Expleo’s global head of robotics process automation discusses the growing trends in AI and the importance of encouraging women in STEM.
Rebecca Keenan has had an impressive career already, having become the global head of robotics process automation with Expleo before the age of 30.
Having joined the company as a graduate in 2016, Keenan is now a senior leader responsible for designing and delivering AI and robotics solutions to enterprises across the world.
She spoke to Siliconrepublic.com about her career, diversity in STEM and the trends she’s most excited about in the AI and robotics sector.

‘I highly recommend getting a class of five-year-olds to design robots for you’ – REBECCA KEENAN

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What sparked your interest in STEM?
From a young age, I remember being surrounded by technology and being interested in how it works, and more so what it did for people. I grew up with parents who really allowed and encouraged us as children to experiment with whatever our interests were.
Continue reading: https://www.siliconrepublic.com/people/expleo-rebecca-keenan-robotics-ai

After more than two decades of a career as a woman in STEM, D Sangeeta launched Gotara, a platform to offer professional support and advice to other women in the field, amidst the pandemic. She had noticed that although female participation in STEM education has increased to a gender ratio of 50-50, things tend to go downhill when women join the workforce. 

“Forty percent of women leave their STEM jobs in the first five to seven years - either completely quitting, or going to different fields that pay less,” she tells HerStory.

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The most common reason is believed to be that women reach the age where they want to start a family and focus at home, but Sangeeta saw a different reality as she began interviewing women who were on leave, had quit, or opted for part-time roles. 
She explains, “I found that maybe five percent of those women really, really want to be mothers and nothing else. About 95 percent of these women wanted a sense of belonging and intellectual stimulation, and did not want to leave the workforce. They were either pushed by the work environment, or the home environment.” 
Continue reading: https://yourstory.com/herstory/2021/09/women-in-stem-tech-pandemic-community/amp

Why is there so much confusion within IT Ops teams about data management and data operations (a.k.a. DataOps)? The answer isn't simple. No, database administrators aren't going to make this go away. Yes, it's your problem in IT Ops. You need to learn to operate multiple databases and other data storage systems. To that end, there are four things you need to know to make your life easier.
But first, let's set the table so you have a firm understanding of DataOps and its role in IT Ops.
What it is, why it matters
DataOps is typically a subordinate of cloud operations (CloudOps), which may include cloud and non-cloud systems. And now organizations tightly couple DataOps with machine-learning operations (MLOps). Of course, data must be protected and governed, so you also have security operations and governance operations (SecOps and GovOps, respectively). 
It's little wonder so many operations jobs chase so few candidates. Operations skills in general, and DataOps skills in particular, now top the priority lists of all Global 2000 CIOs. 
Continue reading: https://techbeacon.com/enterprise-it/4-things-it-ops-teams-need-know-about-data-management

Digital society’s lifeblood is data—and governments have lots of data, representing a significant latent source of value for both the public and private sectors.1 If used effectively, and keeping in mind ever-increasing requirements with regard to data protection and data privacy, data can simplify delivery of public services, reduce fraud and human error, and catalyze massive operational efficiencies.
Despite these potential benefits, governments around the world remain largely unable to capture the opportunity. The key reason is that data are typically dispersed across a fragmented landscape of registers (datasets used by government entities for a specific purpose), which are often managed in organizational silos. Data are routinely stored in formats that are hard to process or in places where digital access is impossible. The consequence is that data are not available where needed, progress on digital government is inhibited, and citizens have little transparency on what data the government stores about them or how it is used.
Only a handful of countries have taken significant steps toward addressing these challenges. As other governments consider their options, the experiences of these countries may provide them with valuable guidance and also reveal five actions that can help governments unlock the value that is on their doorsteps.
Continue reading: https://www.mckinsey.com/industries/public-and-social-sector/our-insights/government-data-management-for-the-digital-age

