In the few minutes that you are reading this article, I will tell you about a completely new type of artificial intelligence, I will name the design features and advantages, I will outline the immediate prospects and possible long-term consequences of the introduction of this technology into real life. Together we will touch the future.
This article is the fourth in a series on the nature of human intelligence and the future of artificial intelligence systems. In the previous article, “The secret of human intelligence,” we found out that human intelligence can work as a classical binary system-symbiosis, functioning due to the structural features of transmembrane proteins in ion channels of brain synapses.
At first glance, it might seem that this new and generally extraordinary neurophysiological concept is of interest only to doctors and biologists. But in fact, this idea from the world of neurophysiology opens the opportunity for us to create a very unusual artificial intelligence.
A new type of AI: technological symbiosis against traditional electronic systems
The existing systems of artificial intelligence, with all their features, have one thing in common: they are all built as single vertically controlled electronic complexes that operate using algorithms of varying complexity. Centralized control is an irresistible property of any man-made electronic computing system. We simply do not know how to build otherwise.
Continue reading: https://bdtechtalks.com/2022/01/04/individual-artificial-intelligence/

Many of today’s hottest technologies come at us as buzzwords.

Artificial intelligence (AI). Machine learning (ML). Edge computing. Internet of Things (IoT). These and many other innovations promise business advancements. Business leaders have an idea what these technologies can offer—but not always why and how to deploy them to deliver maximum return on investment. This, coupled with the meteoric rise of software companies that often star in media articles, means the power of data is still underestimated. We don’t think enough about data.

In reality, data fuels all modern technologies. It’s behind every fashionable trend, solution, and buzzword. Without data, there are few insights and innovations. Without data, there is little profit to be made.
An Overlooked Currency
Some estimates project that individuals create 1.7 megabytes of data every second . The amount of data that proceeds from enterprise businesses is much greater, and—thanks to technologies such as AI, ML, IoT, and edge computing—it’s exploding.
According to Rethink Data, a report commissioned by Seagate and conducted by the research firm IDC, in 2021 alone, the volume of enterprise data grew at an average annual rate of 42%. IDC expects the amount of data around the globe to reach 179 zettabytes by 2025.
When smartly deployed, data can be a game-changing business currency—in some cases literally, given the rise of cryptocurrencies and blockchains. As Google’s Director of Research Peter Norvig famously sums it up, “We don’t have better algorithms. We just have more data.” And yet, as the enabler of business value, data is too often overlooked.
For enterprises, the ability to easily migrate data between companies’ on-premises and cloud environments is more important than ever. However, without a savvy data strategy, massive amounts of data go unused‚ representing wasted business opportunities. In fact, 68% of data available to enterprises goes unleveraged.
Continue reading: https://www.cio.com/article/302119/every-buzzword-was-born-of-data.html

This week on the IoT For All Podcast, Pratexo CEO Blaine Mathieu joins us to share everything companies should know about edge computing and how it complements IoT. Blaine shares some of the most transformative and unique use cases he’s seen edge computing enable, including windmills that automatically slow to prevent collisions with birds.
Blaine also shares his thoughts on what companies should consider before deciding to implement edge computing into their solutions – when it might be most beneficial, especially in environments where connectivity is difficult or unstable, and what some of the biggest benefits companies can expect. Blaine also shares his thoughts on distributed computing and swarm computing, how they work, and in what use cases the technology really shines.
Source article: https://www.iotforall.com/podcasts/edge-computing-benefits-and-considerations

The Internet of Things (IoT) represents the network of physical objects or “things” that are implanted with software, sensors, and technologies to connect and exchange data with other systems and devices over the internet. Today, there are billions of connected IoT devices ranging from consumer or home appliances to complex industrial IoT devices.  
A recent Microsoft research report anticipates that the global workforce will be accommodating 149 million new technology-related jobs by 2025. A significant component of this estimate is the contribution from Information Technology and its allied disciplines.
McKinsey predicts that the number of IoT-connected devices will reach 43 billion by 2023, creating huge demand for the skilled workforce on IoT and allied domains, thus increasing the job opportunities in this space.
Importantly, the salary of IoT professionals will be higher than generic IT professionals with opportunities in different domains like automotive industry, agriculture, domestic safety applications, telecommunication, power management, blockchain tec... Continue reading: https://www.deccanherald.com/supplements/dh-education/a-year-that-defied-comprehension-1065254.html

