Google’s cloud division has formed a group to build business around blockchain applications, following efforts to grow in retail, health care and other industries.
Success could help Google further diversify away from advertising and become more prominent in the growing market for computing and storage services delivered from remote third-party data centers.
Blockchain advocates often talk about constructing decentralized applications that leave large intermediaries out of the equation. In particular, DeFi (short for “decentralized finance”) is a rapidly growing sector of the crypto market that aims to cut out middlemen, such as banks, from traditional financial transactions, like securing a loan.
With DeFi, banks and lawyers are replaced by a programmable piece of code called a smart contract. This contract is written on a public blockchain, like ethereum or solana, and it executes when certain conditions are met, negating the need for a central intermediary. 
This idea of decentralized apps has become more popular among technologists who envision Web3, a decentralized version of the internet that breaks away from Web 2.0, which saw an explosion of user-generated content such as blogs and social networks. Some of those services eventually came to be owned by large internet players — including Google, which bought Blogger and YouTube (which is now one of its strongest businesses).
Today Amazon, Google and other cloud-computing providers represent a type of centralization, by operating vast facilities that offer computing services to millions of customers.
That’s not about to stop Google from trying to capitalize on an opportunity. The cloud group plans to hire a slew of people with blockchain expertise, said Richard Widmann, head of strategy for digital assets at Google’s cloud unit.
“We think that if we do our jobs right, it will drive decentralization,” he said.
Google’s cloud marketplace already offers tools developers can tap to start building blockchain networks, and it has blockchain customers, including Dapper Labs, Hedera and Theta Labs, along with exchanges. Google also offers data sets that people can explore with the BigQuery service to view transaction history for bitcoin and other currencies.
Now, Google is considering what types of services it can offer directly to developers in the blockchain space, Widmann said.
Continue reading: https://www.cnbc.com/2022/01/27/google-cloud-blockchain-team-to-seek-new-business.html

Women from across the US, Mexico and Canada are launching the Women in AI (WAI) Awards North America to honor female pioneers who take the road less traveled and pave the way for others to reach even further.
The kick-off event takes place virtually on February 1, 2022 at 5pm ET when applications for category nominations will also open for: AI in Startups, AI in Research, AI for Good, AI in Government, AI in Industry, Young Role Model in AI.
Winners will be announced at a hybrid event on May 13, 2022. Please email us at [email protected] or visit our website for more information.
Susan Verdiguel, WAI Ambassador to Mexico says, “Through this collaboration, we are able to amplify the AI ecosystem in Mexico for a more robust, informed, and organized community.”
Sponsors/partners include Mila - Quebec Artificial Intelligence Institute, Alberta Machine Intelligence Institute, Topcoder, The Institute for Education, IVOW AI and GET Cities, an initiative designed to accelerate the leadership and representation of women, trans, and nonbinary people in tech.
"We know that AI and machine learning are the future, and we know the risks of not including diverse perspectives in designing solutions for this future. That's why we're thrilled to be a strategic partner for the Women in AI Summit and to celebrate all of the amazing people leading the way in co-creating an inclusive tech economy." - Leslie Lynn Smith, National Director of GET Cities
Continue reading: https://www.businesswire.com/news/home/20220127005418/en/Women-in-AI-Awards-to-Honor-Top-Female-Innovators-in-the-Field-of-Artificial-Intelligence-in-North-America

It is the time of year for reflections, resolutions, predictions and lists. News stories about trends are everywhere, with tips about getting businesses on track for success in 2022. Two trends dominating lists this year are artificial intelligence (AI) and cloud. In the physical security industry the number of security resellers incorporating cloud video surveillance and AI into their business offerings continues to increase. Many resellers are in the process of evaluating newer technologies and business models. Below are four reasons why AI and cloud are topping the 2022 lists, and what it means for security resellers. 1. Security cameras can do more than collect dust Omdia projected that 2021 would be the year that global video surveillance market revenues reached $24 billion, and the year we would surpass one billion security cameras globally. Impressive stats for sure, but those of us who work in the security industry know that the majority of security cameras do not provide proactive security they are simply recording video. More than one billion security cameras are generating video data which is costly to store, and difficult—if not impossible—to interpret or learn from. Fortunately, the cloud can economically and securely store and analyze video data. Even more important, in the cloud, we can make sense of video data. We can learn from it. Meaningful information can be extracted from video to improve customer service, supply chain management and logistics. It can reduce waste, increase efficiency, and more. Another bonus: True cloud video surveillance systems can re-use existing security cameras and infrastructure. There is no rip-and-replace necessary. 2. AI is out of the lab — it is ready In recent years, AI has become a popular and often misused term in video surveillance. In many cases, “AI” became a new name for typical video analytics. The reality is that the deployment of AI is just beginning, but it is no longer just a buzzword. AI is out of the lab and deployed in the real world. Neural networks and AI training make it possible to get more accurate solutions than in the past, and to deliver features such as video search.
Continue reading: https://securitytoday.com/articles/2022/01/27/why-ai-and-cloud-are-topping-2022-trends-lists.aspx