Edge computing is easy to sell but hard to define. More a philosophy than any single architecture, edge and cloud are on a spectrum, with the current cloud service model often dependent on in-browser processing, and even the most edgy deployments reliant on central infrastructure.
The philosophy of edge, as most Reg readers know doubt know, is to push as much processing and compute as close as possible to the points of collection and utilization.
If biology is any guide, edge computing is a good evolutionary strategy. The octopus has a central brain, but each tentacle has the ability to analyze its environment, make decisions and react to events. The human gut looks after itself, with roughly the same processing power as a deer, while both eyes and ears do local processing before passing data back. All these natural systems confer efficiency, robustness and flexibility: attributes that IT edge deployments should also expect.
But those natural analogies also illustrate another of edge's most important aspects – its diversity. 5G is often quoted as the quintessential edge case. It owes most of its potential to being designed around edge principles, moving the decision-making about setting up and managing connections into distributed control systems. The combination of high bandwidth, low latency, traffic management through prioritization, all across moving targets, just can't work unless as much processing as possible takes place as close to the radios (and thus the users) as possible.
Continue reading: https://www.theregister.com/2021/09/21/future_of_edge_computing/

The supply chain is something most people take for granted—until something goes wrong. The pandemic highlighted just how quickly business can grind to a halt if the supply chain is disrupted. Organizations have found that edge computing makes the supply chain run more efficiently, but this move to the edge requires a new approach to supply chain cybersecurity.
Computing on the Edge
Edge computing is becoming a necessity in supply chain management as organizations want the ability to precisely track the status, location and expected arrival time of components and other deliveries.
Because of the ability to better aggregate data, edge computing brings real-time visibility to the supply chain, allowing companies to monitor equipment and operations and make immediate decisions that offer a more effective and efficient delivery of goods.
The increased reliance on internet of things (IoT) and industrial internet of things (IIoT) devices makes edge computing in the supply chain possible, and by 2025, Gartner predicts 75% of enterprises will rely on edge computing. But as the dependence on edge computing rises, so do the security risks.
Continue reading: https://securityboulevard.com/2021/09/securing-the-edge-in-the-supply-chain/

Edge computing is booming. The idea of taking compute out of the data center, and bringing it as close as possible to where data is generated, is seeing lots of traction. Estimates for edge computing growth are in the 40% CAGR, $50 billion area.
Whether it's stand-alone IoT sensors, devices of all kinds, drones, or autonomous vehicles, there's one thing in common. Increasingly, data generated at the edge are used to feed applications powered by machine learning models.
TinyML is a fast-growing field of machine learning technologies and applications that enable machine learning to work at the edge. It includes hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, hence enabling a variety of always-on use-cases.
In order for TinyML to work, a confluence of hardware and software is needed, creating an ecosystem built around the notion of frugal energy needs. This is a prerequisite for applications at the edge.
Today Arm, a global semiconductor IP provider known for its focus on ecosystem creation and frugal energy needs for its processors, is announcing a partnership with Neuton, a provider of an automated TinyML platform. Earlier in September, Alif Semiconductors, another Arm partner building AI chips for the edge, released new product lines.
Continue reading: https://www.zdnet.com/article/machine-learning-at-the-edge-a-hardware-and-software-ecosystem/

Over the last decade, we’ve seen a significant shift in the way we consume services and do business. Users expect rapid performance from digital products, whether they’re using web and cloud applications, streaming content, gaming online or using business-critical services.
At the same time, 5G adoption is increasing and driving growth in more complex and mission-critical Internet of Things (IoT) solutions, resulting in a growing number of devices, applications and volume of data. To be successful in this environment, organizations need faster access to data and seamless, high-speed connectivity, regardless of location, making latency and the flow of data increasingly critical.
Getting Started with Edge Computing
An increasing number of businesses and service providers are turning to edge computing as the answer, adopting decentralized strategies which enable data, applications and content to be processed and managed at the network edge. And with the worldwide edge computing market predicted to grow to $250.6 billion by 2024, resellers must act quickly to capitalize on the opportunity. But where should you start?
Continue reading: https://www.channelfutures.com/best-practices/unlocking-the-edge-opportunity-for-channel-organizations