Tami Mazel Shachar is the CEO of Incredibuild, a development tool that distributes processes across idle processors in the network on-prem and dynamically allocates cloud capacity based on availability and cost. She has previously worked in the Knesset, as well as for 3M and NSO Group, in a sprawling career trajectory that is more than 20 years in the making. Last year, Incredibuild received an investment of $140 million from ScaleUp investor Insight Partners; they hired more than 100 employees in 2021.
As you look at the modern tech industry, how do you view its progress in terms of integrating women into executive roles?
“In terms of data, we’re from where we should be: in terms of female CEOs, the number is really marginal. If I look at the portfolio for all of the great VC funds that have great companies, at the end of the day women CEOs are a very small number - but they’re there, and it’s a growing number.”
What would you say is the primary barrier in increasing that number?
“One of the primary barriers is [role] modeling. When you grow up and you’re in school and you look at the moms and everybody around you, you don’t see a lot of women in very high positions; and you can’t be what you can’t see. As women in high positions, we have a responsibility to go and to be in places where that modeling isn’t present: to go to schools and to villages, and kind of give that visibility, and say “this is an opportunity, and this exists.”
Continue reading: https://www.jpost.com/business-and-innovation/tech/article-691367

1.Introduction
The year 2020 brought into the mainstream consciousness an important concern about Bitcoin (BTC): energy consumption. This led to some questions about the need for sustainable, green energy within the cryptocurrency industry, and the community responded to those concerns, making sustainability a priority. With humanity facing the threat of climate change, the most serious problem for our planet, the trend toward more green solutions must remain in the coming year and decades.
Another important trend that will definitely remain in the coming years is the Metaverse. Building a digitalized dimension where users can buy, sell, play, interact and more looks futuristic enough already, but the future is quickly approaching. I am certain many brands will enter the Metaverse space this year, experimenting with this emerging sector. Let’s just not make it a centralized hell — rather, let’s create a decentralized heaven. 
But that’s just my opinion. To gain more insight on the matter, I reached out to different experts from the crypto and blockchain industry, asking them: “What lies ahead for crypto and blockchain in 2022? What are your personal expectations for the year?”
Continue reading: https://cointelegraph.com/explained/whats-ahead-for-crypto-and-blockchain-in-2022-experts-answer-part-3

During the past couple of years, blockchain technology has become easier to implement for even small- and medium-size participants, thanks to large suppliers like IBM providing specific application-based blockchain technology (IBM Food Trust) and Amazon Web Services providing backbone networking architectures. In addition, smaller blockchain providers now have dedicated applications that can trace food not only to the farm and field in which it originated, but the very seed as well, while also providing complete supply chain visibility for all participants, including consumers.
You might consider blockchain’s “early days” to be about five years ago—when Walmart and IBM were first researching the viability of using blockchain in the food industry. Back then, large programming efforts were typically necessary to create a functional blockchain. Today, blockchain applications are becoming almost as easy to use as email.
In this article, we look at blockchain development and survey its practicality for processors—even small and medium-sized food and beverage companies. 
Blockchain highs and lows
You’ve no doubt heard that blockchain functionality can be used to secure supply chain operations and provide an immutable record of all activities from farm to fork, making the technology so highly practical for track and trace that FDA has been looking into its application for food safety. In addition, blockchain technologies can discourage theft and product tampering, as well as manage the tracking of lower-cost perishable food and high-end products like rare specialty wines.
Continue reading: https://www.foodengineeringmag.com/articles/99942-blockchain-technology-is-it-ready-for-prime-time

As the civil service continues to tackle coronavirus – launching new services, transforming existing ones, and using data to understand this huge and novel threat – machine learning (ML) technologies could prove invaluable. But first, we humans must learn how to avoid the risks inherent in these machines.
Deployed intelligently, ML could dramatically improve the efficiency of civil service business processes, the quality of decision-making, and the government’s ability to tackle threats such as COVID-19. And in an era of rapid, disruptive change and fast-rising public expectations, it’s more important than ever that public services meet citizens’ needs. Poorly designed ML systems could lead to discriminatory outcomes, weaken case management and regulatory frameworks, infringe on citizens’ data rights, and undermine accountability and transparency. So civil servants are – rightly – proceeding with caution: the keys to progress lie in understanding the technology’s characteristics, then creating the frameworks and selecting the applications that will realize ML’s potential whilst addressing its weaknesses.
In essence, ML systems comprise algorithms that, supplied with large datasets, ‘learn’ how to perform a set task by identifying patterns, connections and common indicators. And there are many applications within the government’s work to address COVID-19. By combing through data on coronavirus test results, population mobility data from smartphones and social media feeds, for example, they could forecast where new outbreaks of the virus are likely to appear. And by examining government records on benefits claims, company liquidations, economic stimulus applications and VAT returns, they could identify the regions and industries suffering the greatest economic impact – informing the design and targeting of business support programs.
Continue reading: https://www.civilserviceworld.com/professions/article/artificial-intelligence-without-digital-discrimination

