While you know that more than 120 million global users have invested in cryptocurrencies so far, you may not envision that as a consumer, multiples of this figure have already been exposed to the world of blockchain and its use cases. Slowly but surely, blockchain technology is permeating the backbone of how services are delivered to end users. Be it supply chain management, cross border remittance and distribution of NFTs, the world around us is adopting blockchain technology at a rapid pace. Naturally, we must ask the question – can we sustainably build a career in this space? The short answer is an emphatic yes. Read on to find out more.
Evolution of the Information Age
In the 1990s, Information Technology (IT) was still a developing field. If you ask your relatives who did engineering/sciences back then, many would have chosen electrical/mechanical based specialties over computer science. This changed in the 2000s – IT and related fields continue to be the most dominant field of study even today. Blockchain technology is a specialty within IT. Though it is a newer specialty with a limited set of use cases today, the future is full of possibilities. 
Blockchain is essentially a place to record, store and execute information. Everything we do on a regular basis today can be disrupted by a new service which uses blockchain. Given the above, it becomes a wise choice for the youth of the nation to start building a career in blockchain based companies. One, it gives them early exposure to a fledgling technology. Two, it allows them to innovate and expand boundaries of the space over time. 
Continue reading: https://www.thenewsminute.com/article/building-career-blockchain-technology-157507

Consumers have good reason to worry about the frailty of the global food supply chain. This is not because of lack of food, but because—as we’ve recently seen—supply-chain breakdowns can drive up prices. Logistical hold-ups, factory closures, climate change and labour shortages in the agriculture and agri-food sectors create a domino effect that strikes all levels of the system. 
As this crisis worsens, with no end in sight, food-industry juggernauts like Walmart Canada are experimenting with ways to increase efficiency using blockchain, a technology whose reputation tends to be shrouded in the hype over cryptocurrency. 
These applications have nothing to do with Bitcoin, and everything to do with increasing the level of safety, transparency and traceability of food from farm to table. Even though these applications are still in the early stages of development, pilot projects have been promising enough that blockchain aficionados envision a future where—similar to the internet—it could be hard to imagine life (and food) without it. 
Continue reading: https://www.macleans.ca/economy/how-blockchain-could-revolutionize-food-supply-chains-and-lower-your-grocery-bill/

The cryptocurrency world is full of jargon. You’ve got your non-fungible tokens (NFT), your Ethereum, your Solana, your know-your-customer (KYC), your altcoins, your stablecoins – not to mention where it all started: bitcoin.
If all this jargon had a home, it would be the metaverse, or the parallel digital world in which cryptocurrency and NFTs are transactable. And the metaverse would not be possible without blockchain, the system of decentralized databases upon which all interactions are coded and stored into perpetuity.
This article originally appeared in Crypto for Advisors, CoinDesk’s weekly newsletter defining crypto, digital assets and the future of finance. Sign up here to receive it every Thursday.
In the proverbial chicken-or-egg debate, cryptocurrency and blockchain happened simultaneously, says Robert Konsdorf, the CEO of Facings, a Michigan-based company that creates user-friendly blockchain publishing tools. Bitcoin was both the first publicly debuted blockchain and the first cryptocurrency. Some 12 years ago, its inventor, the pseudonymous Satoshi Nakamoto, authored a famous document known simply as the Bitcoin white paper describing the concept for the world.
Continue reading: https://www.nasdaq.com/articles/demystifying-blockchain-for-your-clients

Incorporating Artificial Intelligence (AI) across fundamental business functions is becoming a necessity for the survival of organisations. Hence, forcing companies to rely even more heavily on data to make core decisions.
Today, there is an influx of companies moving towards the next phase of AI where machine learning runs on the back of information to bolster human capabilities.
Machine Learning algorithms are dependent on the data provided. They make connections, cultivate understanding and execute decisions based on the training data provided. Therefore, the higher the quality of training data, the superior the function of the model.
Tech teams
Therefore, data intended for training algorithms needs to be augmented and labelled.
Now, if one stores a huge amount of well-structured data in the dataset, it might not necessarily be labelled to work as a training dataset for the intended model.
Continue reading: https://www.businessdailyafrica.com/bd/opinion-analysis/letters/bring-artificial-intelligence-business-life-3616716

Although Artificial Intelligence (AI) is a technology that has existed for more than sixty years, today, thanks to greater computing power, the applications of this field of information technology have had a direct impact on the spine of companies. , that is, in business values .
To refer to business values we can say that they are the pillars that guide the behavior of workers and managers, as well as the principles that guide decision-making, helping the company to achieve its founding objective or mission.
It is precisely these values that make it possible to communicate the business culture, facilitate understanding, promote continuous improvement processes, set ethical standards and, above all, those that make your company unique.
The high impact that Artificial Intelligence has had within companies in recent years has led to the transformation of values. That is why, this time, I share with you the 7 new business values in the era of Artificial Intelligence.
Continue reading: https://www.entrepreneur.com/article/396564

