Alephium, which is an efferent sharding-based blockchain, has been able to raise $3.6 million in a pre-sale of its tokens to almost 80 separate buyers. Many large investors participated in the offer, and smaller investors also bought tokens in the pre-sale.
The fresh capital will support development at Alephium, which is developing novel Sharded UTXO Blockchain technology.
Alphemy Capital led the pre-sale, and both White Paper Capital and Archery Blockchain participated. The tokens were predominately bought by smaller buyers, with 91% of the buyers contributing less than $100,000.
Cheng Wang, the Co-founder of Alephium, commented

“After over 3 years focused exclusively on research and development, we are proud and humbled by the success of the pre-sale achieved without any marketing or active online presence…It is rewarding to see the interest raised by our technology and we are excited to have this pre-sale kick-off the expansion of the Alephium blockchain and create the grounds for a broader community.”

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Alephium is creating a blockchain that uses sharding technology called BlockFlow. It is based on stateful UTXO transactions.
Continue reading: https://blockonomi.com/alephium-raises-3-6m/

Cryptocurrency may be the star of the blockchain world. But the same qualities that make blockchain useful for currency — security, transparency, decentralization, immutability — also apply to a slew of other uses. We believe that one of the most important changes on the horizon is in healthcare and we’ll tell you why. But first, let’s go over the basics.
Blockchain basics
Blockchain is a shared and distributed ledger system. It is just like keeping a record of transactions on a spreadsheet (centralized), except blockchain does it through a network of peer to peer computers and follows three essential steps.

• Making a record of each transaction or input
• Verifying the transaction to ensure validity
• Once verified, each input or transaction is added to a block that gets hashed (encrypted)

 Afterward, the block is added to the end of the blockchain.
The important thing to know is that a blockchain is a tamper-proof database that can be accessed by many different parties but is not controlled or manipulated by any single party.
Continue reading: https://www.linkedin.com/pulse/blockchain-remake-healthcare-sector-you-ready-kenneth-daniel-tan/?trk=articles_directory

While the Covid-19 pandemic hit the entertainment industry hard, it hit indie artists even harder, especially when it came to them protecting their revenue-dependent consumer fanbase.
When musicians and producers took to social media to keep their careers alive, hosting virtual concerts and regular content drops, it wasn’t long before platforms like Facebook and Spotify began implementing guardrails. This posed a challenge for the many struggling artists out there just needing to stay afloat.
With concerts returning, indie artists have some catching up to do, beginning by leveraging technology like blockchain and crypto to stay ahead. Music-related non-fungible tokens, or NFTs, have proved to be a new way for both the artist and, finally, their fans to connect.
An NFT is an electronic ID that authenticates the existence of a digital asset, usually in the art world, or in this case, a limited edition piece of music or related benefit, not available anywhere else. NFT token contracts are unique such that the owner of the NFT token contract is the owner of the original artwork; NFTs create the virtual scarcity that elevates the value.
Continue reading: https://www.rollingstone.com/culture-council/articles/artists-blockchain-todays-world-1221252/

The confluence of data, compute power and advances in the design of algorithms for AI (artificial intelligence) and ML (machine learning) are driving new approaches in the laboratory. This gives scientists access to additional tools that can open new avenues for research or accelerate existing workflows. 
The increasing interest in AI and ML is driving software companies to examine how they can develop their own software frameworks, or integrate functionality into existing laboratory software to support laboratory scientists’ use of AI.  
Some examples of domain areas that are already seeing benefits of early AI  adoption include predictive maintenance of instruments; predicting efficacy and potential of small molecules for drug discovery; and image analysis for a  variety of different use cases such as crystallography and medical imaging. 
Stephen Hayward, product marketing manager at Biovia, Dassault Systèmes highlights the steps the company has taken to integrate AI functionality into its software:  ‘We have a product called Biovia Pipeline  Pilot, which is all about data science, data preparation, connecting data sources together and performing various functions on it. When we talk about machine learning  and AI, it’s Pipeline Pilot that is core to that.’ 
As the adoption of AI and ML techniques becomes more widespread the techniques are beginning to transform how scientific research is conducted. However, organizations need to ensure their teams are focused on their scientific goals rather than trying to develop expertise in advanced computational methods. While it is true that there should be some staff with a  good understanding of AI and the software frameworks they are using to build these intelligent systems, it is unreasonable to think that specialized domain expert lab scientists should be expected to develop skills in computer science or the development of AI frameworks. 
Continue reading: https://www.scientific-computing.com/feature/ai-revolution