The age of artificial intelligence (AI) is here. Despite being around since the early 50s, AI is finally maturing from an interesting piece of technology to one that is delivering significant, tangible benefits in numerous market segments and across many different businesses. From self-driving cars to website chatbots and intelligent robots in factories, AI is here to stay.
Yet, things have been more slow-moving in the enterprise back-office. We are seeing AI introduced in areas such as invoice processing and loan approval, but only as an optional extra to enhance parts of the existing process. To achieve the same levels of benefit as other AI-enabled areas, we need to think bigger and start solving real business problems, not just making existing processes go faster. But to do that, we need to first look at what AI is not.
The AI Silver Bullet
Many people see AI as a silver bullet — a single shot to solve a single, big problem. But the reality is that businesses do not have one single problem they want to solve; they typically have a series of big issues, each of which can be broken down into a further series of smaller challenges. Early AI deployments failed to deal with this nuance. AI software was complex to use, and each AI model took considerable time and effort to build. With so much effort required to solve one problem, what chance did the business have of solving more?
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/03/ai-apps-and-platforms-get-real/?sh=4e8accd6c519

Is the AI hype justified? It depends on who you ask. Artificial intelligence (AI) is populating different areas of the Gartner hype cycle. Chatbots? Disillusion. Machine learning? Great, but expectations have been lowered a bit. Responsible AI? Could be the next big thing! Understanding AI is hard because it is not one thing, and the technology has many use cases. In this article, I’ll provide a simpler way to understand AI (a bit): Understand the AI market.
The basics of AI have been promoted widely by consultancy firms like PwC and McKinsey & Company: AI has the potential to add trillions of dollars to the world economy in the next decade, although the impact depends on policymakers and the associated market dynamics. That impact will not impact regions easily, as China (potential 26% boost in GDP by 2030) and the U.S. (14.5% boost in GDP by 2030) will see more gains than other areas, like, for example, the EU (10% boost in GDP in the same time frame).
Specific use cases also see more benefits than others, with the big chunks going to customer-centric topline activities such as customer service, recommender systems, pricing, ads and lead generation. A second high-impact area is value chain optimization, with use cases in predictive maintenance, yield optimization, smarter logistics and inventory optimization.
Continue reading: 
https://www.forbes.com/sites/forbestechcouncil/2022/01/04/understanding-the-ai-market/?sh=426aa2552202

Privacy is the number one most important technology, topic, or space for marketing in 2022, according to almost 500 CMOs and other marketing leaders. Also significant: AI, the power of story and content in video and audio, metaverse technologies like VR and AR, web3 technologies like crypto and blockchain, and environmental, social, and corporate responsibility.
Plus the continued evolution of marketing fortresses like Facebook, Reddit, TikTok, Google, and Twitter.

I recently asked 463 marketing technologists: what are the most important technologies or topics for 2022. The result was an avalanche of insight including 616 distinct predictions which I’ve synthesized into seven main themes for marketing technology. (Full disclosure: this was for a consulting client, Singular.) Together they outline major storylines, opportunities, and potential pitfalls for brands in the coming year.
Seven predictions for marketing technology in 2022:

1. Privacy
2. Story (video/audio)
3. AI
4. Metaverse
5. Web3
6. ESG
7. Marketing fortress
   [/LIST=1]
   Continue reading: https://www.forbes.com/sites/johnkoetsier/2022/01/03/7-predictions-for-marketing-technology-in-2022/?sh=49e355678d55

There has been a considerable struggle of acceptance for lesbians, gays, bisexuals, transgender, queer, intersex, asexual (LGBTQIA), and other marginalized genders. Even when there is acceptance in the workplace or at home, LGBTQIA individuals don't feel welcomed. The judgmental eyes in their surroundings are always hovering around them.
The technology world has been growing in influence across sectors but is it ensuring gender equality? A critical step for driving equality across all genders in companies is that LGBTQIA individuals should feel comfortable coming out openly about their gender identity and sexual orientation. Along these lines, seeing role models in the technology sector, especially in a cutting field like Artificial Intelligence, builds the comfort level.
I am sharing stories of 10 LGBTQIA technology executives who took the bold step of openly announcing their gender identity and sexual orientation, hence unblocking the coming-out arterial path for their fellow community members. But more than their names or stature, their stories of resilience, self-discovery, and victory over fear stand out. My spirit in summarizing these stories is to inspire others to feel comfortable about their gender and sexuality, first within themselves and then in front of society.
Tim Cook
In 2014, Tim Cook, CEO of Apple, became the first leader of a major company to come out as gay. In an editorial for Bloomberg Business, Tim publicly came out, saying, "I'm proud to be gay, and I consider being gay among the greatest gifts God has given me."
Tim said he was receiving emails and letters from children who had been ostracized or bullied because of their identity. Tim, a reserved person, realized that he was selfish by concealing his identity. So he finally decided to leverage his executive status to help the cause of children facing abuse due to gender identity.
Gigi Chao
Gigi is the Executive Vice-Chairman of Cheuk Nang Holdings Limited in Hong Kong and the lesbian daughter of a billionaire named Cecil Chao Sze-Tsung.
Continue reading: https://www.forbes.com/sites/taarinikaurdang/2021/12/30/10-inspiring-lgbtqia-technology-executives-and-their-stories/?sh=46317e68392d