Businesses want to get personal with their customers to better understand their intentions, behaviors and desires, in order to create trust, build loyalty, and of course, drive revenues. It’s also something customers are coming to expect in an internet-driven economy. Today’s consumers are looking for intuitive shopping venues, compelling product information, personal recommendations based on their preferences, seamless transactions and a consistent experience, regardless of the channel they’re using.
For retailers, manufacturers and distributors, the key to understanding their customers and building a relationship with them is in their data, specifically master data. Reinvented models of multi-domain master data management (MDM), built on new technologies and insights, can help retailers, manufacturers and distributors combine data from across the spectrum, including product, customer, location and supply data, to improve the customer experience and increase sales, while also reducing costs. Multi-domain MDM can also help these organizations better understand not only the customer, but also the marketplace, allowing them to anticipate trends and respond more quickly to shifts in customer interest.
How data is impacting the way goods are made, moved and sold
The new economy has blurred the lines between production, supply, sale and other traditionally separate elements of consumer sales.
Retailers. Retailers, for example, need both master data and operational data in order to provide a unified, holistic experience. For instance, users may interact with the same product using a marketplace or a wholesaler’s website. The journey to that product may take different routes, but the same information is still needed as consistency in the way the product is presented is crucial. Combining these two data sources by leveraging advanced technologies provides a more unified experience and increases the product’s competitive advantage.
Take the use of machine learning (ML) and artificial intelligence (AI), which can help create a contextualized, empathic customer experience. AI’s role in the process is flexible, depending on the use cases or business outcomes being sought, but at a high-level the technology can help provide new insights into data on what customers are buying, why they’re buying and what channels they’re using, answering questions such as: What drives a consumer to shop? What drives a sale? What types of products are customers willing to pay more for?
AI analytics, along with other technologies like 3D virtual reality (VR), can also draw on data to help customers experience a product, putting it in context and telling a story they can relate to. MDM and product information management (PIM) combined with VR can, for example, allow retailers to offer customers highly detailed 3D tours of stores—tailored even to individual stores—and products down to the atomic level of product data, attributes and metadata. It can incorporate dynamic modeling of customer behavior to make the experience even richer. It’s an approach that can build brand loyalty and trust with the customer.
Manufacturers. Manufacturers are also being enabled by data. Today, they’re much like retailers in their direct-to-customer approach. They take the same dynamic approach to understanding their customers and combine operational data with product and consumer data to improve the customer experience and boost their revenues. Where manufacturers really thrive is in understanding what’s in demand. This is crucial for manufacturers. By driving these insights, they can feed that knowledge back to their development lifecycle. This means, changing products in real-time if needed so that there’s an increased chance of making a sale.
Continue reading: https://www.sdcexec.com/software-technology/ai-ar/article/21747696/precisely-the-role-of-data-management-in-the-future-of-manufacturing-distribution-and-retail

The Internet of Things (IoT), the convergence of the digital and physical worlds, has emerged as one of the fundamental trends underlying the digital transformation of business and the economy. From the fitness trackers we wear to the smart thermostats we use in our homes to the fleet-management solutions that tell us when our packages will arrive to the sensors that promote increased energy efficiency or monitor natural disasters resulting from climate change, the IoT is now embedded in the lives of consumers and the operations of enterprises and governments.

Sidebar
Defining the Internet of Things

In 2015, the McKinsey Global Institute published a research report entitled The Internet of Things: Mapping the value beyond the hype. The report analyzed the economic potential that the IoT could unleash through consideration of hundreds of use cases in the physical settings in which they could be deployed.
Six years later, in a new report, The Internet of Things: Catching up to an accelerating opportunity, we have updated the analysis to estimate how much of that value has been captured, how the potential value of the IoT could evolve in the coming decade, and the factors that explain both (see sidebar, “Defining the Internet of Things”). The market has grown considerably in the intervening years but not as fast as we expected in 2015. The IoT has faced headwinds related to change management, cost, talent, and cybersecurity, particularly in enterprises.
Here’s what our latest research found:
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Research overview

• The potential economic value that the IoT could unlock is large and growing. By 2030, we estimate that it could enable $5.5 trillion to $12.6 trillion in value globally, including the value captured by consumers and customers of IoT products and services.
• The IoT’s economic-value potential is concentrated in certain settings (types of physical environments where IoT is deployed). We found that the factory setting (which includes standardized production environments in manufacturing, hospitals, and other areas) will account for the largest amount of potential economic value from the IoT, around 26 percent, in 2030. The human-health setting is second, representing around 10 to 14 percent of estimated IoT economic value in 2030.
• B2B applications are where the majority of IoT value can be created, with around 65 percent of the estimated IoT value potential by 2030. But the value of B2C applications is growing quickly, spurred by faster-than-expected adoption of IoT solutions within the home.
• The 2030 IoT economic-value potential of the developed world will account for 55 percent of the global total, decreasing from 61 percent in 2020. China is becoming a global IoT force as not only a manufacturing hub and technology supplier but also an end market for value creation.

Continue reading: https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/iot-value-set-to-accelerate-through-2030-where-and-how-to-capture-it

It’s a bold statement, but I predict every enterprise organization will be impacted by one or more of three key wireless trends in the next 18 months.
When we hear “wireless,” most of us will immediately associate it with “Wi-Fi” — the 802.11 WLAN standard we know, (usually) love and use daily both at home and in the office. But wireless encompasses so much more than just traditional Wi-Fi, and the burst of digital transformation combined with enterprises’ escalating security demands is proving ripe for the emergence of novel wireless use cases and, therefore novel, sometimes repurposed, wireless technologies.
Here’s a look at the top three wireless trends that I believe will shape the face of network security architecture in the enterprise.
New Wi-Fi Standards And Security
While wireless extends beyond it, Wi-Fi is still the leading technology for our hyperconnected and very mobile world, so it’s worth noting two significant changes every organization should be prepared for, starting with the new Wi-Fi security standard.
Our dirty little secret in Wi-Fi is that we’ve been limping along with the same security standards for 15 years — eons in the context of the rapid advancements in cryptography and security protocols. Announced in early 2018, the latest Wi-Fi Protected Access version (WPA3) is just now making its way through all the enterprise Wi-Fi products. The new security standard brings several notable improvements for enterprise security architecture, including all three types of networks: enterprise-secured (802.1X), pre-shared key (PSK-based networks) and open networks for guest portals.
In addition to much better application of cryptography, stronger algorithms, forced mutual authentication and even encryption for open guest networks, the new security suite promises enhanced resiliency by securing Wi-Fi management traffic and preventing downgrade attacks that are common vectors for both penetration testers as well as malicious attackers.
The good news is, WPA3 is designated for continuous improvement, ensuring organizations will have enhanced protection and new security controls as the threat landscape changes. The bad news is, taking advantage of WPA3 has some gotchas when transitioning from legacy WPA2 — meaning security and IT leaders will need to ensure their architects are well educated and trained on the newer technology.
Also, for IT teams considering the latest Wi-Fi 6E technology (6th generation Wi-Fi, 802.11ax, over the newly-opened 6GHz spectrum), WPA3 holds a special meaning, as it will be required for those deployments; there will be no backward compatibility or transition modes for security.
Ultimately, WPA3 addresses countless vulnerabilities and is something your organization should explore and implement as soon as you can, but it does take thoughtful planning and coordination. There’s no “easy button” here.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2021/11/10/three-wireless-trends-impacting-enterprise-security-in-2022/?sh=7479b0e26163