Artificial Intelligence (AI) is on the cusp of becoming mainstream. But research suggests that barriers such as a lack of data quality and technical expertise in the deployment of live applications are creating an implementation gap that will leave some organizations lagging behind in the AI race.
In the 2020s AI looks more and more like the internet did in the 1990s. Every day it’s becoming less of a fringe topic discussed and understood only by the tech-savvy and more like one that businesses across all sectors and of all sizes can’t afford to ignore. The next five years will see more and more businesses use AI to deliver insights and automation more widely across their operations.
However, shifting from AI talk to trials and then onto effective implementation is no easy task. Even for IT literate, technology-focused businesses, successfully implementing AI so that it makes a significant impact on the organization can be an uphill struggle. For other businesses it can feel like a mountain to climb.
Moving from AI talk to trials
Recent research conducted by Opinium for an AI in Business report captures this difficulty and dichotomy – talking the talk is one thing, but effectively using AI is quite another. So, while four out of ten firms are investigating the benefits of AI, only one in 30 is actually actively using AI in at least part of their business. True, this figure is driven by low rates of adoption by micro businesses, but even amongst the largest businesses only ten percent are currently using AI widely, while 35 percent are using AI in a limited way.
The distinction is even more marked when looking at SMEs. Only one percent of small businesses and two percent of medium-sized businesses are widely using AI within their organizations, while 18 percent of small businesses and 32 percent of medium-sized ones are testing it in a limited way. And around a quarter of SMEs and a little under a fifth of large businesses are still just at the stage of talking about AI.
Looking at this data, it’s clear that there’s an implementation gap - and not just across smaller businesses. The willingness is there, but many organizations are struggling to move beyond investigating AI technology.
Only 16% of large businesses have strong data foundations
Overcoming this AI implementation gap means tackling a number of issues within an organization, including technical and cultural. But the most important step is arguably getting the data foundations for AI within a business right including data quality and governance. Research shows that even among large companies only 16 per cent have the right data foundations in place for AI.
Strong data foundations give a business a single reliable version of the truth on which decisions can be made, and around which AI-powered solutions can be built. A data-driven business has three key characteristics:

• Data insight is easily available at all levels within an organization and is used to back up every decision
• Data is combined in one single architecture to enable deeper analysis
• Advanced analytics and AI guide actions across multiple business processes

Continue reading: https://www.techradar.com/features/how-businesses-can-overcome-the-ai-implementation-gap

Artificial intelligence (AI) has already changed our lives in many ways. Applications of the science are visible in smartphone assistants, helpful search engines that seem to predict your thoughts, automated financial advisors, and even automobiles that warn of potential traffic hazards. In the industrial world, companies in sectors such as heavy industry and oil and gas have been using AI to drive value for more than a decade.
But humanity has barely scratched the surface of AI’s tremendous potential. The coming year will see a wider adoption of AI in business and industry. Gartner predicts that worldwide AI software revenue could total $62.5 billion in 2022, an increase of 21.3% from 2021 – a trend only partly attributable to the accelerated digital adoption resulting from the pandemic. Organizations will also continue spending on AI to streamline their operations, reduce costs, boost efficiencies, and foster value chain resiliency.
At the same time, the way AI is deployed is changing. Here are three ways that AI could be deployed in 2022 and beyond.
Multiple types of AI are coming together
The term AI encompasses many different scientific technologies that are applied in various ways. Machine learning algorithms, for example, use data models to make predictions. Reinforcement learning enables intelligent systems to test new approaches and adapt according to failure or success. Natural language processing helps computers communicate with humans, among other use cases.
We are now beginning to see multiple types of AI being applied within a single software environment to deliver an elevated solution. These different subfields – each a unique technology – are beginning to work together to enhance organizational capability and improve business value.
Through a combination of AI and physics-based simulation, for example, we see cutting-edge analytics at work in predictive asset optimization, where probable asset failures can be forecast alongside the provision of an optimized set of actions to mitigate losses. Machine downtime and production losses can thus be eliminated, evolving over time into self-healing autonomous machines, potentially saving hundreds of millions of dollars along the way for large industrial businesses.
Human ability gets extended with AI
AI systems are a natural partner for human intelligence, and we will see this synergy play out over the next few years as the world embraces the concepts behind Industry 5.0. Already, artificial intelligence models help human decision making by providing data-led insights to improve value and sustainability – something AVEVA calls Performance Intelligence.
Continue reading: https://www.cio.com/article/303978/ai-is-maturing-it-will-have-a-transformative-effect-on-industrial-operations.html