Artificial intelligence (AI) is quickly changing the world. As an emerging area of study, it has already found many applications in business, technology and society.
AI is the idea that machines can mimic human intelligence to perform tasks like image recognition or natural language processing. AI refers to any time a machine mimics human behavior or processes to complete complex tasks that are normally done by people.
Why companies are investing in AI and what's next
Companies are investing in AI because they know that it will help them diversify their income sources and make them more competitive in the workplace. It can help with tasks such as analyzing data sets, providing research to back up a hypothesis, creating conversational interfaces and many other things. It is becoming an essential part of the modern workplace.
There are many theories about what might happen as artificial intelligence improves. One theory suggests that we will create a world where we no longer need to work and can spend all our time exploring and living life to its fullest while AI takes care of everything for us. 
How to implement AI in your business
It is possible to use AI in your business, whether it be for marketing, automation or data analytics.
The first step is understanding what kind of work can benefit from AI. This includes tasks like content generation and writing, customer service, marketing automation and lead matching. The next step is understanding the value of each task before implementing any changes. What follows is the implementation process which involves three steps: data unification, model training and model implementation.
The future of artificial intelligence in our everyday life includes some challenges that may arise as well as some potential solutions.
Continue reading: https://www.entrepreneur.com/article/398924

More organizations are turning their eyes to edge computing as cloud adoption reaches new heights. Experts predict there will be 55 billion edge devices by 2022 as latency and resilience demands grow and 5G makes these networks possible. While this growth is impressive, it raises several security concerns.
Edge computing expands attack surfaces, and data centers lack the resources of traditional cloud infrastructure. If security approaches don’t shift to meet these new challenges, the edge may bring more risks than value.
Here are six ways companies can improve their security as companies prepare to expand their edge environments in 2022.
1. Zero-Trust Architecture
Another way edge environments can ensure security by design is to embrace a zero-trust approach. While many think of zero trust as a method of restricting user access, it applies to devices, too. Each edge device should only have access to what it absolutely needs, and even then, authenticate its identity before access.
Edge environments are too complex and full of endpoints to trust any network request. Implementing zero-trust security will ensure one endpoint doesn’t jeopardize the rest of the network. Zero-trust architecture also works well with SASE, as SASE provides the context necessary for situational authorization.
2. SASE
One of the most important security upgrades is secure access service edge (SASE) architecture. SASE brings wide-area networking (WAN) and network security services into a single cloud solution. This convergence gives organizations more transparency and control over their operations, which is essential for edge security.
Monitoring edge networks can be challenging given their distributed, endpoint-heavy nature. SASE makes it easier to look into and control these networks by reducing complexity and automating background security tasks. As IT sprawl rises and edge environments become increasingly complex, that benefit will become difficult to overlook.
Fewer than 1% of organizations had SASE strategies as of 2018, but Gartner predicts that figure to rise to 40% by 2024. As edge computing becomes more common, it may have to grow faster still.
3. Distributed Resiliency
Part of reliable cybersecurity is ensuring a network can continue functioning when a disruption occurs. Traditional data centers can ensure this resiliency through redundant on-premises infrastructure, but this isn’t an option for edge computing. That’s why nine out of 10 edge data center owners say that network-based distributed resiliency will become common in the next few years.
Distributed resiliency involves replicating data across multiple sites. That way, if one edge data center experiences disruption, the network can shift the workload to another center or across several. This setup lets these facilities mitigate disruptions and downtime without increasing their physical infrastructure.
Continue reading: https://www.tripwire.com/state-of-security/security-data-protection/cloud/improving-edge-computing-security/