In early 2021, Americans living on the East Coast got a sharp lesson on the growing importance of cybersecurity in the energy industry. A ransomware attack hit the company that operates the Colonial Pipeline—the major infrastructure artery that carries almost half of all liquid fuels from the Gulf Coast to the eastern United States. Knowing that at least some of their computer systems had been compromised, and unable to be certain about the extent of their problems, the company was forced to resort to a brute-force solution: shut down the whole pipeline.
The interruption of fuel delivery had huge consequences. Fuel prices immediately spiked. The President of the United States got involved, trying to assure panicked consumers and businesses that fuel would become available soon. Five days and untold millions of dollars in economic damage later, the company paid a $4.4 million ransom and restored its operations.
It would be a mistake to see this incident as the story of a single pipeline. Across the energy sector, more and more of the physical equipment that makes and moves fuel and electricity across the country and around the world relies on digitally controlled, networked equipment. Systems designed and engineered for analogue operations have been retrofitted. The new wave of low-emissions technologies—from solar to wind to combined-cycle turbines—are inherently digital tech, using automated controls to squeeze every efficiency from their respective energy sources.
Meanwhile, the covid-19 crisis has accelerated a separate trend toward remote operation and ever more sophisticated automation. A huge number of workers have moved from reading dials at a plant to reading screens from their couch. Powerful tools to change how power is made and routed can now be altered by anyone who knows how to log in.
Continue reading: https://www.technologyreview.com/2021/09/21/1036050/securing-the-energy-revolution-and-iot-future/

As the number of connected devices increases worldwide, the ways that they are being used, designed, and tested have also expanded. The rise of connected devices is demanding engineers to harness the power of the internet of things, which is expected to hit 28 billion by 2025.
A comprehensive approach to device design is needed more than ever to address the challenges that this rapid growth will bring.
Why Engineers Should Be Using IoT Technology In Product Design
The demand for devices designed to use the Internet of Things (IoT) technology is increasing as more industries are finding expanded ways to put them into use. Industries such as healthcare, automobiles, and agriculture are becoming more dependent on cloud capabilities and are therefore in need of new devices able to connect to it.
Due to this rise in demand, an increasing amount of devices are delivering a multitude of benefits both to consumers and companies. However, this new wave of products has led to a growing list of challenges for engineers as they are forced to address IoT tech in regards to connectivity, regulations, longevity, and security.
Continue reading: https://www.securityinformed.com/insights/addressing-internet-iot-challenges-device-design-co-2925-ga.1631540683.html

Not a week goes by without some sort of vulnerability or breach associated with the IoT taking place. More devices, varied devices, and the rise of far more sophisticated attackers have led to big IT firms investing in their own security capabilities while our government issues executive orders trying to compel companies to invest in better security.
Today’s version of better security requires layers. And after a conversation with Kate Scarcella, chief cybersecurity architect at Micro Focus, I’m convinced that monitoring device behavior will be one of those layers. Much like law enforcement officials trying to assess threats look for suspicious behavior exhibited by people, Scarcella believes devices can provide a set of “tells” after they’ve been compromised.
All we need is software that can spot the one weird device out of thousands.
Continue reading: https://staceyoniot.com/forget-perimeters-for-security-look-at-device-behavior/

Companies from various industries discovered the world of Internet of Things and incorporated it in their workflows to increase productivity, cut costs and deliver better services to clients. But there is one thing that is dangerous to overlook: IoT security. If the IoT devices are compromised, a threat of DDoS attack, identity theft, spoofing and data leakage appear. That’s why the correct approach to protection in Internet of Things software development is vital.
What is IoT Security?
IoT security means practices that companies implement to increase the level of protection in the devices that receive, keep and transfer sensitive data. Every industry uses the advantages of Internet-connected devices, yet companies have to pay more attention to the safety of their data.
Although the Internet of Things significantly increases the efficiency of business workflows and makes the work processes quicker, companies are now hugely dependent on these modern technologies. Recently, due to a number of data breaches, it is pivotal to establish well-worked IoT security requirements.
Continue reading: https://latesthackingnews.com/2021/09/20/iot-security-internet-of-things-security/

In recent years, there has been a lot of talk about the potential of the Internet of Things (IoT) to revolutionize how we live. From microwaves that scan food packaging and follow cooking instructions, lights that switch on and off as we enter and leave rooms, to fridges that automatically order items as we run out, the vision is that connected devices will share information to make our lives easier.
Some of this potential has already become reality. Many of us wear a smartwatch or have a smart speaker and, as a result, have a clearer sense of how a network of interrelated devices might change how we interact with appliances and physical objects. While it may be more difficult to envisage IoT having a transformative impact on a service industry like wealth management, there is in fact immense potential. The ability to collect and transfer data between sensors, wearables, and other devices and applications offers wide-ranging opportunities to help wealth managers and advisers deliver a more personalized, suitable, and affordable service.
Crucially, IoT can help to optimize the service experience and outcomes for clients. Through geolocation, they can be referred to a local adviser, with calendars aligned and optimized to ensure the best use of time for all participants. Pulling data on all the client’s financial affairs by utilizing Open Finance will help the adviser ensure the client has enough money for day-to-day bills and expenses, accessible savings, separate savings for specific events, and long-term investments. The adviser can also automate switching between pots as cash flow changes to maximize returns and make the best use of tax allowances.
Continue reading: https://www.finextra.com/blogposting/20924/will-internet-of-things-transform-the-wealth-management-customer-experience