At Connect 2021, Mark Zuckerberg proceeded in a critical strategic announcement by officially introducing the Facebook company rebrand Meta, the name of the company that will focus on developing metaverse ecosystems.
Meta is not the only company including metaverse technology in its strategic roadmap, with Microsoft, SK Telecom, Unity and Nvidia all investing in the technology with aspirations of leading the metaverse arena. All these tech players already are experienced with the key technologies essential for metaverse.
The metaverse is the convergence of the physical and virtual 3D world over the internet, where users own their avatars/holograms and can collaborate and interact with virtual objects and other avatars. Use cases could include conducting business, socializing or attending events.
To become a reality, metaverse requires the further maturity and the synergy of multiple emerging technologies that are the key components of the digital transformation journey for many industries today, including AI, computer vision IoT, AR/VR, edge/cloud compute, blockchain and 5G.
Among the technologies essential for building the metaverse, IoT, digital twins and AI are the most critical that need to be deployed first.
To establish the duality of digital and physical world, it is essential to create the digital twins of the real world, environments and assets. Digital twins are digital replications of physical assets/buildings or processes that use collected data to reflect their real time performance and status changes.
As the amount of collected data increases, the introduction of AI and machine learning algorithms can make digital twins more viable and increase the capabilities in a metaverse scenario. AI algorithms can learn from the large amount of historic data, make informed decisions and automatically predict future actions or recommend solutions.
For example, the deployment of smart city metaverse use case is very promising, thanks to the rapid growth of smart city IoT projects. By leveraging data from IoT sensors, it is possible to create the digital twin of the entire city that can provide information about buildings, traffic status, parking availability and energy consumption.
In the metaverse stage of a smart city, citizens could visit public authorities virtually through their avatars or be continuously updated and visualize smart city data where and when they need it.
At that point, the XR (extended reality) devices which is essentially the human interface for metaverse scenarios allow users to visualize IoT data and digital twins in the real world, interact with digital objects, create content and manage their avatars or holograms.
In the early stage of metaverse deployment, the majority of apps and use cases will be focused on entertainment, gaming and social networking. However, as metaverse technology evolves and matures, it has the potential to empower other verticals like manufacturing, engineering and smart cities.
Besides the technological requirements needed to reach that stage of metaverse, it requires a series of activities focused on social acceptance, privacy and security and content creation.
Continue reading: https://www.iotworldtoday.com/2021/11/10/omdia-analyst-metaverse-leaders-should-heed-security-privacy/

Every two years, we eagerly watch from our homes as swimmers break world records or skiers fly down the slopes, and with every passing event, IoT becomes more and more embedded in all of our relationships with The Olympics. From how we watch and engage with the athletes and the sports, to training, to even how judges assess athletes’ technique and performance, the Internet of Things is playing an increasingly valuable role in not just the Olympic Games, but in all sports as we know it.
IoT Technology in the Olympics
At the Rio and Tokyo Olympics, IoT technology improved the accuracy and interactivity of the Games. These are some of the top six IoT technologies used in the recent Olympic Games.
Smart Stadiums
One of the biggest IoT providers in Japan introduced the smart stadium to the Tokyo Olympics. Smart stadiums enhanced the user experience for spectators at the Olympics and for people watching at home. A smart stadium is blanketed with wireless connectivity that allows everyone in the stadium to have fast and easy access to the internet. For viewers at home, the smart stadiums increase instant replays on the stadium’s app that make it easier to see what’s happening in real-time. Athletes are able to see real-time metrics as well, thanks to the connectivity in the stadium.
For attendees in the stadium, smart stadiums enhance the experience of being in the stadium. Spectators can watch the real-time replays while panning their phones over different areas of the stadium for more details and an up-close view. Augmented reality lets spectators zoom in on athletes for their stats and performance. Attendees can also monitor concessions and restrooms to limit the amount of time spent in line.
Robot Assistants
Toyota helped develop robot assistants for the Tokyo Olympics. These robots greet spectators and athletes as well as provide on-field assistance. The robots can retrieve javelins and hammers to return to athletes, and they can guide staff across these dangerous fields to help them do their jobs while keeping them clear of thrown equipment. To make sure these robots can assist everyone, they are programmed to understand and speak many languages. IoT connectivity allows the robots to communicate, move, scan, and choose routes.
Continue reading: https://www.iotforall.com/how-iot-is-involved-in-the-olympics