Artificial intelligence has worked its way into our everyday lives, and in doing so, has given businesses in many industries a chance to leverage it for better marketing opportunities and smoother operations. Each year, new developments are being made with artificial intelligence and automation that businesses can use in various innovative ways.
The year 2022 promises to follow in the footsteps of its predecessor and start with a whole new realm of possibilities for artificial intelligence and automation. Below, nine professionals from Young Entrepreneur Council weigh in with their predictions of the roles artificial intelligence and automation will play in business this year.
1. Improved Google Algorithms 
AI is already starting to have a big impact on almost every facet of our lives. As innovation in that space is compounding, we will see more and more advancements. This year, I believe that we will see significant improvements to the impact that AI is having on algorithms such as the ones that Google is using to deliver search. And by doing so, businesses that aren't actively optimized for the change will fall behind. I also think that as these machine learning and AI advancements come into play, we will see more automation in customer support, with automation taking over the easy tasks, so that humans can truly focus on assisting customers that need that human touch, which is something I am really excited for! - Emily Stallings, Casely, Inc.
2. Personalized User Experiences
The most significant way artificial intelligence will change the game is by offering a more personalized user experience. Just look at the way that social media algorithms have changed the game in the past decade alone. TikTok in particular is off the charts when it comes to analyzing what their users want to see, and then immediately providing them with more of that exact thing. I think we're going to see a real push in that direction in the world of e-commerce, too. Online ads are going to become even more specific than they already are, and customers will become more receptive to them. AI isn't just about selling a particular product, it helps to capture the interest of clients too. This information won't just come from purchase history, either, but potentially from social media.  - Nick Venditti, StitchGolf
Continue reading: https://www.forbes.com/sites/theyec/2022/01/27/nine-predictions-for-artificial-intelligence-and-automation-in-2022/?sh=64eca0299faf

Amid rapidly changing technology, many people still associate artificial intelligence (AI) with science-fiction dystopias. But in reality, AI has become an integral part of our daily lives. We now rely on search-engine algorithms and digital assistants like Alexa and Siri for almost everything, including ordering a taxi or finding out how many calories there are in a 10-inch Margherita pizza. The potential of this technology goes beyond its household use. AI is making great strides in the business world, and creativity may be its ultimate moonshot. About 200 years ago, scientists believed that machines could not create anything new; they could only follow set instructions to perform tasks. But recently, we've seen AI creating original paintings, music and poetry. 
Of course, artificial intelligence has advanced to a point where it can autonomously generate ideas, concepts or rough drafts. But having this ability doesn't imply that artificial intelligence can replace human creativity. It's not that sophisticated yet. Instead, it serves as a tool humans can utilize to augment their creative ability. So a combination of both elements is necessary to maximize creative output in every field.
We've mentioned how artists are using AI algorithms to create poetry and paintings. But what about business executives? How are they using this technology to find innovative solutions and create opportunities out of problems? AI is proving to be a revolutionary tool across every industry, transforming the way employees and customers interact with businesses and carry out daily operations. AI's adoption in the business domain increased by 270% in the past four years, and we can only expect more widespread adoption in the coming years.
Let’s take a closer look at how AI is radically transforming creativity in business.
Hiring
With the future of work trending towards digital and remote, HR managers are overwhelmed with tons of resumes and applications. Thanks to advanced AI algorithms, they no longer have to spend endless hours identifying the right candidates from a large applicant pool. This intelligent software filters resumes and job applications to find candidates worthy of an interview. Depending on the number of applications a company handles, AI can shave hours or even days off the hiring process.
Another remarkable benefit of implementing a more intelligent, data-driven process is the tendency to eliminate hiring discrimination based on implicit biases. Prejudice is a human trait, but machines are impartial. With such biases out of the way, recruiters and hiring managers can access candidates fairly and make more rewarding hiring decisions.
Continue reading: https://www.entrepreneur.com/article/412856

During her first week as a product marketer for a technology startup in Silicon Valley, Adriana Gascoigne received a disturbing email. It was from one of the company’s lead engineers. It described in detail his infatuation with how she looked and smelled, and professed his desire to be with her – content so inappropriate that Gascoigne first assumed the email was spam.
“That was the beginning of a whole series of issues,” she says.
In the weeks and months that followed, Gascoigne experienced more sexual harassment, profane language, and a dismissive supervisor who deemed her too sensitive when she raised these problems.
“This wasn’t a conducive work environment for diverse groups of people – specifically women,” she says. “I thought it was par for the course, that I had to deal with it and suck it up. But that saddened me, because I knew a lot of other people who were experiencing the same things.”
 
That harsh realization inspired Gascoigne to found Girls in Tech, a global nonprofit dedicated to creating and nurturing a diverse and inclusive technology workforce. Through online and in-person classes and training, Girls in Tech aims to empower, educate, and mentor women through career development, educational resources, and job opportunities. Since its launch in 2007, the group has grown to more than 80,000 members in 55 chapters across 38 countries.
Today, diversity, equity, and inclusion (DEI) are among the most critical issues tech companies face, according to Pega’s Future of IT research report. While the tech industry is slow to make progress, Gascoigne says, the benefits for companies that get it right are invaluable.
The statistics bear that out. Companies that focus on ethnic and cultural diversity are 33% more likely to outperform on profitability, according to McKinsey, while companies with diverse management teams produce 19% more revenue, the Boston Consulting Group has found. Not only that, but organizational teams that focus on diversity and inclusion tend to deliver the highest levels of engagement, according to Deloitte, while diverse teams have been found to solve problems faster than teams of cognitively similar people, Harvard Business Review says.
Despite those undeniable benefits, many tech companies struggle to improve in these areas. Google, for example, only increased the number of women in its workforce from 30% to 32% between 2014 and 2020. Facebook’s percentage of women in the workforce has also been slow to climb, rising from 31% to 37% during the same time period.
Continue reading: https://www.pega.com/magazine/inclusivity-tech-talent-battle

While women are certainly a minority among hardware designers, their leadership and design feats are driving innovation and expanding the talent pool of engineers.
It’s no secret that women tend to be underrepresented in the tech industry and even more so in hardware design. Yet, when it comes to the Newlab, a Brooklyn-based tech lab, you don’t have to look far to find women in leadership positions.