Machine Learning Operations (MLOps) is on the rise as a critical technology to help to scale machine learning in the enterprise. According to McKinsey, by 2030, ML could add up to 13 trillion dollars back into the global economy by enabling workers in all sectors to improve their output. Furthermore, MarketWatch indicates that, in 2021, the global MLOps market size will be USD million and it is expected to reach USD million by the end of 2027, with a CAGR during 2021-2027. According to IBM  by 2023, 70% of AI workloads will use application containers or be built using a server less programming model, necessitating a DevOps culture. What’s more, according to Algorithmia, 85% of machine learning models never make it to production. For businesses, creating machine learning applications, managing those models and putting them into action is challenging. Different companies, such as DataRobot, have emerged as top machine learning operations tool enablers for the industry to handle these challenges. 
Processing, implementing and deploying machine learning models requires specific tools that can solve challenges in the process. The challenge of getting data from aa data to decisions is made more accessible by applying various operations on-device or in the cloud as needed. To do this at scale, businesses need a platform to add support for new ML frameworks through open interfaces. There are several ways to add or remove models and processes.
The leading machine learning operations tools for enterprise are:
Continue reading: https://www.forbes.com/sites/markminevich/2021/09/10/leading-mlops-tools-are-the-next-frontier-of-scaling-ai-in-the-enterprise/?sh=31beaf9263d8

More and more, networking and security teams are realizing that AI has quickly become a serious strategic necessity. But adopting and implementing it can seem like one more enormous challenge in a period that has already delivered many challenges already. In the wake of the pandemic, it is clear that work from home is exploding into work from anywhere — and not just anywhere. Work from anywhere really means work anywhere, at any time and from any device to access any resource in data centers, in the cloud or on networks comprising vast edges of endpoints.
Accommodating work from anywhere is as sprawling as the networks themselves. Organizations are in a constant struggle to see and control who is accessing their network and what actions they are taking. And what they can see is resulting in more tickets and more reports than ever before, even as the economic downturns from Covid-19 have forced them to slash budgets and shrink teams.
Guess who knows about all these challenges? Cybercriminals whose tactics have become household words in the past year. They have taken advantage of the expanded threat surface to increase ransomware attacks tenfold in the last year.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2021/09/10/ai-is-no-longer-optional-and-thats-a-good-thing/?sh=332df2047852

AI is becoming strategic for many companies across the world. The technology can be transformative for just about any part of a business. 
But AI is not easy to implement. Even top-notch companies have challenges and failures.
So what can be done? Well, one strategy is to provide AI education to the workforce. 
“If more people are AI literate and can start to participate and contribute to the process, more problems–both big and small–across the organization can be tackled,” said David Sweenor, who is the Senior Director of Product Marketing at Alteryx. “We call this the ‘Democratization of AI and Analytics.’ A team of 100, 1,000, or 5,000 working on different problems in their areas of expertise certainly will have a bigger impact than if left in the hands of a few.”
Just look at Levi Strauss & Co. Last year the company implemented a full portfolio of enterprise training programs—for all employees at all levels—focused on data and AI for business applications. For example, there is the Machine Learning Bootcamp, which is an eight-week program for learning Python coding, neural networks and machine learning—with an emphasis on real-world scenarios. 
Continue reading: https://www.forbes.com/sites/tomtaulli/2021/09/10/ai-artificial-intelligence-should-you-teach-it-to-your-employees/?sh=598de0587b73