In the twenty-first century, smart technologies have begun to penetrate nearly every facet of our lives and the sports and fitness industry is no exception. The Internet of Things (IoT) is a global tech trend that marries everyday devices to the power of the cloud, thus creating endless opportunities for businesses. IoT has the potential economic impact of up to $1.6 trillion in the health and fitness sector globally by 2025, according to McKinsey and Co. In addition, the global sports tech market is expected to reach $40.2 billion by 2026. And yet, businesses at the intersection of sports, fitness, and health still fail to identify the benefits that disruptive technologies have to offer.
The Shift in Consumer Expectations of Sport and Fitness Industries
To illustrate how technologies have tightly wound themselves into our everyday lives, let’s look at how someone might start their day. They wake up and exercise or maybe start their day with yoga or meditation. In all of these activities, they are most likely to use technologies at hand – to track their heartbeat with fitness bands or smartwatches, track their speed or count the distance, or use guided meditations that help switch off the distractions and remind them to concentrate on breathing.
All of these fitness trackers with sensors that collect data are nothing other than IoT that we use on a daily basis without even realizing it. What we do realize is that we use all these devices to improve our performance, and in order to improve, we need them to collect more and more data about our activities. Data aggregation, analysis, and connectivity make these devices smart. With such smart fitness devices, consumers’ expectations become limitless.
Users want real-time monitoring and analysis of their vitals. They expect their smart gadgets to be tailored to their needs and offer them a more personalized approach. The smart wristbands and watches should – and are already – reading blood oxygen levels, generating an ECG, detecting spikes in heart rate levels, tracking sleep stages, and even detecting if the person wearing it has washed their hands.
Beyond health tracking, smart devices also connect us to global sports events with remote spectating, stadiums and sporting venues now offer immersive fan experiences. The connected person isn’t just a concept from sci-fi movies anymore, it’s reality.
Continue reading: https://www.iotforall.com/how-iot-can-help-businesses-in-the-sports-and-fitness-industry

What IoT trends are you keeping an eye on for 2022?
Having started as a hyped futuristic technology, the Internet of Things (IoT) is now a fully-fledged reality. IoT solutions are already helping businesses with predictive maintenance, schedule maintenance and the collection of data – and in 2022 we will continue to see companies using IoT to enhance their operations.
For example, over the course of the pandemic we saw a significant increase in spending on various technologies ranging from 5G and Blockchain to Artificial Intelligence (AI) and automation; companies will continue to implement these alongside IoT to optimize their remote workforce in the on-going shift to hybrid working.
Given the numerous safety challenges that have arisen recently in the IoT domain, next year there is likely to be much attention placed on the security of devices and the data transferred. IoT-driven cyber tools will be a major focus in the efforts to combat cyberattacks which are increasingly common in IoT networks.
Integrations with data analytics and AI have enabled IoT solutions to help businesses improve their processes, boost earnings and reduce overheads, especially valuable during the difficult COVID-19 period. In 2022, we will see more integrated analytics being embedded into devices to decrease the low latency environment and improve performance.
Any sector specific trends?
From a sector perspective, I’ll be keeping an eye on IoT developments in the automotive industry, where solutions are increasingly improving transportation efficiency, creating a superior driving experience and offering advanced vehicle management capabilities. For example, through connected vehicle solutions, owners can remotely control their vehicle from the comfort of their own home. With Voice AI, owners can simply speak aloud to remotely lock or unlock vehicle doors, start or stop the engine and adjust the cabin temperature – to name a few possibilities.
In customer services, IoT technology will continue to increase the power of customer relationship management (CRM) systems – for instance, IoT devices can report problems to the customer desk even before the customer notices them.
We’re also seeing IoT innovation in the education sector where wearables are becoming a game changer. Students can use Virtual Reality (VR) headsets to explore three dimensional views of the human body, providing a more immersive and compelling learning experience. Additionally, wearables are improving student engagement and the quality of teacher-student communication.
Continue reading: https://www.intelligentcio.com/north-america/2021/11/11/how-iot-has-become-a-fully-fledged-reality/

In its analysis of the impact of COVID-19, consultancy McKinsey calculated that digital transformation programmes accelerated by seven years in just a few months to meet customer demand. In turn, this has fuelled growth in IoT. Today, we’re seeing IoT finally come of age as enterprises move from experimentation to understanding how to deploy IoT. Recent Eseye research: ‘The State of IoT Adoption in 2021’ found that the larger the project, the faster the acceleration as organisations embrace IoT.
Security of devices cited as the biggest hurdle to overcome
Our research showed that organisations are reaping multiple benefits by embarking on IoT projects. It includes entering new markets and launching new product lines to disrupt business models and markets. However, while businesses can reap impressive benefits from IoT, adoption is not without its challenges.
Again, in our research, over one-third of our survey respondents (39%) said the security of devices and environments was the biggest hurdle they had to overcome. Meanwhile, 35% said that device onboarding and cellular connectivity had proved difficult.
So why is IoT security so problematic?
For a start, each connected device represents a potential breach point for enterprises. As the number of devices rises exponentially, there is a more complex ecosystem to manage, leading to increased security vulnerabilities.
The first thing to ensure is that the organisation has visibility of these devices. You can’t accurately assess potential dangers to the network until you understand what could be causing it. Many organisations don’t prioritise IoT security. It means they don’t realise the risks until it is too late. Furthermore, the pandemic has made threats more sophisticated and widespread.
Continue reading: https://www.enterprisetimes.co.uk/2021/11/10/why-securing-your-iot-device-has-never-been-more-important/

There is DeFi, GameFi and so many other Fi’s. Yet the elephant in the room is MachineFi. What if machines could be your profit center and economic driver? There is a paradigm shift that I am starting to see in the blockchain and crypto space: the focus on the decentralization of everything and the opportunity of a trillion-dollar machine base economy focused around smart and connected IoT devices.
The internet has changed our lives, yet if you told someone from 1999 that a major share of human interaction would happen online in the next 20 years, they probably wouldn’t believe you. Imagining a blockchain future is a “riddle wrapped in a mystery inside an enigma.” We are in the beginning stages of connecting the pieces of this decentralized digital and physical universe that has arrived.
A few of these baby steps are pretty obvious. For one, an application of blockchain that runs as smoothly as a non-blockchain application is a no-brainer, and we’re already there. Next is an interconnected network of smart devices that act as building blocks for this future. This is what the most exciting projects on the market have been trying to tackle.
And this is where MachineFi comes in.
MachineFi describes the intersection of smart devices and finance (similar to how DeFi is short for decentralized finance). Smart devices are already present everywhere. A decade ago, the idea that your refrigerator would talk to your home security camera would have seemed like a very funny parody, but as it turns out, that’s where we are! Who’s laughing now?
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2021/11/11/machinefi-the-future-of-smart-devices-iot-and-blockchain/?sh=7c7df63d3556