To think we live in a wirelessly connected world is a bit of an understatement
Our lives revolve around technology! Here us out: many of us begin our days checking our smartphones. We often tell Alexa to switch on the radio while preparing a meal and use wearables to track our daily workouts. None of this was imaginable ten years ago!
Add the Internet of Things (IoT) to the mix in the public spaces, and we can suddenly operate systems and devices from afar — from automatically-controlled street lights to agri-apps to optimize fertilizer usage to remotely-monitored parking garages.
Long gone are the days of long wires and tin cans. Today, communication protocols such as cellular, Bluetooth, and WiFi rule the roost and provide us seamless connectivity anywhere we are, regardless of the device in use. Life without access to the internet is now unthinkable.
With 5G around the corner, cellular IoT is mainly well-positioned to benefit from higher bandwidth solutions that would usually be allocated to WiFi or wired Ethernet.
Continue reading: https://technative.io/future-of-cellular-iot-is-now/

Until the first half of the 20th century, industrial organizations relied primarily on the human factor to control and monitor their processes. However, with increasingly complex operations and ever-larger factories, in the 1970s, digital PLCs (programmable logic controllers) and computers became famous as an interface for data transmission to remote control centers. Soon later, the «telemetry» was born, from the Greek «metria» (measurement) and «tele» (remote), and with it, a control system the SCADA: Supervisory Control and Data Acquisition Systems. It is called the third industrial revolution, and today, there is no industrial company that does not have PLCs or SCADAs in its operation.
Internet of Things (IoT) and Artificial Intelligence (AI) allow today to witness another great technological leap that many dare to call the fourth industrial revolution.
The scope goes far beyond «data acquisition and monitoring.» It focuses on the advanced processing of large volumes of data that allows faster and more efficient decision-making processes and less risk and margin for error. However, we are still in the process of consolidating this new revolution, as the limits between the investment made in the third industrial revolution and the one needed for the fourth one are not yet clear.
In this article, we give three keys to the roadmap that must be followed by any company that doesn’t want to be left out of the fourth industrial revolution.
Continue reading: https://www.iotforall.com/iot-and-scada-systems-forced-to-coexist-and-understand-each-other

The Internet of Things (IoT) is one of the most important trends of the 21st century and is destined to change our business and markets.
IoT applications have been present for the longest time in the industrial field, leading to the emergence of the Industrial Internet of Things (IIoT).
IIoT is the area of IoT in the greatest rise and prominence, with advancements related to automation and robotics. This is thanks to the innovation that production systems are experiencing with the adoption of the Industry 4.0.
With this fourth industrial revolution, we have stopped separating companies to ones that only do services and others that only deal with products. Instead, there is now a union of the physical with the digital (named “Phygital”), that allows all those who have the courage, audacity, and skills to start using IoT technology to imagine a different world.
Continue reading: https://www.automationworld.com/process/iiot/article/21723170/iot-applied-to-marketing

The previous article provided a brief introduction of what blockchain technology is and how it differs from the conventional ledger technology we use today. This article will build on that to explain how a blockchain works and how it can be useful to different sectors.
Now, it is important to note that all of blockchain technology, whether it is cryptocurrencies or anything else, relies heavily on very advanced cryptography. As such, explaining how it works to the lay person can get quite technical. The following explanation is an attempt to convey the ideas behind blockchain without getting bogged down in the details.
Transactions in Blockchain
Before a transaction takes place and can be uploaded onto the blockchain, it needs to be verified. Let’s take an example. Person A wants to transfer money to Person B. The details of the transaction, along with other key information, is processed into a block. This block also contains a public key or password that every node has access to and a private key that only Person A has access to. contains the transaction information. The solving of this complicated problem simultaneously provides the details of the transaction and also authenticates it. Once the authentication is complete, everybody on the blockchain knows that Person A has transferred money to Person.
Continue reading: https://www.livemint.com/brand-stories/how-can-blockchain-technology-be-used-11632214222337.html