AgWeb talks with a futurist and former naval intelligence officer about what he sees impacting agriculture in the new year.
As we prepare to ring in a new year, what trends will shape 2022? Sara Schafer at AgWeb talked with Jack Uldrich, a futurist and former naval intelligence officer, about what he sees impacting agriculture in the new year. He said there are four trends:
1. Blockchain technology
“What it allows businesses to do is have a secure, trustworthy and transparent view of the supply chain. With blockchain, in the not-too-distant future, both consumers and businesses are going to know exactly where their crops came from, how they were grown, how they were shipped, how they were stored, etc.,” Uldrich says.
It will also enable companies such as Cargill, PepsiCo, General Mills and their customers to hold farmers accountable for production practices and resource use.
2. Regenerative Agriculture
Big food companies are betting on regenerative agriculture to thwart climate change which is paying farmers to sequester carbon by adopting conservation practices.
“We’re seeing European governments be more aggressive on requiring agribusinesses and farmers to get more serious about regenerative agriculture, and the Biden administration will likely provide financial incentives for farmers to store carbon in their land. This is a huge opportunity for farmers; it’s not too soon for every farmer to begin getting up to speed on this issue.”
Continue reading: https://www.precisionfarmingdealer.com/articles/4886-4-trends-that-will-shape-agriculture-in-2022

As we look forward to 2022, it’s time to reflect on the drone industry 2021.  Despite chip shortages, new regulations, an ongoing global pandemic, and the challenges inherent in a growth sector, the drone industry came out on top in 2021.  We asked our sponsors and partners to describe the drone industry 2021 in a word (or two) – and here’s what they said.
Brett Kanda, drone industry veteran and VP of Sales and Marketing at BRINC Drones, makers of drone solutions for law enforcement and first responders, says the industry is shifting.
“2021 was an inflection point in our industry. We saw the 90% market share lion in DJI start to lose some momentum and most importantly, key executives and personnel in North America. This has created an opportunity for other manufacturers to build differentiated solutions that can compete with DJI in the very near future. We also started to see the landscape change in terms of end user sentiment. The need for tailored solutions that solve niche problems were on the rise. No matter the vertical, the end user is becoming more educated and comfortable with robotics and autonomous systems. What we as an industry have been seeing and feeling for years is starting to bleed over to the end users in terms of ROI, value proposition, and capabilities for autonomous systems.”
Booming
 
For BVLOS Fixed Wing providers Censys, the advance of regulations for flight beyond visual line of sight (BVLOS) has led to a lot of activity.  Waivers are increasing, and customers are seeing the opportunity to take advantage of using unmanned systems in the field.
“We have seen an incredible increase of companies looking to start utilizing UAS in day-to-day operations and companies currently with UAS advancing their operations,” says Kyle Miller, Director of Business Development for Censys.  “The number of BVLOS approvals we won in 2021 and drones we have sold are a testament to the booming industry.”
Coiled – Like a Snake!
Commercial UAV‘s Carl Berendtson always has the mot juste – and has a unique bird’s eye view of the drone sector, with the biggest rolodex in the industry.  Despite the ongoing pandemic, Commercial UAV Expo put on a great show in Vegas this year, and is getting ready for the future – when flight beyond visual line of sight will help drive even more industry growth.
“I would say “coiled” like a rattlesnake,” says Berendtson.  “Held back by external forces, but building momentum none the less, beneath the waves. BVLOS will be the catalyst to release the hounds.”
Continue reading: https://dronelife.com/2021/12/30/drone-industry-2021-in-a-word-we-asked-our-partners-to-describe-this-year-in-drones/

2021 was an eventful year for AI. With the advent of new techniques, robust systems that can understand the relationships not only between words but words and photos, videos, and audio became possible. At the same time, policymakers — growing increasingly wary of AI’s potential harm — proposed rules aimed at mitigating the worst of AI’s effects, including discrimination.
Meanwhile, AI research labs — while signaling their adherence to “responsible AI” — rushed to commercialize their work, either under pressure from corporate parents or investors. But in a bright spot, organizations ranging from the U.S. National Institutes of Standards and Technology (NIST) to the United Nations released guidelines laying the groundwork for more explainable AI, emphasizing the need to move away from “black-box” systems in favor of those whose reasoning is transparent.
As for what 2022 might hold, the renewed focus on data engineering — designing the datasets used to train, test, and benchmark AI systems — that emerged in 2021 seems poised to remain strong. Innovations in AI accelerator hardware are another shoo-in for the year to come, as is a climb in the uptake of AI in the enterprise.
Looking back at 2021
Multimodal models
In January, OpenAI released DALL-E and CLIP, two multimodal models that the research lab claims are “a step toward systems with [a] deeper understanding of the world.” Its name, inspired by Salvador Dalí, DALL-E was trained to generate images from simple text descriptions, while CLIP (for “Contrastive Language-Image Pre-training”) was taught to associate visual concepts with language.
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DALL-E and CLIP turned out to be the first in a series of increasingly capable multimodal models in 2021. Beyond reach a few years ago, multimodal models are now being deployed in production environments, improving everything from hate speech detection to search relevancy.
Google in June introduced MUM, a multimodal model trained on a dataset of documents from the web that can transfer knowledge between different languages. MUM, which doesn’t need to be explicitly taught how to complete a task, is able to answer questions in 75 languages, including “I want to hike to Mount Fuji next fall — what should I do to prepare?” while realizing that “prepare” could encompass things like fitness as well as weather.
Not to be outdone, Nvidia recently released GauGAN2, the successor to its GauGAN model, which lets users create lifelike landscape images that don’t actually exist. Combining techniques like segmentation mapping, inpainting, and text-to-image generation, GauGAN2 can create photorealistic art from a mix of words and drawings.
Continue reading: https://venturebeat.com/2021/12/30/a-look-back-at-recent-ai-trends-and-what-2022-might-hold/