As part of All About Circuits' tour of the Newlab, we had the chance to interview Deren Güler, CEO of Teknikio. In this article, we’ll take a look at the technology of this company with an ambitious female founder at its helm.
Teknikio Makes STEM Available to Both Girls and Boys
Deren Güler is the CEO and founder of Teknikio—a STEM education company focused on engaging children and young girls in particular.  The inspiration for Teknikio was born from the glaring inequities in marketing for STEM educational tools.
“You walk through a store and there's a pink aisle and a blue aisle," Güler says. “I thought it was strange that there wasn’t that much STEM in the pink aisle.”
The goal for Güler became clear: create a STEM company that offers children starter kits and resources that aren’t complicated, daunting, or gender-specific. This mission drove Teknikio’s flagship product: the Bluebird.
Continue reading: https://www.allaboutcircuits.com/news/women-in-tech-are-moving-the-needle-at-brooklyns-newlab-tech-lab/

When Vitalik Buterin, the founder of Ethereum, has been asked lately about his favorite projects being built on the blockchain, he often names Proof of Humanity. Created by the non-profit Democracy Earth Foundation, Proof of Humanity looks something like an online phonebook, on which people can sign up and add their citizenship, degrees or skills. But while the concept is very simple on its surface, Buterin hopes that the system will be an onramp to all sorts of more advanced benefits, including better and fairer voting processes, universal basic income and social media networks that aren’t overrun with bots and misinformation.
To sign up for the registry, you make a short video of yourself, put down a returnable deposit of .157 ETH (about $400) and find one person who is already certified to vouch for you. Your profile then gets added to a theoretically secure and decentralized registry on the blockchain (as opposed to your data living on a Facebook or LinkedIn server). If other members of the community feel you aren’t real, or use the platforms’ facial recognition tools to determine you have duplicate accounts, they can dispute your profile. All of the hoops you have to jump through, combined with the continual communal monitoring of accounts, are meant to discourage the creation of bots or fake accounts in a way that Facebook or Twitter do not.
For this week’s newsletter, I spoke with Santiago Siri, the founder of the Democracy Earth Foundation and the lead creator of Proof of Humanity, as well as a couple blockchain experts who are more skeptical about Proof of Humanity’s goal to become the “internet’s social backbone.” Siri himself doesn’t necessarily see Proof of Humanity as a definitive issuer of internet IDs, but rather one step toward breaking out of what he terms the “colonial internet” controlled by a few Big Tech giants. Here are some of the main problems Siri hopes Proof of Humanity can solve–and the challenges that the project faces.
Continue reading: https://time.com/6142810/proof-of-humanity/

Blockchain technology stands to revolutionize a wide range of industries, and many companies are eager to move their operations on-chain. According to a survey from consultancy Deloitte, 78% of companies believe there is a compelling use case for blockchain technology within their organization, and 73% of them agree they stand to lose their competitive advantage if they fail to adopt the technology.
Most companies want in, but less than 0.1% of developers are senior enough to deliver on the projects they want to build. Why are blockchains so difficult to code for? To build blockchain apps, you need to have access to nodes (essentially units of the blockchain network). Installing and running nodes is difficult, expensive and time-consuming. It’s a full-time job in and of itself.
Running nodes for one blockchain is difficult enough, but maintaining perfectly functioning nodes for multiple blockchains requires a full dev-ops team. Each blockchain has its own language and set of particularities. Learning to code for one can take quite a bit of time; learning to code proficiently for multiple blockchains is next to impossible. Not only that, but smart contracts – executable programs on the blockchain used to build blockchain apps – are coded using completely different languages than the blockchains themselves.
All this learning to build blockchain apps can take months or years to master, and hiring blockchain developers is extremely expensive, if you can even find them. For this reason, up to 90% of blockchain implementations never even get successfully launched. They run out of time and money, and the majority of them fail.
Continue reading: https://www.coindesk.com/sponsored-content/how-to-build-full-blockchain-apps-with-zero-blockchain-development-experience/

At a moment in time when the value of business agility is becoming clearer than ever, a growing range of diverse brands and businesses are prioritizing agility and engaging in digital transformations. Business agility unlocks greater operational flexibility, more nimble and responsive pivots to new processes or priorities, and smarter and more strategic decision-making — all of which is enormously valuable in an increasingly tech-savvy and competitive professional environment, as discussed in my previous article.
One of the most powerful tools that can be deployed to make that transformation successful is artificial intelligence (AI). AI-powered tools and tech form the backbone of systems and solutions that help companies become more agile. What follows is a brief overview of how agile methodologies emerged and why AI delivers such valuable synergies with agile business.
What's Old Is New
Agile methodology was popularized and refined by software developers in the early 2000s, but the roots of agile operation actually date back to the 1950s, with Toyota's development of an innovative production system. Two decades ago, when software engineers began experimenting with new and different ways of developing software, projects and products, the result was a more adaptable and collaborative approach that was producing working software earlier and with higher quality.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/26/the-strategy-and-synergy-of-ai-and-agile-methodologies/?sh=1b47479576c5