Women are increasingly enrolling in online learning courses and earning STEM certificates during the pandemic, according to the latest Women and Skills Report from Coursera.
Women now make up 52% of new registered users on the e-learning platform in 2021, compared with 47% in 2019. In terms of course enrollments overall, women have nearly reached parity, at 49%, compared with making up just 42% of total enrollment in 2019.
The narrowing gender gap in online learning comes at a time when women have been disproportionately sidelined at work during the coronavirus outbreak. Despite economic recovery in many job market sectors, millions of women remain unemployed or underemployed due to their overrepresentation in in-person service jobs disrupted by Covid-19, as well as ongoing child care challenges over the last 18 months. Unemployment figures also exclude the 1.6 million women who’ve been pushed to drop out of the workforce altogether since February 2020.
But the growing share of women upskilling and reskilling through online learning could be an encouraging sign about the future of women in the workforce, says Betty Vandenbosch, Coursera’s chief content officer.
Continue reading: https://www.cnbc.com/2021/09/09/womens-enrollment-in-online-courses-certificates-rises-during-pandemic.html

In the lead-up to the Women in IT Europe Summit, Leslie Hawthorn, vertical community strategy manager at Red Hat, and Cali Dolfi, data scientist at Red Hat, spoke to Information Age about digital transformation trends in open source, and promoting workplace DEI.
During the upcoming Women in IT Europe summit, taking place on the 14th September 2021 from 10:00am CET, Leslie Hawthorn, vertical community strategy manager, and Cali Dolfi, data scientist, both at event premium sponsor Red Hat, will be delivering a presentation on the topic of ‘Creating Growth with Data Analytics’. The presentation will cover the work that Red Hat is doing to help open source communities use data to empower themselves, and shape their engagement. To register for this virtual event, please click here.
In the lead-up to the summit, Leslie and Cali spoke to Information Age about how open source has prominently facilitated digital transformation, their respective journeys in tech, and the importance of promoting DEI in the workplace.
What have been the most valuable examples of digital transformation initiatives involving open source technologies that you’ve seen over the past 18 months or so?
Cali: One thing that my mind constantly goes towards is the data-powered research being done at hospitals right now, including studies being carried out around Covid-19. The past 18 months have seen the pandemic dominate our lives, so research is being done that’s powered by AI, data science and open source. For example, the Open Data Hub project is creating a blueprint on how to set up AI and data science initiatives, using open source technology.
Continue reading: https://www.information-age.com/wit-summit-europe-qa-digital-transformation-open-source-123496815/

Today’s Woman in Tech: Miriam Bressan, VMware Tanzu
Miriam Bressan is Manager Solution Engineering, Global Accounts in CEMEA and SEMEA at VMware Tanzu.
When did you become interested in technology? What first got you interested in tech?
My fascination started very early. My parents didn’t allow me to have a Gameboy or game consoles. But there was an old Atari with an unbelievable amount of floppy disks that nobody really needed anymore. The manual wouldn’t have been able to help me, because it was in English, so: Learning by doing
When I was 18, I saved up for my first real PC, which I built myself. Fun fact: The motherboard, drive, and card reader are still in my tower Back then they thought BlueRays would be the absolute hit and now I’m looked at incredulously when I say I can burn BlueRays.
I studied computer science – “media and communication informatics” to be exact – and wanted to become either a game developer or a penetration tester. Somehow it turned out differently…
Continue reading: https://jaxenter.com/women-in-tech-bressan-175445.html

Mastercard has agreed to acquire blockchain analytics start-up CipherTrace, in the latest sign of how major companies are warming to cryptocurrencies.
The payments giant said Thursday it entered into an agreement to buy CipherTrace for an undisclosed amount. Based in Menlo Park, California, CipherTrace develops tools that help businesses and law enforcement root out illicit digital currency transactions. The company’s competitors include New York-based Chainalysis and London start-up Elliptic.
“Digital assets have the potential to reimagine commerce, from everyday acts like paying and getting paid to transforming economies, making them more inclusive and efficient,” Ajay Bhalla, president of cyber and intelligence at Mastercard, said in a statement. “With the rapid growth of the digital asset ecosystem comes the need to ensure it is trusted and safe.”
Financial terms of the deal were not disclosed. Mastercard shares were up about 0.6% Thursday morning in New York.
Continue reading: https://www.cnbc.com/2021/09/09/mastercard-to-buy-blockchain-analytics-start-up-ciphertrace.html