Anyone who’s ever sold their home will know about the mountain of paperwork that’s required to transfer large assets: title deeds, conveyancing reports, legal contracts and so on.
Now imagine what it’s like when you’re selling a commercial aircraft. As well as being much more valuable than the average home – a ten-year-old narrowbody jet might set you back $30 million – these are assets that literally jump around the globe on a daily basis, spinning a web of paper trails in each and every country they’re operated from.
Factor in the staggering amount of maintenance work that’s needed to keep planes airworthy – all of which must be properly documented – and you can see how the business of trading aircraft is a bureaucratic nightmare.
That will always be the case.
But, according to Dublin-based startup BlockAviation, there is at least room to streamline and automate much of the necessary complexity – just as long as the aviation industry is willing to embrace blockchain technology.
“The aircraft is not worth anything without a fully coherent paper trail,” BlockAviation’s chief executive, John Roberts, told me. “So we're building a network to manage all of that.
“We're looking at the actual aircraft itself. And then all the parts that are on that aircraft. And then utilization reporting, which is one of the things that lessees [companies such as airlines that rent aircraft] must do every month. At the moment, lessors [companies that loan out aircraft] are updating their asset management platforms ad hoc [with reports that] come in on email and PDF.
“We can network that and we can keep it on the network.”
BlockAviation has signed up four customers to date – including lessors SMBC and Aircastle – who collectively have 1,200 aircraft under management. That’s about 5% of the global fleet of 25,000 commercial planes.
Leasing companies are an obvious target for the startup as they tend to take delivery of brand new aircraft straight from the manufacturer. These units are placed with a succession of customers across the globe under short-term operating leases. They are typically then sold after about a decade – by which time their value has fallen sharply, but they’re still commercially viable as passenger jets.
Older aircraft also have some residual value – though it’s largely based on the plane’s prospect of being converted for cargo operations, or being scrapped for metal and components.
In all cases, Roberts said that aircraft buyers will demand “massive discounts” if there are “incomplete paper trails, or paper trails which can be questioned”.
That, of course, should never happen.
The industry’s existing regulations and protocols should, in theory, ensure that lessors have all the component, maintenance and airworthiness compliance records they need in order to prove their asset’s true value. In practice, though, collating the necessary documentation is a time-consuming, cumbersome and costly process that requires the cooperation and competence of lessee customers.
A better approach, according to BlockAviation, is giving every aircraft its own “networked record” – a digital logbook that’s remotely accessed and continually updated with all the data needed for a seamless, efficient and fair transfer of ownership.
The only stumbling block is trust: how can buyers be certain that the digitized, networked records are as accurate as the signed, physical hard copies they represent?
Enter blockchain.
Trustworthy notarization
“Blockchain, very simply, is a secure network. And that's what we're using it as,” Roberts explained. “We're using it as a notarization service to notarize these transactions as parts move and aircraft move and records move from place to place.”
Explaining blockchain technology without turning off readers is always a challenge.
In essence, blockchains are strings of data that are being shared by multiple different parties and that are continually cross-checked to ensure that no one party has altered any of their contents. This requires a ledger (a digital book storing all the data); encryption (a process for writing new data into the ledger, without invalidating the old, immutable data); and nodes (different parties who agree to store a copy of the ledger, thereby ensuring it can be cross-checked).
“[Without blockchain] you don't have the possibility to create a networked record,” Roberts continued. “You don't have the ability to create a record that's there; it's networked; it's trusted by everybody; it can be accessed at any time; it can be referred to; and it can be queried, because there's a full audit trail behind it.
“These records don't have any inherent value [by themselves]. It's the concatenation of all the records that has value.”
BlockAviation isn’t the only company trying to convince the industry about the benefits of blockchain technology.
Continue reading: https://www.forbes.com/sites/martinrivers/2021/11/10/how-blockchain-technology-can-revolutionize-commercial-aircraft-trading/?sh=62c37cf16e53

The Department of Homeland Security (DHS) is collecting feedback and opinions regarding the use of artificial intelligence (AI) and facial recognition between now and December 6.
DHS has used and piloted AI-enabled technologies in several functions like customs and border protection, transportation security, and investigations. Earlier this year, DHS launched new shoe-scanning imaging technology, to be deployed at TSA security checkpoints to improve the efficiency of airport screening and potentially eliminate the need to remove shoes and outerwear when passing through checkpoints.
However, AI and facial recognition bring public controversies, such as bias, security, and privacy concerns.
“Understanding how the public perceives these technologies and then designing and deploying them in a manner responsive to the public’s concerns is critical in gaining public support for DHS’s use of these technologies,” an information collection request posted to the Federal Register stated.
Learn more: https://www.meritalk.com/articles/dhs-seeks-public-perception-of-facial-recognition-ai-use/