From my position at the front line of AI development, I have seen companies beginning to reshape their perceptions and their plans for bringing AI into the workplace — so much so that I believe AI is poised to become more accessible and more productive than ever in the coming year.
First, let’s look at the employment climate: The continuation of the Great Resignation will force companies to accommodate new boundaries while accelerating digital transformation and productivity. From August to November 2021, U.S. job quit rates ranged from 2.8% to a record 3%. Research from HR analytics firm Visier reported that employees between 30 and 45 — the core of most management teams — increased their resignation rate more than 20% between 2020 and 2021. That’s a lot of institutional knowledge and experience walking out the door.
With low unemployment and access to talent limited, employers will look to train, retrain and adapt talent to address skill gaps. In an inflationary market, the situation will get more challenging as the cost of hiring and compensation increases.
I see two complementary effects from this where AI has a role to play:
One, companies may be pressured to accelerate digital transformation efforts that compensate for disruptions in productivity. Two, workers are no longer just looking for a job — they’re feeling empowered to seek a balanced, more holistic work-life experience. The kneejerk reaction to the Great Resignation is the same that it has been for any kind of attrition: Focus on retention. It is less disruptive, more productive and costs far less to invest in current employees than to onboard and train new ones. Adobe’s Future of Time study found that half of enterprise workers surveyed would switch jobs if it gave them access to better tools that made them more efficient at work.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/26/farm-to-table-aiwill-changehow-people-workand-innovatein-2022/?sh=dc6db6c53394

Enterprises yearn for the competitive advantage that ML and AI can offer their business, but often prioritize technology strategically over people to unlock the value of their data. The hype about AI and ML, and the ease of access to it through cloud tooling, belies the complexity of effectively leveraging these capabilities. Why are AI and ML critical capabilities to your business and how will pushing their introduction or expanding their use impact your data strategy?
Unfortunately, many leaders also misinterpret the desire for AI/ML capabilities as a proxy for “we need a better data strategy” and underestimate the effort required to take on this change. It’s imperative that leaders define their data ambitions clearly and align them with the business outcomes sought. This is because the key to effectively unlocking the value of your data starts with aligning your people to this business outcome-driven data strategy. Don’t get me wrong, technology is essential for a modern data strategy, but too often organizations over-rotate on technology and forget about the critical strategic and human elements.
Establishing a data strategy that successfully supports AI/ML adoption requires 3 foundational elements:
1) Data strategy aligned to business goals
Define the “Why” and the “What” first. Start by defining what concrete business goals can be achieved through their use, in what timeframe, at what cost, and at the expense of what other organizational priorities. Is your organization looking to drive down product defects, increase client satisfaction, or innovate new products? Understanding the product or service drivers of your new data strategy will highlight how your existing data strategy will need to change.
Continue reading: https://www.cio.com/article/303947/artificial-intelligence-needs-people-intelligence.html

Edge computing may be a relatively new technology term, but it has not taken long for businesses to understand the benefits of locating their compute and storage resources near the user or the source of the data. By processing information right where applications are running without having to travel back to a data center located miles away, software works faster and so can do more.
The difference is especially noticeable for businesses where every millisecond matters, such as high-frequency financial trading, automated vehicles and equipment safety monitoring. But it’s also highly appealing in contexts where latency isn’t mission-critical, such as content streaming, manufacturing and smart utilities, since today’s users expect near-instant reaction times and an exuberance of capabilities from their applications.
In a recent survey of 1,470 IT professionals, Red Hat found that 72% of the respondents ranked the combination of Internet of Things and edge computing as a priority emerging tech workload over the next 12 months. The range of applications for edge devices is vast – whether it be IoT sensors, internet routers, wearable tech, or factory floor robots. By 2022, there will be an estimated 55 billion edge devices on the market, and by 2025 this is expected to grow to at least 150 billion.
However, the clear benefits of edge computing need to be balanced with perceived risks. Historically, cybersecurity for businesses has been about centralizing operations, meaning that for some, the distributed nature of edge seems a riskier choice. Having more devices can increase the attack surface, and given that edge devices need to be able to send information to and from their data centers, there are possible connections that could be exploited.
Continue reading: https://www.techradar.com/features/edge-computing-a-balance-of-risks-and-benefits