Stony Brook University professor Peng Zhang, a SUNY Empire Innovation professor in the Department of Electrical and Computer Engineering, is leading a statewide team of collaborators in developing “AI-Grid,” an artificial intelligence-enabled, autonomous grid designed to keep power infrastructure resilient from cyberattacks, faults and disastrous accidents.
The work is part of the National Science Foundation’s (NSF) Convergence Accelerator Program, which supports and builds upon basic research and discovery that involves multidisciplinary work to accelerate solutions toward societal impact.
In September 2020, the program launched the 2020 cohort, which included AI-Grid as a phase 1 awardee and grant funding of a $1 million to further AI-Grid research from an idea to a low-fidelity prototype. The Convergence Accelerator recently selected teams for phase 2, to focus on expanding the solution prototype and to build a sustainability plan beyond the NSF funding. Under phase 2, a new $5 million NSF cooperative agreement will fund the AI-Grid project.
“This project led by Professor Zhang is a great example demonstrating the impact of this novel research on essential infrastructure that we rely on daily, and defines a pathway for enhancing the resiliency and security of our electrical grid systems,” said Stony Brook University Vice President for Research Richard J. Reeder.
Continue reading: https://news.stonybrook.edu/university/protecting-the-energy-grid-through-artificial-intelligence/

IoT proves to be a valuable technology for many organizations and sectors. If organizations can develop and standardize certain aspects of the IoT architecture, they can tap into the full potential of their investments. In this article, Kamal Rupareliya, chief of customer product success, Intuz, discusses the key factors to consider before designing IoT infrastructure.
Unlike a few technology fads of the past (remember, AOL, Napster, AltaVista?), the Internet of Things or IoT has proven extremely valuable for a range of organizations and sectors.
The technology has the potential to revolutionize all industries, from agriculture and healthcare to transportation and education. As per reports by IDC, the IoT global market revenue is predicted to reach approximately $1.1 trillion by 2025.
IoT promises a future where we can control almost every aspect of life remotely. In contrast to traditional data applications, the technology has no limit in terms of the number of devices deployed.
While the IoT invariably generates immense amounts of data, there is a heightened focus on harnessing and transmitting the information collected.
Obviously, the Internet infrastructure is going to face challenges as more sectors adopt it. Thus, we need wider access to create a better system for exchanging and storing our data while at the same time making efficient use of available technology.
Eight Components of IoT Infrastructure
If businesses develop and standardize certain aspects of the IoT architecture, they can tap into the full potential of their investments. They can prepare their IoT deployments successfully by understanding each infrastructural component and how they all work together.
Continue reading: https://www.toolbox.com/tech/iot/guest-article/factors-to-consider-when-designing-the-iot-infrastructure/

As the number of connected devices increases worldwide, the ways that they are being used, designed, and tested have also expanded. The rise of connected devices is demanding engineers to harness the power of the internet of things, which is expected to hit 28 billion by 2025.
A comprehensive approach to device design is needed more than ever to address the challenges that this rapid growth will bring.
Why Engineers Should Be Using IoT Technology In Product Design
The demand for devices designed to use the Internet of Things (IoT) technology is increasing as more industries are finding expanded ways to put them into use. Industries such as healthcare, automobiles, and agriculture are becoming more dependent on cloud capabilities and are therefore in need of new devices able to connect to it.
Due to this rise in demand, an increasing amount of devices are delivering a multitude of benefits both to consumers and companies. However, this new wave of products has led to a growing list of challenges for engineers as they are forced to address IoT tech in regards to connectivity, regulations, longevity, and security.
Ways To Use IoT In The Development Process
Engineers are facing these new challenges along with the normal pressure of deadlines and test considerations. By approaching all of these issues from a comprehensive point-of-view, the solutions become clearer and new device capabilities can be born. Let’s look at the challenges individually as well as possible solutions for them.
Improving Connectivity
IoT enables data to be transferred between infrastructure, the cloud, and devices, making the process smooth 
Because IoT is based around connection, it’s no surprise that the primary challenge for engineers to overcome is the improvement of connectivity between devices. IoT enables data to be transferred between infrastructure, the cloud, and devices, so making this process as smooth as possible is crucial.
The main challenges involved with connectivity have to do with development and product testing while meeting industry standards and best practices. Additionally, many companies lack the necessary equipment and technology to develop new IoT devices, which makes it difficult to create scalable prototypes and test new products.
Suggested Solutions
To address the issue of not having the expertise and necessary tools for testing, we suggest outsourcing the prototyping and evaluation process instead of attempting to tackle this in-house. By doing this, you’re able to free up resources that would otherwise be needed for expensive equipment and qualified staff.
Helping Comply With Regulations
When working with devices that are connected across the world, there is a complex web of regulations and conformance standards that can lead to challenges for engineers. The necessity of complying with these regulations while also pushing to meet deadlines can be burdensome and lead to an increase in production time and expenses.
Failure to comply with global and regional laws, as well as system and carrier requirements, can lead to fines and costly setbacks. This type of failure can destroy a company’s reputation on top of causing financial losses, often leading to the loss of business.
Continue reading: https://www.securityinformed.com/insights/addressing-internet-iot-challenges-device-design-co-2925-ga.1631540683.html