The demand for artificial intelligence that can help solve real-world problems is only continuing to grow, and consequently, investors are receiving more pitches from startups claiming to be the next big thing.
Global revenue for A.I. is expected to grow 16.5% this year and by 2024, will break the $500 billion mark, according to IDC.
At Fortune Brainstorm A.I. in Boston on Tuesday, Sunil Dhaliwal, founder and general partner of Amplify and Reed Sturtevant, general partner on the investment team at The Engine, shared what they look for when deciding whether to back an A.I. startup. 
For Dhaliwal, the “best companies” have founders who have the technical, academic background and also a deep curiosity about the world and the problem they’re trying to solve.
“Who brings those two things together? That’s what most customers need. They don’t need one of the other. They need both,” Dhaliwal said.
He shared the example of one of his portfolio companies, Covariant, which was started by a team of scientists from Berkeley, and Open A.I., which brought expertise in deep reinforcement learning and robotics.
“[They are] creating systems that allow logistics companies, manufacturers, people in the e-commerce fulfillment business to solve their biggest problems, which are human problems…people need to turn to robotics to solve those problems,” he said.
Sturtevant said he looks to academic research to help identify opportunities. Often times, he said researchers can be so “underwater” that they might not necessarily be at the place where they’ve decided whether to turn their academic work into a company. 
While Dhaliwal said he doesn’t want to be in the position to help guide founders toward the problem they should be solving, Sturtevant said he has helped companies in this area.
Continue reading: https://fortune.com/2021/11/09/ai-investing-in-artificial-intelligence/

Hello and welcome to a special edition of Eye on A.I., recapping insights from Fortune’s Brainstorm A.I. conference, which took place over the past two days in Boston. The second day of the conference yesterday saw some fascinating discussions of everything from the use of A.I. in wealth management to the cutting edge of robotics. Among the highlights was a fireside chat with Lynne Parker, director of the National AI Initiative Office in the White House Office of Science and Technology Policy. Parker said she sees great potential in privacy-preserving machine learning, in part as a way to create larger datasets that might help counter China’s advantage in having access to more data. She also spoke about the need for explainable and transparent A.I. algorithms, especially in “high risk” use cases, like credit and mortgage underwriting or medical diagnoses. Parker’s comment may hint that the U.S. government is considering following the European Union in taking a risk-based approach to A.I. regulation. The EU has proposed categorizing A.I. use cases as high, medium or low risk, with different levels of regulatory compliance required for each category. She said “the right regulation can spur innovation.” One of the overarching themes running through many of the conversations at the conference was the idea that the success or failure of A.I. projects is rarely about the technology and almost always about the culture of the business in which that project is being implemented. “Step back from the tech and bring people along on the journey,” Carol Juel, the chief technology and operating officer at the online bank Synchrony, advised. “A.I. will not solve the problems of any organization.” Jeff McMillan, the chief data analytics and data officer at Morgan Stanley Wealth Management, similarly said that if he could do things over again he would be less of a perfectionist about the A.I. algorithms he was creating and worry much more about how those algorithms fit with the business. “You have to go there based on the business demand and not my A.I. strategy, which nobody cares about,” he said. On the other hand, Julie Sweet, Accenture’s CEO, warned companies “not to confuse necessity with strategic choice.” Many companies had to implement automation, such as chatbots to assist with customer service or new algorithms to deal with pricing decisions, because of the pressures of the COVID-19 pandemic. That, she says, is necessity. But CEOs and boards need to start thinking more strategically about where they can derive the most value from A.I. and not be afraid to think big and move fast. Still many companies stumble in implementing A.I. projects, struggling to move from proof-of-concept projects to full-scale implementations. And there was plenty of discussion at Brainstorm A.I. about how to avoid those pitfalls. Tony Kreager, the vice president of data engineering and data science at FedEx’s Dataworks division talked about the advantage of thinking in short timescales: six days, six weeks, and six months. That is six days to cobble together a bare bones proof of concept that data scientists and machine learning engineers can show to a business unit, six weeks to scale it up and prove that the application can deliver business value, and six months to go to full deployment. But, like many at the conference, Kreager also talked about the importance of being willing to walk away from a project if, after six days or six weeks, it isn't working. At the same time, most of the executives at the conference said they recognize the need to have multi-functional, multi-disciplinary teams working on these A.I. projects from the outset. This can help spot potential challenges, including critical ethical or legal issues, before a company has invested too much time and money in building an application.
Continue reading: https://fortune.com/2021/11/10/successful-a-i-depends-on-people-not-tech/

Your business’s use of AI is only going to increase, and that’s a good thing. Digitalization allows businesses to operate at an atomic level and make millions of decisions each day about a single customer, product, supplier, asset, or transaction. But these decisions cannot be made by humans working in a spreadsheet.
We call these granular, AI-powered decisions “micro-decisions” (borrowed from Taylor and Raden’s “Smart Enough Systems”). They require a complete paradigm shift, a move from making decisions to making “decisions about decisions.” You must manage at a new level of abstraction through rules, parameters, and algorithms. This shift is happening across every industry and across all kinds of decision-making. In this article we propose a framework for how to think about these decisions and how to determine the optimal management model.
Micro-Decisions Require Automation
The nature of micro-decisions requires some level of automation, particularly for real-time and higher-volume decisions. Automation is enabled by algorithms (the rules, predictions, constraints, and logic that determine how a micro-decision is made). And these decision-making algorithms are often described as artificial intelligence (AI). The critical question is, how do human managers manage these types of algorithm-powered systems?
An autonomous system is conceptually very easy. Imagine a driverless car without a steering wheel. The driver simply tells the car where to go and hopes for the best. But the moment there’s a steering wheel, you have a problem. You must inform the driver when they might want to intervene, how they can intervene, and how much notice you will give them when the need to intervene arises. You must think carefully about the information you will present to the driver to help them make an appropriate intervention.
The same is true for any micro-decision. The moment there is a human involved, you need to think carefully about how to design a decision system that enables the human to have a meaningful interaction with the machine.
The four main management models we developed vary based on the level and nature of the human intervention: We call them HITL, HITLFE, HOTL, HOOTL. It’s important to recognize this is a spectrum, and while we have pulled out the key management models, there are sub-variants based on the split between human and machine, and the level of management abstraction at which the human engages with the system.
Continue reading: https://hbr.org/2021/11/managing-ai-decision-making-tools

