The edge is a rich source of new data, whether it's from subscribers connected to a telco's latest 5G network, or radio signals detected in a battlefield environment. Faced with the huge data volumes and an increasing demand for low-latency analysis and action, the processing needs to occur local to the source – at the edge itself. Furthermore, security, compliance and corruption risks may dictate whether the data is permitted to be moved away from the edge at all, and if allowed, in what curated form. A data center or cloud used in isolation cannot meet all these emerging needs. But most customers don't want to reinvent the wheel when analyzing data at the edge, and instead prefer to reuse proven technologies like AI, while adopting architectures that have already been honed inside a data center or cloud.

Leading cloud and managed service company, Maintel, recently revealed a new study into the attitudes consumers and businesses share towards virtual assistants. As artificial intelligence and voice-activated bots become more commonplace, the recent research from Maintel highlights why some companies are still hesitating before rolling out this new tech. Among consumers, data protection is usually the most significant concern linked to AI, with 47% saying they're worried about being hacked. Additionally, there's a consistent sense of reluctance among consumers in the UK when it comes to engaging with smart devices. Around 59% of customers don't have an intelligent device with a virtual assistant.

Opportunity, accuracy, exploration, medical progression, risk reduction, support, disruptive innovation, quality of life improvement, equality, just a few of the many opportunities that can be explored through the development of Artificial Intelligence (AI). What would once be the script for a Sci-Fi movie, is now nothing but the nowadays reality. Now the fiction element is gone and space travel, quantum computing, mind-reading, human memory upload to cloud and brain wave communications turned into simple development projects of AI integration. While the advantages gained by AI and Machine Learning integration are undeniably beneficial to humanity and a core evolution facilitator, introducing such powerful and impactful tech to society can easily spin around and become a colossal threat. So, the challenge lies around identifying this fine ethical line that separates the good from the unjust, the honest from the unfair or the moral from the corrupt.

New Story partnered with the design firm Fuseproject to offer what it believes to be quality architecture. Alexandria Lafci explained that, "Even when populations are seemingly vulnerable, or seemingly will accept whatever is given, that's not an excuse to not really push to have the highest quality of whoever you're working with." This raises another concern, one about craftsmanship. If 3D houses are the next big advance in architecture, surely this means that any profession that involves craft expertise will be changed, if not be replaced by machines. Jason Ballard, the CEO and co-founder of Icon explained to Wired, "You could print a house in the shape of a Fibonacci spiral if you wanted to.

Questions about the future of work are on the rise, as automation and artificial intelligence become more pervasive in our lives. For example, the newspaper articles you've read this week might have been written by bots. These questions deal with the economic, social, and environmental impact of automation technologies. Whether we consider this impact as positive or negative, the change is deep. It challenges the traditional productivism model that has been so far applied to business but also society and nature, where resources are transformed to create consumable products.

Municipalities, just like the industrial and commercial sectors, are coming under increased pressure to reduce their energy consumption and outputs, not to mention the need to reduce costs overall. Municipal buildings and services have a huge energy savings potential, which can reduce their overall energy consumption and energy costs. At Maximpact our expert teams have assisted municipalities all over the world to identify their energy saving capacity in various sectors. As cities around the world become more urbanised and populations grow, the pressure of cities to find sustainable solutions to serve their communities is only going to increase. Changes to municipalities in becoming more energy efficient and using artificial intelligence to manage energy resources are part of a global trend of developing smart cities. Smart cities are looking to the future to redefine their energy outputs in cleaner, more sustainable and more cost-efficient ways.

If human intelligence is the capacity to assimilate new information, assess its implications and relative importance and to come to a conclusion that guides decision making, then Artificial Intelligence (AI) is the technology to make machines do the same thing. These technologies include machine learning, natural language processing, computer vision and chatbots. The potential for AI to assist in healthcare decision making is huge; we have barely scratched the surface. While the role of AI in routine diagnosis and treatment is growing steadily, its significance in avoiding medical errors and ensuring patient safety can only be imagined. According to a January 2019 white paper from the UK's Academy of Medical Royal Colleges, the question of whether patients will be safer with technology than without it is central to the introduction of AI in healthcare.

For Adam Jasinski, a technology director for a school district outside of St Louis, Missouri, monitoring student emails used to be a time-consuming job. Jasinski used to do keyword searches of the official school email accounts for the district's 2,600 students, looking for words like "suicide" or "marijuana". Then he would have to read through every message that included one of the words. The process would occasionally catch some concerning behavior, but "it was cumbersome", Jasinski recalled. Last year Jasinski heard about a new option: following the school shooting in Parkland, Florida, the technology company Bark was offering schools free, automated, 24-hour-a-day surveillance of what students were writing in their school emails, shared documents and chat messages, and sending alerts to school officials any time the monitoring technology flagged concerning phrases.

Research by the UK's Bank of England (BoE) and Financial Conduct Authority (FCA) has found that the country's financial services businesses are fast deploying machine learning (ML) technology to tackle money laundering and fraud. The survey found that ML – defined as "the development of models for prediction and pattern recognition, with limited human intervention" – is increasingly being deployed, with use expected to more than double in the next three years. As well as addressing crime, businesses are developing ML tech for customer-facing applications such as customer services and marketing. The central bank and regulator combined forces to run the survey, having pinpointed ML as a'principal driver' of how innovative technology is transforming global finance. The survey was sent to organisations such as e-money institutions, banks, financial market infrastructure firms and investment managers.

SEATTLE, Oct. 24, 2019 (GLOBE NEWSWIRE) -- Global supercomputer leader Cray, a Hewlett Packard Enterprise company (NYSE: HPE), today announced that the High-Performance Computing Center of the University of Stuttgart (HLRS) in Germany has selected a new Cray CS-Stormä GPU-accelerated supercomputer to advance its computing infrastructure in response to user demand for processing-intensive applications like machine learning and deep learning. The new Cray system is tailored for artificial intelligence (AI) and includes the Cray Urika -CS AI and Analytics suite, enabling HLRS to accelerate AI workloads, arm users to address complex computing problems and process more data with higher accuracy of AI models in engineering, automotive, energy, and environmental industries and academia. "As we extend our service portfolio with AI, we require an infrastructure that can support the convergence of traditional high-performance computing applications and AI workloads to better support our users and customers," said Prof. Dr. Michael Resch, director at HRLS. "We've found success working with our current Cray Urika-GX system for data analytics, and we are now at a point where AI and deep learning have become even more important as a set of methods and workflows for the HPC community. Our researchers will use the new CS-Storm system to power AI applications to achieve much faster results and gain new insights into traditional types of simulation results." Supercomputer users at HLRS are increasingly asking for access to systems containing AI acceleration capabilities.