Artificial intelligence (AI) and machine learning (ML) are here to stay. Research shows that the global AI market can reach up to a $190 billion market valuation in 2025. Additionally, in 2022, companies are expected to run around 35 AI projects in their operations.
Because AI and ML are becoming so ubiquitous, enterprises must be aware of the seven trends directly affecting their operations and future moving into 2022. These trends will not only affect the more tangible, business-side of operations, but also point towards more abstract, ethical questions surrounding AI.
Cybersecurity
Cybersecurity concerns are an inevitable consequence of AI’s rise. AI-backed technologies, such as hyperautomation and 5G, all have security implications that only further these concerns. As enterprises process more and more data, they will need to adopt greater cybersecurity vigilance, which will be aided in large part by AIOps.
Cybersecurity companies are also keeping pace with these increasing threat areas and are utilizing AI and ML to help combat malicious attacks. Leaders in this space—including NortonLifeLock, CrowdStrik, and Darktrace—use AI to learn from previous attacks to help prevent any future compromises. Because most of these software solutions are hands-off, they are affordable and scalable — helping to fuel greater adoption of AIOps platforms in coming years. 
Hyperautomation
Hyperautomation is the identification and automation of as many processes as possible. Many of the solutions adopted under hyperautomation, such as Microsoft Power Automate and Laiye RPA, are AI-focused. An example  of the crossroads between hyperautomation and AI is robotic process automation (RPA) tools, which use bots and automate simple, routine processes within various software applications.
There are two advantages hyperautomation and AI can bring for businesses: employee upskilling and business efficiency. This is primarily due to the growth of low-code and no-code solutions adopted under hyperautomation to ensure everyday users have access to more advanced techniques and skills than ever before. 
Continue reading: https://www.enterprisenetworkingplanet.com/management/top-business-ai-trends-2022/

Blockchain, the underlying infrastructure behind cryptocurrencies, is likely among the most transformative technological innovations of our age, with promising use cases for many industries.
In a nutshell, blockchain is an open and censorship-resistant database model, secured by encryption and decentralization. Blockchain records information in blocks on a shared ledger, storing a synchronized copy of it on all the systems participating in the network, hence assuring its immutability.
As companies start recognizing the benefits of this technology, we’ve seen exciting new blockchain developments this past year. Below we’ll take a look at five of the biggest blockchain trends of 2021 and what they might mean for the next year.
Blockchain in supply chain
Blockchain can be a game-changing technology for multiple sectors, especially for the supply chain industry. Increasing globalization has created more complex distribution processes than ever, creating new challenges in supply chain management. Blockchain infrastructure can be applied to create more transparency and automation in supply chain processes on a global scale.
Continue reading: https://forkast.news/top-5-blockchain-trends-with-lasting-impact/

ublic demand for blockchain use cases has exploded in the past year, especially around the adoption of non-fungible tokens (NFTs), cryptocurrency and decentralised finance (DeFi) through enterprise applications. Indeed, Gartner predicts that by 2024, at least 20% of large enterprises will use digital currencies for payment, stored value, or collateral.
With blue chip payment processors such as Visa, Mastercard, PayPal, and Square leading the way and supporting forms of cryptocurrency transactions, enterprises have increasingly taken notice. Many are embracing these new applications as they seek to extract value from new business models and the processes which they enable.
There are, however, risks attributed to the integration of enterprise applications needed for digital currencies – ranging from volatility to a lack of legal protection and regulatory clarity – especially for those more inexperienced organisations. And with enterprises, particularly application leaders, under pressure to embark on the blockchain journey in 2022, businesses must agree on use cases and follow several key processes to ensure success.
Use cases for blockchain in 2022
First, for any organisational adoption of blockchain, the initial step is establishing use cases, often boiling down to three potential applications: stored value, payment, and leverage for high-yield investments available in DeFi. Leaders should next select solutions corresponding to these applications.
Continue reading: https://techmonitor.ai/technology/emerging-technology/how-can-tech-leaders-prepare-for-blockchain-based-digital-disruption-2022