The practical application for Unmanned Aerial Vehicles (UAVs), better known as drones, in the agriculture sector has been expanding at a steady rate. Experts predict that drones are going to make the agricultural sector more efficient than ever before. According to a study conducted by Informa Economics and Measure, farmers could save an estimated $1.3 billion annually by using these aerial devices to increase crop yield and reduce input cost. With the improved drone technology, the agriculture business can drastically change and this has been proven by farms that have embraced it. Here’s how drones can change the agriculture business based on facts.
Health Assessment
It is essential to assess crop health in order to control pathogens that may damage your crops. Drones carry devices that scan crops using both visible and near-infrared light. These devices detect the plants that reflect the different amounts of NIR light and green light thus producing multispectral images that indicate their health. Discovering these diseases as soon as possible enables farmers to look for a precise remedy.
David Schmale, a Virginia-based farmer and scientist who runs the Schmale Laboratory at Virginia Tech, uses drones to track down pathogens before they even land. He has managed to capture the airborne fungus of Fusarium graminearum which is a great threat to wheat and corn and can travel hundreds of kilometers. He also uses air sampling whenever he discovers pathogens in a neighboring country.
Crop Monitoring
Vast field assessment is the biggest obstacle in farming as it takes a lot of time and manpower. Drones can remedy this, take stock, and inspect for slow-growing crops among other problems. To produce color contrast images that highlight these problems, drones have sensors that measure wavelengths of light that are absorbed and reflected by crops. The images produced include Normalized Difference Vegetation Index (NDVI). These drone sensors can not only tell apart crops, soil, and forest but also sick plants since they reflect light differently.
To make the monitoring process even more effective, many farmers are in favor of combining drones with the use of heavy machinery. In other words, combines, tractors and other robust farming equipment can still be very useful when assessing crops. One important detail to pay attention to however, is functionality. Besides a smooth running engine, assessing the state of your rubber tracks is also important before going out on the field.
Continue reading: https://trendingnewsbuzz.com/how-drones-can-change-the-agriculture-industry/

5G and edge computing have the potential to change the way businesses operate and the way consumers engage with them. From advances in media and entertainment to improvements in manufacturing and retail, these technologies can help businesses boost efficiency and provide more satisfying customer experiences. The two technologies are still in their early stages of adoption, however, and many businesses may not be sure how best to integrate them into their long-term strategy.
For a recent Fast Company virtual panel, Verizon and Amazon Web Services (AWS) brought together experts to discuss how 5G and edge computing are transforming businesses both large and small. These are the key takeaways.
1. TOGETHER, 5G AND EDGE COMPUTING ARE ENABLING NEW INNOVATIONS.
4G has been the network standard since around 2008. Its higher performance enabled an explosion of new applications, including streaming videos, gaming applications, and disruptive platforms like Uber. The promise of a new network with even higher performance capabilities has been with us for several years, but it’s only recently that 5G has started to become standardized. Now that it’s here, its immense promise can begin to be fully realized. “5G is a transformational technology that offers improvement in a variety of performance metrics, including connectivity, latency, and throughput,” says George Elissaios, general manager and director of product management at AWS.
Edge computing is a type of computing that complements 5G to make services even faster and more reliable. It builds on the flexibility enabled by cloud computing, which has become the norm over the past decade, and works by shifting computing services closer to the people who use them. “Edge computing offers the same powerful computing storage and networking services as the cloud, but in more places and closer to end users,” Elissaios says. Together, 5G and edge computing are enabling a new wave of applications requiring ultra-high data speed, higher reliability, and massive network capacity.
Continue reading: https://www.fastcompany.com/90694668/how-5g-and-edge-computing-are-helping-businesses-thrive

Community colleges are designed to help students acquire new skills to obtain meaningful work. Today, junior colleges are faced with declining revenue, declining enrollment due to the pandemic and the increased demand to prepare and train a skilled workforce for the jobs of the future.
Sometimes educators are slow to react to new, rapidly changing and disruptive technologies. They need to adapt quickly to the changing needs of their communities. For example, rural area colleges might focus on the changing technologies in agriculture. The ability to identify and adapt quickly to the changing needs of their regions is paramount to their success.
Community colleges and high schools are historically very closely linked, and this career pathway is essential to successful workforce placements and outcomes, especially when it comes to STEM programs.
As we continue to feel the effects of Covid-19, it’s a great time to consider updating your strategies to address new technologies. I’m not just saying working at home; the pandemic has caused many people to reconsider their entire career and its future during this time of massive change. Some surveys report up to 25% of workers are looking for career changes. This is particularly true for older workers seeking new opportunities, and this is where community colleges can provide an updated solution.
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One piece of new technology that community colleges should consider is small unmanned aircraft systems (sUAS), which are frequently referred to as drones. New sUAS pilots require training and must pass a Federal Aviation Administration (FAA) certification called Central Federal Register part 107 Remote Pilot Certification. It is a necessary certification for any commercial work done with drones. This certification is just the first step in understanding the use cases for drones in all types of businesses. This disruptive and transformative technology market is projected by Grand View Research to grow to $129.2 billion by 2025.
To help students seek out new opportunities when it comes to drone piloting and other technological programs, community colleges can create partnerships with local businesses. These partnerships will ensure community colleges tailor their training programs to the unique needs of the local workforce. They can also help students find potential employment options after graduation.
Drones are some of the best data-collecting solutions on the market today; they’re used for more than aerial photos and videos. Using photogrammetry software is a core competency sought by many organizations today. Therefore, drone-related data analytics should be considered a key component of drone training. 
In addition, colleges should link drone training with real-world apprenticeships, which can give new pilots insights into the business side of drone management and use. Alternately, providing entrepreneurial training can help these students prepare to operate a small business. This can include basic accounting, proposal writing and how to manage a startup business.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2021/11/10/why-community-colleges-should-consider-investing-in-drone-certification-programs/?sh=1bb348c26ece

