Auto V" beginning Thursday. But demand proved to be so high that it crashed the game downloading service. Epic Games, which also makes the hugely popular online game "Fortnite," has been releasing a free game weekly through its online store. It plans to continue giving "GTA V" away until May 21. But soon after the giveaway began Thursday, Epic Games tweeted "We are currently experiencing high traffic on the Epic Games Store. We'll provide an update as soon as we can."

Artificial Intelligence: Taking driverless navigation up a gear


AI is not only vital in ensuring successful and efficient navigation, but it's a crucial element in ensuring the journey from A to B is as safe and comfortable as possible. The biggest benefit of AI is its ability to boost efficiency and complete complex tasks that cannot be easily managed by humans. When it comes to navigation, this translates to evaluating real-time conditions with optimum route guidance that helps the driver avoid traffic, amongst other road hazards. The implementation of AI into cars, however, is no easy task. When the control over navigation is taken out of the driver's hands, there's a need to ensure that the data the AI is working with is up to code.

Industry Convergence in the Intelligent City Ecosystem


Everything working and connected – in perfect symbiosis." I help our customers and partners with their digital journey, which involves innovation, business growth, and digital transformation. In this blog series of 6 posts, I look at the universal framework and the "building blocks" of smart cities in several contexts, trying to answer and interpret some of the questions that arise when thinking of digital transformation and smart city construction. In this third post, I touch upon the intelligent city ecosystem and industry convergence. We can think of "smart" at more of a technological level – sensor, actuators, data collection, and a reactive response; for example, a smart street light that switches on and off when it senses a pedestrian.

Driverless Cars Still Have Blind Spots. How Can Experts Fix Them?


In 2004, the U.S. Department of Defense issued a challenge: $1 million to the first team of engineers to develop an autonomous vehicle to race across the Mojave Desert. Though the prize went unclaimed, the challenge publicized an idea that once belonged to science fiction -- the driverless car. It caught the attention of Google co-founders Sergey Brin and Larry Page, who convened a team of engineers to buy cars from dealership lots and retrofit them with off-the-shelf sensors. But making the cars drive on their own wasn't a simple task. At the time, the technology was new, leaving designers for Google's Self-Driving Car Project without a lot of direction.