2021 has been a watershed year for blockchain technology, with several new trends prompting a rethink of financial possibilities. Non-fungible tokens (NFTs) in the Metaverse, Exchange-traded funds (ETFs), and Decentralized Autonomous Organizations (DAOs) have become mainstays bringing with them more adoption of crypto. These innovations have seen businesses worldwide adopt blockchain solutions bringing about considerable investments in the space.
Financial payment company TripleA estimates that the total number of crypto users exceeds 300 million. This claim is substantiated by data provided by Chainalysis, which shows that as of Q2 2021,  global adoption was at least 880% higher than 2020.
Growing Adoption Poses Scaling Problems
As more users and investors come into the crypto ecosystem, the problem of scalability poses a challenge. As adoption grows, the need for faster transactions and increased throughput also goes up. However, scaling up in the industry brings up the age-old belief of the blockchain trilemma. 
The blockchain trilemma refers to the widely held notion that decentralized networks can only provide two of three benefits (decentralization, security, and scalability) at a time. The industry is rife with examples of this challenge.
Bitcoin can only transact around seven transactions per second (TPS) with its decentralized and secure system. Ethereum has a throughput not greater than thirty TPS. On the other hand, Enterprise blockchains like Hyperledger’s Fabric are safe and can handle high transactional throughput but are centralized.
FTX CEO Sam Bankman-Fried (SBF) praised the current scaling efforts but pointed out the need for more to be done. He shared his thoughts on Twitter, where he detailed a possible roadmap for the industry in 2022.
Continue reading: https://tokenist.com/just-how-much-has-the-blockchain-industry-scaled-up-in-2021/

Thanks to IoT (Internet of Things), we can now make our homes smart. New sets of IoT devices, which hit the market this year were a cut above their previous versions. Here are the five best IoT devices launched in 2021

Lawfare contributors Ashley Deeks and Russell Spivak discussed, in 2017, the U.S. Court of Appeals for the D.C. Circuit ruling in Taylor v. Huerta that struck down the 2015 Federal Aviation Administration (FAA) interim drone registration rule. Some of the same players involved in that case, including Taylor’s attorneys, Jonathan Rupprecht and Kathleen Yodice, as well as the presiding judge, Robert L. Wilkins, reconvened on Dec. 15 for oral arguments in the case RaceDayQuads (RDQ) v. FAA, challenging the FAA’s remote identification (RID) rule. This post provides an overview of the rule, summarizes the challenges and offers analysis of the arguments as well as thoughts on what might happen going forward. Given that the FAA has made RID a prerequisite for certain operations over people, beyond visual-line-of-sight drone operations and the future unmanned traffic management system, this case has the potential to set the commercial drone industry back years and hamper national security agencies in protecting against rogue drones.
The Rule
The FAA’s stated purpose of the RID rule is to protect airspace safety and national security by requiring all small drones (0.55-55 lbs) in the U.S. to broadcast out a “digital license plate” that is accessible in near real time to the FAA, national security agencies, law enforcement entities, other government officials and the general public.
It took the FAA more than two years to finalize the rule. The process began on New Year’s Eve 2019 when the agency published its initial Notice of Public Rulemaking (NPRM). Despite multiple requests to extend the deadline, the FAA closed out the public comment period on March 2, 2020. Even so, during that 60-day period, the FAA received more than 53,000 comments. Almost a year later, in January 2021, the FAA promulgated the final RID rule (which added a new Subpart C to Part 89 in Title 14 of the Code of Federal Regulations, Remote Identification of Unmanned Aircraft).
Under this rule, a drone will need to broadcast message elements (MEs) over WiFi and/or Bluetooth, including its unique identifier (e.g., a serial number), precise coordinates, geometric altitude, velocity, the control station coordinates or broadcast takeoff location and geometric altitude. In some cases, it will need to broadcast a time mark and an emergency status indication. 
With regard to the range for broadcasting MEs, 14 USC § 310(g)(2) states:

Any broadcasting device used to meet the requirements of this section must be integrated into the unmanned aircraft without modification to its authorized radio frequency parameters and designed to maximize the range at which the broadcast can be received, while complying with 47 CFR part 15 and any other applicable laws in effect as of the date the declaration of compliance is submitted to the FAA for acceptance. (Emphasis added.)