With new technological advancements coming to light every day, the supply and demand for IoT devices has increased significantly. Humans have started relying on these devices for even the most basic everyday functions. In fact, as per a study conducted by IDC, 4 out of 5 people check their phones within 15 minutes of waking up! With IoT devices taking over our daily lives, cyber criminals are a little too ambitious to let the opportunity slide. 
As IoT devices store, transmit and process so much essential data every day, they serve as the perfect target for cyber criminals. According to an article published by Cyber Magazine, IoT devices suffer an average of 5,200 cyber attacks every month. While businesses are reaping huge benefits from the IoT ecosystem, the risk of cyber attacks has increased exponentially as well. 
Major IoT Cyber Threats in 2021
There are a number of cyber risks plaguing the world of IoT devices. Some of the major IoT cyber threats in the current times include:
#1 Absence of Updates and Unencrypted Updates
Another primary cyber risk associated with IoT devices is the lack of regular updates and weak update mechanisms. These devices may be secure initially, however, they become vulnerable with the discovery of new security bugs or issues. If these bugs and issues are not fixed through regular updates, the devices become exposed to attacks. 
Several old devices don’t even provide any security updates and most of the newer models do not ensure secure installation of security patches. The absence of proper encryption in a device’s security patch installation process significantly increases the risk of code modification by threat actors. 
The infamous Satori malware serves as a perfect example of such attacks. This malware delivers a worm to a vulnerable device so that the infection spreads from device to device without any human interaction. It spreads by targeting known vulnerabilities in specific ranges of IoT devices. 
In December 2018, Satori infected several D-Link home routers around the globe, making them a part of the potent IoT botnet used for attacking websites and mining cryptocurrency. The routers were infected by exploiting a 2-year-old remote code-execution vulnerability. 
Continue reading: https://securityboulevard.com/2021/09/cyber-threats-haunting-iot-devices-in-2021/

Edge computing is easy to sell but hard to define. More a philosophy than any single architecture, edge and cloud are on a spectrum, with the current cloud service model often dependent on in-browser processing, and even the most edgy deployments reliant on central infrastructure.
The philosophy of edge, as most Reg readers know doubt know, is to push as much processing and compute as close as possible to the points of collection and utilisation.
If biology is any guide, edge computing is a good evolutionary strategy. The octopus has a central brain, but each tentacle has the ability to analyse its environment, make decisions and react to events. The human gut looks after itself, with roughly the same processing power as a deer, while both eyes and ears do local processing before passing data back. All these natural systems confer efficiency, robustness and flexibility: attributes that IT edge deployments should also expect.
But those natural analogies also illustrate another of edge's most important aspects – its diversity. 5G is often quoted as the quintessential edge case. It owes most of its potential to being designed around edge principles, moving the decision-making about setting up and managing connections into distributed control systems. The combination of high bandwidth, low latency, traffic management through prioritisation, all across moving targets, just can't work unless as much processing as possible takes place as close to the radios (and thus the users) as possible.
Move it
But another high-profile edge application, transport, needs a very different approach. An aircraft can generate a terabyte of performance and diagnostic data on a single flight, which outstrips the capabilities of in-flight datacomms.
Spread that across a fleet in constant global flux, and central control isn't an option. Autonomous processing onboard, prioritising of immediate safety information such as moment-to-moment engine parameters for available real-time links, and efficient retrieval of bulk data when possible, lead to design decisions far removed from 5G engineering.
Continue reading: https://www.theregister.com/2021/09/21/future_of_edge_computing/