To the dismay of most, 2021 began with disruption everywhere. The global pandemic continued its churn, forcing organizations to maintain remote workforce practices established the year prior. More and more applications needed to be deployed at the edge, and IT managers scrambled to keep up and accelerate their digital transformation strategies. Several key trends that are on my mind — and the 2022 horizon — are listed below:
1. Cost-Effectively Storing Video Forever: In most cases, enterprises must continue to buy expensive disk systems to store video footage for future use, and retention times are limited due to cost. New technologies are emerging that allow video data to be stored for months, years or even forever at low costs by moving to other media like low-end NAS, tape and cloud storage.
2. Customers Seeking Alternatives To Cloud Computing: Data often needs to be processed at the edge due to performance or budgets, and the cost of cloud computing can be prohibitive. The edge needs to be able to process huge amounts of data in real time and send only archived or summary data to the data center or cloud.
3. New Data-Thinning Techniques Introduced: This will help edge solutions handle the massive amounts of data being generated. This will entail sophisticated software to quickly analyze data importance and move it to the appropriate place — keep it local for analytics and AI, move it to a lower-cost storage tier like cloud or tape for long-term storage and future use or delete it if the data just isn’t needed.
4. Virtual Reality Going Corporate: This technology will enter business outside of gaming and entertainment. Healthcare devices, education, training and manufacturing will have a profound impact on the amount of data being generated and the type of files, with a sharp increase in the amount of video data.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/26/2022-predictions-edge-computing-takes-center-stage/?sh=51a7811a38b0

IoT presents many exciting and transformational opportunities in dozens of vertical markets, but the design and test challenges are formidable. End-to-end testing brings a wide range of opportunities. Following the comprehensive 5 C's + 1 approach -- connectivity, continuity, compliance, coexistence, cybersecurity and customer experience -- can maximize your IoT device performance.
Design and validation engineers should optimize IoT products and ensure comprehensive test coverage of the entire range of potential user journeys. Using a modern, AI-assisted approach to model-based testing that emulates user behavior enables testing any technology at every layer. Design and validation engineers can predict the quantified effects of new product versions and create high-quality products that meet and exceed users' needs.

5 C's + 1 test approach ensures your devices thrive
Rapid wireless device growth on the industrial, scientific and medical bands increases complexity in device design, test, performance, security and use. Device testing is one of the biggest challenges for design engineers and device manufacturers. They must address the following challenges across the IoT device lifecycle:

• Connectivity ensures IoT devices connect to other IoT devices, the cloud and necessary software.
• Continuity requires IoT devices have an extended battery life to function.
• Compliance helps IoT devices adhere to and meet global regulations.
• Coexistence ensures that IoT devices work harmoniously in crowded IoT networks.
• Cybersecurity safeguards IoT data from cybersecurity threats.

To set devices apart from competitors, manufacturers should incorporate users' needs and behavior into product design and test early in the lifecycle. 
Continue reading: https://internetofthingsagenda.techtarget.com/post/Surpass-competition-with-user-experience-centered-IoT-devices

The authors of a dangerous malware sample targeting millions of routers and Internet of Things (IoT) devices have uploaded its source code to GitHub, meaning other criminals can now quickly spin up new variants of the tool or use it as is, in their own attack campaigns.
Researchers at AT&T Alien Labs first spotted the malware last November and named it "BotenaGo." The malware is written in Go — a programming language that has become quite popular among malware authors. It comes packed with exploits for more than 30 different vulnerabilities in products from multiple vendors, including Linksys, D-Link, Netgear, and ZTE.
BotenaGo is designed to execute remote shell commands on systems where it has successfully exploited a vulnerability. An analysis that Alien Labs conducted last year when it first spotted the malware showed BotenaGo using two different methods to receive commands for targeting victims. One of them involved two backdoor ports for listening to and receiving the IP addresses of target devices, and the other involved setting a listener to system I/O user input and receiving target information through it.
Researchers at Alien Labs discovered that while the malware is designed to receive commands from a remote server, it does not have any active command-and-control communication. This led the security vendor to surmise at the time that BotenaGo was part of a broader malware suite and likely one of multiple tools in an infection chain. The security vendor also found that BotenaGo's payload links were similar to the ones used by the operators of the infamous Mirai botnet malware. This led Alien Labs to theorize that BotenaGo was a new tool that the operators of Mirai are using to target specific machines that are known to them.
IoT Devices and Routers Hit For reasons that are unclear, the unknown author of the malware recently made BotenaGo's source code publicly available through GitHub. The move could potentially result in a significant increase in BotenaGo variants as other malware authors use and adapt the source code for their specific purposes and attack campaigns, Alien Labs said in a blog this week. The company said it has observed new samples of BotenaGo surface and in use to spread Mirai botnet malware on IoT devices and routers. One of BotenaGo's payload servers is also in the list of indicators of compromise for the recently discovered Log4j vulnerabilities.
The BotenaGo malware consists of just 2,891 lines of code, making it a potentially good starting point for several new variants. The fact that it comes packed with exploits for more than 30 vulnerabilities in multiple routers and IoT devices is another factor that malware authors are likely to consider appealing. The many vulnerabilities that BotenaGo can exploit include CVE-2015-2051 in certain D-Link wireless routers, CVE-2016-1555 impacting Netgear products, CVE-2013-3307 on Linksys devices, and CVE-2014-2321 that impacts certain ZTE cable modem models.
Continue reading: https://www.darkreading.com/vulnerabilities-threats/source-code-for-malware-targeting-millions-of-routers-iot-devices-uploaded-to-github