The crypto world is known for its volatility, and hard forks—blockchain updates with security patches or other changes in the code—reinforce this perceived lack of stability. With updates like the recent Ethereum London hard fork, resistors are left behind on an obsolete, outdated fork. In perhaps the most famous example of a hard fork, Bitcoin Cash, the adopters didn’t quite steal the show. The split still, however, followed a series of debates within the Bitcoin community, with tensions still high today. 
A better solution is needed to keep communities united while still allowing for blockchains to be updated. One major feature setting Polkadot’s “Layer 0” blockchain apart from others is its choice to be forkless, meaning there’s no need to create a fork in order to update the blockchain. As the crypto community continues to expand, a forkless future is the only way forward.
Blockchain is a decentralized system with anonymity. Therefore, it’s difficult to coordinate updates that will be agreed upon by the whole community, especially when it’s not always clear who is running the software. While blockchain upgrades are necessary for technological innovation, they lead to tensions within their respective communities, with endless debates on the necessity and timing of specific improvements. 
Continue reading: https://www.nasdaq.com/articles/no-more-forks%3A-a-case-for-the-polkadot-approach-to-blockchain-upgrades-2021-09-09

Many companies need strong supply chain traceability.  For the most prevalent tracing challenges, blockchain may provide a formidable solution.
Real-World Applications
Using blockchain to trace products is especially promising for certain industries, including the food, fashion and regulated products industries.
Food Industry
Supply chain traceability is crucial in many industries, but arguably none more so than the food industry, where concerns about contamination, intentional adulteration, and bioterrorism are ever-present.
The most promising applications in the food industry involve conducting product recalls and ensuring consumer satisfaction for perishable products.

1. Food Recalls and Market Withdrawals
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   Some of the keys to successfully stopping outbreaks of foodborne illnesses through food traceability protocols include the accuracy and speed of obtaining tracking information and the inability of third parties to manipulate that tracking information.  Companies that attain top recall accuracy and speed by implementing investigation improvements can reduce recall costs, loss of profits, and reputational damage, and in the case of food recalls, save lives.  Enter blockchain.
   Continue reading: https://www.natlawreview.com/article/fast-track-using-blockchain-to-trace-products-through-supply-chain

Bitcoin and other cryptocurrencies can be among the most volatile securities trading today.
A safer way to invest in cryptos and blockchain-technology companies is through exchange traded funds.
The Amplify Transformational Data Sharing ETF BLOK is, by far, the largest ETF focused on cryptocurrencies and companies that use or develop blockchain technology. It has $1.3 billion in assets and is actively managed. The second-biggest ETF in the space is the Siren Nasdaq NexGen Economy ETF BLCN, which is passively managed — it follows an index — and has $291 million in assets. Both ETFs were established on Jan. 17, 2018. There’s more about each of them below.
Digital currencies — risks and rewards
Before digging into the blockchain ETFs, consider the risks of bitcoin and other digital currencies beyond volatility. For example, if you hold bitcoin in a digital wallet, make sure you don’t lose your password. One investor lost access to an account with 7,002 bitcoin in 2012, according to Yahoo Finance. That equates to more than $327 million, based on bitcoin’s BTCUSD, -1.30% settled price of $46,777 on Sept. 7
Continue reading: https://www.marketwatch.com/story/heres-a-safer-way-to-invest-in-bitcoin-and-blockchain-technology-11631199388

In the last century, paper lists and ledgers gave way to powerful electronic databases that enable IT admins to search, sort, share and move records and associated information.
But traditional databases have limitations. For example, databases are singularly owned services. A business deploys, builds and manages its database and the data it contains. The business can then use that data -- or sell or share it with other businesses within its digital economy. The business that owns the database has total control over its design, contents and availability -- and data users are wholly dependent upon the integrity of the data and database owner, often dubbed a "trusted authority." And as the world becomes evermore connected and dependent on data and data sharing, the limitations of traditional databases pose challenges to security and trust.
These limitations have driven the development of distributed electronic database systems. It's a technology intended to democratize information by distributing and synchronizing data between multiple independent stakeholders, such as businesses or governments, that choose to participate in the system. The most common example of this system is blockchain.
Continue reading: https://searchitoperations.techtarget.com/tip/Blockchain-An-immutable-ledger-to-replace-the-database