Artificial intelligence (AI) conjures a lot of unique imagery depending on your background and how much exposure to the topic you’ve had. For some people, AI looks and feels like something out of The Terminator or 2001: A Space Odyssey — an oppressive, human-like intelligence that poses an existential threat. To some, AI is simply a fancy name for digital assistants like Siri or Cortana. Of course, if you have a lot of development experience, you know the line between AI and any other kind of computer programming is blurry and that in some ways, a basic pocket calculator could be considered AI.
But no matter what your initial conceptions are, we can all agree on one thing for sure — AI has incredible potential to transform our world and to increase productivity, improve efficiency and solve problems that have henceforth been considered unsolvable. But is your business ready for the impending AI explosion?
The Exponential Potential Of AI
Technology rarely develops in a linear way. Instead, our technological progress tends to leap forward in major spurts and increase exponentially in some contexts (think of, for example, Moore’s Law, which is used to predict innovations for semiconductors). Over a period of years, the entire business landscape can be transformed, multiplying productivity, opening the door to new market opportunities and pushing the limits of human potential.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2021/09/20/how-to-prepare-for-the-coming-ai-explosion-in-business/?sh=7f539cdf2113

As Artificial Intelligence becomes increasingly ubiquitous, it's developing a special relationship with edge computing. Consider these important factors as you develop your AI strategy
Artificial Intelligence (AI) is moving from the realm of science fiction to widespread enterprise scalability. Even ten years ago, AI workloads were almost exclusively utilized by a small number of very profitable companies that had the resources to experiment and hire an extensive team of data scientists. Today, AI is used in a number of everyday tools, from language recognition to health care prediction and nearly every industry in between.
AI is also now deployed at the edge, not just inside massive data processing facilities. That trend will continue in the coming years. Here are three things that executives in any field should know to capitalize on the change.
1. Open source is your friend
Open source is fueling the rise of AI as developers learn from the larger community to make software elements more accessible for a number of use cases. The open source community operates as a school of fish, pivoting quickly en masse in response to the environment. For example, TensorFlow became a hit within a month before the majority of developers converted to the library for deployment solutions. That fast a timeline was unheard of before.
Continue reading: https://enterprisersproject.com/article/2021/9/artificial-intelligence-ai-edge-3-key-facts

RPA, commonly referred to as drones, are an emerging and innovative technology being used around the world. Drones have a diversity of applications including in the agricultural sector, emergency services, infrastructure inspections and surveys, surf lifesaving, delivery of medical supplies, aerial photography and commercial delivery just to name a few.
There are currently no internationally-mandated noise aviation standards for drones. Countries and regions across the world are considering what regulations and standards may be appropriate given the drone industry is rapidly evolving and any regulation needs to take account of advances in drone technology.
The Air Navigation (Aircraft Noise) Regulations 2018 (the Regulations) apply to drones, therefore a range of commercial and recreational drone operations within Australia require approvals under Section 17 of the Regulations. 
Drone Noise Regulations
Given increasing use of drones, the department conducted a review of current noise regulations to determine the appropriate scope and breadth of future noise regulations for drones. More information on the review can be found at Noise Regulation Review for RPA and Specialised Aircraft.
One of the recommendations from the Review of the Air Navigation (Aircraft Noise) Regulations 2018 – Remotely Piloted Aircraft & Specialised Aircraft report was the development of flexible, risk-based interim regulations for drone and electric Vertical Take-off and Landing (eVTOL) aircraft noise.
The Review’s recommendation would require amendments to the Air Navigation (Aircraft Noise) Regulations 2018 to appropriately regulate noise impacts from emerging aviation technologies, such as drones and eVTOL aircraft. The current Regulations are designed for traditional aircraft noise management.
To address this recommendation from the Review, a Regulation Impact Statement (RIS) has been prepared for public consultation which contains options for amendments to the regulations. A copy of the RIS can be found at National Emerging Aviation Technologies Consultation.
Continue reading: https://www.infrastructure.gov.au/infrastructure-transport-vehicles/aviation/aviation-safety/aircraft-noise/drone-noise