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Utilizing the 1 watt of output power provided for in FCC regulations, 47 CFR 15.247(b)(1), a RID system at +30 dBm (1 watt) on 2.4 GHz would transmit identification information more than 1 mile omnidirectionally. This will enable a wide swath of people, over large distances, to persistently track drones. 
Continue reading: https://www.lawfareblog.com/dc-circuit-may-blow-remote-identification-rule-drones

As new year approaches, crowds around the world may be expecting whizzes and bangs to light up the sky. But the appeal of fireworks could fizzle out with the growing use of drones for light shows.
One notable example was the opening ceremony of this year’s Tokyo Olympics, while the Over the Top NYE event at Reunion Tower in Dallas is among those planning to combine fireworks and drones to welcome 2022.
They are also being embraced at a local level: more than 1,000 people watched a drone display at Mercia Marina in Derbyshire to celebrate Bonfire Night this year.
Ollie Howitt, the creative coordinator at SkyMagic, which used a fleet of 300 drones to create a display for the mayor of London’s new year celebration last year, said demand had increased substantially, something the pandemic has helped accelerate. She added that drones were increasingly able to fly in greater density and for longer.
“We do think it’s going to be something that’s ever evolving, as opposed to it being a short-lived sort of fad that people have suddenly got interested in,” she said.
Robert Neff, a partner and general manager at Mercia Marina, also believes drone displays will become more common. “There’s a big movement against fireworks,” he said.
Neff said the decision to use a drone display at the marina was down to a number of factors, including the impact of fireworks on animals – from wildlife and waterfowl to the cats and dogs of boat owners.
“They’ve often commented on how much distress is caused to their pets by the fireworks,” he said.
Howitt said there were benefits to drones: “They’re no emission, they’re reusable, there’s no fallout or any debris or that kind of thing. So in that sense they are a very good, sustainable option.”
Continue reading: https://www.theguardian.com/uk-news/2021/dec/30/fireworks-could-fizzle-out-drones-rise-popularity-new-year

The internet of things and AI are groundbreaking business technologies on their own, but when they are combined, their benefits are magnified for enterprise users. IoT connects devices together, giving and receiving signals like a nervous system, while AI acts as a brain, receiving data, processing it and using it to make informed decisions that control the overall system.
When joined together, they deliver intelligent, connected systems that can correct and heal themselves as needed — forming the Artificial Intelligence of Things (AIoT).
AIoT Can Automatically Take Actions
To appreciate the capabilities that AIoT can unleash, it is helpful to reflect on the impact IoT has already made on industry. With IoT technologies such as cloud computing and storage, as well as enhanced connectivity and machine-to-machine (M2M) communication, manufacturers have been able to complete three key tasks: connect machines, store data and make it meaningful. Now, as we introduce AIoT, they can benefit from a fourth capability — possessing the ability to act.
Now, manufacturers can be presented with more than just facts. Instead of only learning about how equipment is performing and then having to react with their own decisions on how to act upon those findings, AI is closing the loop by automatically taking actions for users.
However, to make AIoT feasible, manufacturers need a data management system that can support fast decision-making. While cloud storage is a viable option, analyzing data closer to its source — at the edge — will take AIoT to the next level.
Entering the Edge
In many cases of AI integration, activities need to occur locally to act fast. For example, if the AI system receives an alert about a machine fault, the AI system may make the decision to stop the machine to avoid product damage. By integrating the AI system at the edge instead of in the cloud, latency issues can be avoided, meaning the machine is switched off more quickly and fewer products are damaged.
The same is applicable for process optimization activities, such as changing the speed or type of movement by a machine. An AI system at the edge can send instructions to equipment to improve its performance faster than a similar instruction coming from the cloud.
An additional benefit of integrating AI and processing data at the edge is increased security. Cloud computing can present several security issues – through data stored by a third-party provider away from the company’s premises, and the accessibility of that corporate data over the internet. Edge computing can work as a complement to overcome these security concerns by filtering out sensitive information at the source and storing it on-premises, so there is less transfer of confidential material to the cloud.
Another use case where it is advantageous to integrate AIoT at the edge is when visual inspection systems are involved. Cameras and sensors create massive amounts of data, so it is more sensible to analyze and filter this data at the edge, instead of sending it all to an off-site cloud or to a large centralized system.
Continue reading: https://www.enterpriseai.news/2021/12/29/aiot-and-edge-analytics-a-powerful-combination/