Many people are looking for drone registration statistics. While the Part 47 registration database is publicly available, the Part 48 registration database is not. The vast majority of drones register under Part 48. The FAA has released Part 48 drone registration data in pieces. They haven’t ever bundled it all together to see what is going on overtime. You have to search around and find snippets.
When you piece it all together, you’ll start noticing interesting things. I compiled this graph-based upon FAA sources around the net. A news article, PDF, announcement, etc. would provide the numbers. I just compiled them all with the date.
TOTAL DRONE REGISTRATION NUMBERS ARE FALLING
Everyone has been hyping drones and saying things are growing, etc.  The total registrations are actually descending.
You’ll also notice the timing of the numbers is interesting. AFTER the remote ID rule came out, drone registrations dropped by more than 50% which leads to the conclusion that FAA was not reporting the numbers honestly.
Continue reading: https://www.suasnews.com/2021/11/american-drone-registration-decline/

Federal researchers are hoping that a cheap, 21-pound glider with stubby wings will help them solve a daunting climate challenge: How to thoroughly explore the Earth’s upper atmosphere.
The stratosphere, which begins between 26,000 and 47,000 feet above Earth, depending on whether you’re at the poles or the equator, is home to the ozone layer, which protects people from harmful sun rays and is vulnerable to pollutants.
Major emissions of climate-warming greenhouse gases collect in the stratosphere, but at the moment it remains one of the least examined layers of the atmosphere. Weather balloons — the traditional tool for exploring the upper gases enveloping the planet — can get up there. They carry a packet of instruments that can measure the weather and identify, or even capture, samples of pollutants.
But that’s where the trouble begins, according to Colm Sweeney, who’s investigating the problem for NOAA.
Weather balloons deploy parachutes carrying instruments and their data, packed in a Styrofoam container. The parachute drops into the the lower atmosphere where it is often driven off course by high winds. They can often be sent into thick forest or sometimes the ocean.
“Then we have to go out and find it,” explained Sweeney in an interview.
Because the parachutes and their data are frequently lost, NOAA has refrained from using more expensive instruments in the stratosphere and has been reluctant to increase the number of ultra-high flights using balloons. At the same time, improved computer models require more data from the stratosphere to track the rise of global warming.
“We’ve been trying to find people to fix this for at least a decade,” Sweeney noted.
Three years ago, he called one of his former college professors, who suggested that Sweeney consult the professor’s son, who teaches a course in aeronautical design at Arizona State University.
The teacher, Timothy Takahashi, and one of his graduate students came up with the design of a smart, automated glider to carry the cargo. After being dropped from the balloon in very thin air, the glider’s wings help it gather speed so it can steer its way through high winds and return to its launch location.
That was the birth of HORUS, which stands for High-altitude Operational Return Unmanned System. The drone found a sweet spot in the often hyper-expensive economics of stratospheric exploration.
The prototypes of HORUS developed at Arizona University were cheap, made from fiberglass and foam. While the idea of a space glider seemed like an oxymoron to many people, Sweeney thought it might be built for less than $2,000.
“If you paid for an airplane to go up to 40,000 feet, it’s unlikely that you’re going to do that for less than $10,000,” he said.
Continue reading: https://www.eenews.net/articles/near-space-drones-search-atmosphere-for-climate-answers/

The persistent gender and diversity gap in technology has been widely known, discussed and worked on for years, yet we remain far from closing it. This is despite a growing body of research showing that diverse teams increase financial results, innovation and job satisfaction. The problem is systemic and daunting, and since the pandemic, it has become appreciably worse.
When I founded my company 21 years ago with three male partners, I was often one of just a handful of women or diverse people in the room. While this is no longer the case, women still make up only 15%-20% of the tech workforce in British Columbia where my company is based, and 30% nationwide, according to recent data. In two concerning findings from a 2021 Canadian study on women in the tech sector, 41% of women in tech roles said their careers had been negatively impacted by the pandemic, compared to just 29% of women in non-tech roles. Adding to this, 44% believed that tech employers don’t really want to hire women. It’s a devastating finding that speaks to far deeper issues than the overly simplistic “pipeline problem” that is regularly cited as the root cause.
The reality is that women and people of color who work in technology are still incredibly impacted by bias in recruiting methods, insufficiently supportive workplace cultures and HR policies, a deficit of representative mentorship and equal access to education. The lack of representation will only improve when tech companies, including small ones like mine, assume responsibility for their roles in perpetuating the status quo, get curious about the structural and systemic roots of the problem and commit to implementing practical solutions. Now, let’s examine how to start implementing beneficial changes, whether you’re a five-person startup or a 500-strong tech company.
First, get curious about the problem.
For decades we’ve heard that the gender gap in technology is a pipeline problem, but the pandemic has blown up the simplicity of this explanation for all to see. From the wealth gap contributing to unequal educational access to gatekeeping caused by restrictive credential requirements, gender bias in recruitment practices to unsupportive schedules and unhealthy workplace cultures, there are many factors blocking women’s entry, advancement and retention in tech. Take responsibility for learning about the diversity of issues.
Assume accountability for your own workplace culture.
Ensure inclusivity is reflected in your values and incorporate education around unconscious bias, inclusion and intersectionality in respectful workplace training. Articulate clearly that diversity is a priority in your organization and, together as a company, that you will be taking steps to nurture an inclusive culture. Then follow through on it. Don’t over-explain. Don’t justify your motives. Just get to work.
Look inward for opportunities to improve.
Unpack HR, hiring and salary data, and critically examine it. Does it align with your diversity values? Are hiring salaries, pay increases, performance bonus formulas, vacation allotments equitable? Does the team have equitable access to educational, career development or promotion opportunities? Level your home playing field by addressing historical or lingering inequities, and set targets for improvement and transparently report on your progress.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2021/11/10/small-companies-can-help-close-techs-gender-gap---heres-how-to-start/?sh=77db43e6572f