The proposed Product Security and Telecoms Infrastructure Bill will receive its second reading in the House of Commons today in a debate to be opened by current digital secretary Nadine Dorries, as it takes a significant step forward towards becoming law.
The bill – which mandates improved cyber protections for smartphones and other smart or connected internet of things (IoT) devices – has been years in the making. Its scope has expanded over time to include new provisions that will supposedly spur the roll-out of full-fibre broadband services by making it easier for operators to upgrade and share infrastructure, and reform the process of how they go about negotiating with landowners to whose property they need access.
At its core it places strict new requirements on the manufacturers and retailers of connected consumer technology, banning easy-to-guess default passwords programmed onto devices, creating a vulnerability-reporting system, and forcing manufacturers to be upfront about how long their products will receive security updates.
Failure to comply could result in fines of up to £10m, or 4% of global turnover, and up to £20,000 for every day in the case of ongoing breaches.
“Whether it’s your phone, smart speaker or fitness tracker, it’s vital that these devices are kept secure from cyber criminals,” said Dorries.
“Every product on our shelves has to meet all sorts of minimum requirements, like being fire resistant or [noting if it’s] a choking hazard, and this is no different for the digital age where products can now carry a cyber security risk. 
“We are legislating to protect people across the UK and keep pace with technology as it transforms our everyday lives,” she said.
The bill will apply to any device that can access the internet, including smartphones and smart TVs, games consoles, security cameras and connected alarms, smart toys and baby monitoring kit, smart home hubs and voice activated assistants (such as Alexa) and connected appliances such as washing machines and fridges.
Also in scope will be products that, while they can connected to other devices, do not directly access the internet themselves – such as smart lightbulbs and thermostats, or wearable fitness bands.
Matthew Evans, director of markets at TechUK, said: “Industry has long supported the shared ambition to improve the cyber resilience of devices and has worked with DCMS across the secure-by-design agenda over the past five years. Most suppliers already adhere to the principles of the legislation and, if implemented practically, this will both protect consumers and ensure they have access to a wide range of connected devices. 
“TechUK also welcomes the government’s efforts to reforming the Electronic Communications Code, which is essential to speeding up the roll-out of gigabit and 5G infrastructure. Industry looks forward to further clarity on the amendments to the code to ensure we can deliver the connectivity consumers and businesses need,” he added.
Continue reading: https://www.computerweekly.com/news/252512472/MPs-to-debate-landmark-IoT-security-law

Let’s explore the technological hurdles that we need to clear to advance from one stage to the next in climbing the IoT maturity model. Keep in mind that this is a cumulative process; not only does each stage build on the previous stages, but they also become increasingly complex. Think of it as a progression of math courses. Each lesson builds on the previous ones, and the difference between college and high school math is a lot greater than the gap between elementary and middle school levels.
And, just like doing calculus will be near impossible without command over algebra, any technical shortcomings that we fail to overcome in lower stages are magnified as we move higher into the maturity model.
Is building a mature IoT product challenging? It sure is. But that doesn’t mean it is not possible.
What Technical Skills Are Required to Progress in the IoT Maturity Model?
Stage 1: Embedded Devices
Starting at the bottom of the model, we have purpose-built electronic devices. These products don’t feature connectivity, and people have been building them since Thomas Edison invented the light bulb in 1879. Stage one devices are a bit more complicated now than then, but they still rank low on the maturity model.
The technological challenges to reach this stage are likewise straightforward. As long as our teams have the required hardware and software engineering know-how, we can create a product.
Stage 2: Cloud Computing
Stage two devices connect to the internet. This means we have to add communication protocols, network interface cards (NICs), and back-end infrastructure. Essentially, the technical hurdles of stage two build onto those of stage one with one crucial component: networking.
We need to build server infrastructure and leverage efficient ways to manage it. Another corollary of networking is cybersecurity. Since we facilitate secure connections over a public, unsecured network — the internet — we also need to invest in security talent for a successful stage two product.
Continue reading: https://www.iotforall.com/technical-challenges-to-climbing-the-iot-maturity-model

Elizabeth City State University is building an Unmanned Aircraft System (UAS) training facility to prepare students for jobs in that field.
Stephanie Marquis, a spokeswoman for ECSU, said the outdoor pavilion will be open-air inside a netted area, so students can fly drones for practice. It's on schedule to be built by late summer.
She said the 100-foot wide, 250-foot long, 50-foot high facility will be "the only structure of its kind in North Carolina."
The training pavilion could help students prepare for photography, public safety, disaster response, homeland security and other jobs that commonly use drones.
"UAS is a fast-growing public and private industry – more than 170,000 jobs are expected to be created by 2025," Marquis wrote.
ECSU is already known for its four-year Aviation Science program.
Continue reading: https://www.13newsnow.com/article/news/education/elizabeth-city-state-university-drone-training-facility/291-7ba949bd-35ca-44ae-b37d-71b7bc00217a

Umakant Soni, the co-founder and CEO of ARTPARK joins host Nandagopal Rajan to talk about drones. The duo discuss the prospective use of drones as ambulances, cabs, cargo transportation etc. They further go on to talk about the viability of widespread use of drones in India as well as air traffic management post the introduction of drones for the array of uses in India.

The commercial drone industry is expected to grow at a compound annual growth rate of 57% from 2021 to 2028 as a result of the need for better data and analytics that only drones provide. In order for drones to reach their full potential, drone developers must work with the Federal Aviation Administration (FAA) to manufacture devices that can safely and successfully operate under Aviation Rulemaking Committee (ARC) and FAA guidelines. 
That's the clarion call of American Robotics, the first company approved by the FAA to operate automated drones without humans on-site, which was recently selected to participate on the FAA's Unmanned Aircraft Systems (UAS) Beyond-Visual-Line-of-Sight (BVLOS) Aviation Rulemaking Committee (ARC) to advance BLOVS drone operations. In the eyes of co-founder and CEO Reese Mozer, the FAA's approach to BLOVS flight for commercial drones will dictate the state of the drone industry for years to come, and it's up to the industry to do all it can to work in lockstep with the regulator. 
I sat down with Mozer about why the drone sector needs to work with the FAA and what that means for the future of drone delivery and other BVLOS applications.
GN: What's the FAA's current policy on BVLOS, and what are the FAA's primary concerns when it comes to BVLOS?
Reese Mozer: The FAA's mission and responsibility is the safety of the National Airspace System (NAS), including people and property in both the skies and on the ground. Prior to American Robotics 2021 waiver and exemption, no company had demonstrated to the FAA safe operation without human visual observers (VOs) on-site. The reasons for this are numerous and complex and are both technological and cultural. The short explanation is that humans have been a constant presence during flight for the past hundred years, and ultimately, the primary failsafe if anything goes wrong. Shifting more of this responsibility to software and hardware required a series of technology innovations to be developed, tested, and adequately communicated to regulators at the FAA.
For the past five years, American Robotics has been developing a suite of proprietary technologies explicitly designed to produce the industry-leading solution for safe automated flight. We designed these technologies in concert with a low-risk Concept of Operations (CONOPS) and conducted extensive testing and evaluation as part of a long-term regulatory strategy to prove our system's safety. 
For example, the Scout System incorporates multiple novel risk mitigations, including proprietary detect-and-avoid (DAA) sensors and algorithms, advanced automated system diagnostics and failsafes, automated pre-flight checks, and automated flight path management. If anything were to deviate from the expected, safe operation plan, our drone systems take immediate action to correct, such as altering flight course and returning to the base station. By developing a layered, redundant system of safety that includes these proprietary technical and operational risk mitigations, we have proven that its drone-based aerial intelligence platform operates safely in the NAS, even when it conducts flights beyond-visual-line-of-sight (BVLOS) of both the operator as well as any humans on-site.
Continue reading: https://www.zdnet.com/article/hey-drone-industry-time-to-work-with-the-faa/

Take a look behind the scenes of The Green Planet and discover how drone technology has brought the world of plants to life in the ground-breaking new series.

Ownership of remotely serviced equipment, as well as the right to repair said equipment, could emerge as an issue across many other product lines.
Earlier this month, it was disclosed that the John Deere Company was being sued on the basis of its alleged proprietary maintenance policies. While the lawsuit is specific to John Deere, it might have broader ramifications for IoT down the line.
As documented in Vice, “a class action lawsuit filed in Chicago has accused John Deere of running an illegal repair monopoly. The lawsuit alleged that John Deere has used software locks and restricted access to repair documentation and tools, making it very difficult for farmers to fix their own agricultural equipment.”
This raises some thorny questions about manufacturer’s efforts to keep tabs on product performance through remote sensors, employing ongoing and preventive maintenance or upgrades to sold or leased items. The ability to remotely, and automatically, forestall problems was seen as nothing short of revolutionary as the Internet of Things developed. But can customers opt out of remote maintenance arrangements? If manufacturers still control and modify the software, does that mean they still own the software, and perhaps the hardware around it?
John Deere has been a leader in the IoT space for monitoring and maintenance of the equipment it sells. The company even just announced a fully autonomous tractor, based on “a package of hardware and software that combines machine learning with the company’s GPS-powered auto-steer features.”
Over the past few years, the company “created a cloud-based operations center to analyze data harvested from hundreds of thousands of connected tractors and other farm equipment,” wrote Martha DeGrasse in Enterprise IoT Insights in 2017. “John Deere uses cellular networks to move data from the fields to the cloud. Data is encrypted at the device level and also within the network. Sensors built into the equipment made by John Deere track soil moisture, equipment performance, and even the pressure with which seeds are pushed into the ground during planting. Wi-Fi or low-power wide area networks can be used to collect data and send it to a gateway that connects to the cellular network. Tractors connect directly to John Deere’s cloud using cellular modems. The giant machines report on their location, what activity they are performing, and whether they need service. Farmers can see this data through John Deere’s iPad application.”
Still, farmers have attempted to override John Deere equipment software, and the company has suggested there are legal implications in doing so. “The farming giant argued that because the software was intrinsic to the value of a connected tractor, copyright law meant farmers didn’t actually own the machine,” according to a report by Stacey Higginbotham as the controversy started brewing. “This claim was highly problematic, as typically when someone decides to buy a tractor, this normally entails that the tractor is owned by the buyer. Instead, John Deere granted farmers, “an implied license for the life of the vehicle to operate the vehicle.” This could have interesting implications in the case of an accident.”
Continue reading: https://www.rtinsights.com/iot-implications-lawsuit-alleges-lock-in-maintenance/