The coronavirus pandemic has been a boon for the test proctoring industry. About half a dozen companies in the US claim their software can accurately detect and prevent cheating in online tests. Examity, HonorLock, Proctorio, ProctorU, Respondus and others have rapidly grown since colleges and universities switched to remote classes.
While there’s no official tally, it’s reasonable to say that millions of algorithmically proctored tests are happening every month around the world. Proctorio told the New York Times in May that business had increased by 900% during the first few months of the pandemic, to the point where the company proctored 2.5 million tests worldwide in April alone.
I'm a university librarian and I've seen the impacts of these systems up close. My own employer, the University of Colorado Denver, has a contract with Proctorio.
It’s become clear to me that algorithmic proctoring is a modern surveillance technology that reinforces white supremacy, sexism, ableism, and transphobia. The use of these tools is an invasion of students’ privacy and, often, a civil rights violation.
If you’re a student taking an algorithmically proctored test, here’s how it works: When you begin, the software starts recording your computer’s camera, audio, and the websites you visit. It measures your body and watches you for the duration of the exam, tracking your movements to identify what it considers cheating behaviors. If you do anything that the software deems suspicious, it will alert your professor to view the recording and provide them a color-coded probability of your academic misconduct.
Depending on which company made the software, it will use some combination of machine learning, AI, and biometrics (including facial recognition, facial detection, or eye tracking) to do all of this. The problem is that facial recognition and detection have proven to be racist, sexist, and transphobic over, and over, and over again.
In general, technology has a pattern of reinforcing structural oppression like racism and sexism. Now these same biases are showing up in test proctoring software that disproportionately hurts marginalized students.
A Black woman at my university once told me that whenever she used Proctorio's test proctoring software, it always prompted her to shine more light on her face. The software couldn’t validate her identity and she was denied access to tests so often that she had to go to her professor to make other arrangements. Her white peers never had this problem.
Similar kinds of discrimination can happen if a student is trans or non-binary. But if you’re a white cis man (like most of the developers who make facial recognition software), you’ll probably be fine.
Students with children are also penalized by these systems. If you’ve ever tried to answer emails while caring for kids, you know how impossible it can be to get even a few uninterrupted minutes in front of the computer. But several proctoring programs will flag noises in the room or anyone who leaves the camera’s view as nefarious. That means students with medical conditions who must use the bathroom or administer medication frequently would be considered similarly suspect.
Beyond all the ways that proctoring software can discriminate against students, algorithmic proctoring is also a significant invasion of privacy. These products film students in their homes and often require them to complete “room scans,” which involve using their camera to show their surroundings. In many cases, professors can access the recordings of their students at any time, and even download these recordings to their personal machines. They can also see each student’s location based on their IP address.
Continue reading: https://www.technologyreview.com/2020/08/07/1006132/software-algorithms-proctoring-online-tests-ai-ethics

During hurricanes, flash flooding and other disasters, it can be extremely dangerous to send in first responders, even though people may badly need help.
Rescuers already use drones in some cases, but most require individual pilots who fly the unmanned aircraft by remote control. That limits how quickly rescuers can view an entire affected area, and it can delay aid from reaching victims.
Autonomous drones could cover more ground faster, especially if they could identify people in need and notify rescue teams.
My team and I at the University of Dayton Vision Lab have been designing these autonomous systems of the future to eventually help spot people who might be trapped by debris. Our multi-sensor technology mimics the behavior of human rescuers to look deeply at wide areas and quickly choose specific regions to focus on, examine more closely, and determine if anyone needs help.
The deep learning technology that we use mimics the structure and behavior of a human brain in processing the images captured by the 2-dimensional and 3D sensors embedded in the drones. It is able to process large amounts of data simultaneously to make decisions in real time.
Looking for an object in a chaotic scene
Disaster areas are often cluttered with downed trees, collapsed buildings, torn-up roads and other disarray that can make spotting victims in need of rescue very difficult. 3D lidar sensor technology, which uses light pulses, can detect objects hidden by overhanging trees.
My research team developed an artificial neural network system that could run in a computer onboard a drone. This system emulates some of the ways human vision works. It analyzes images captured by the drone’s sensors and communicates notable findings to human supervisors.
First, the system processes the images to improve their clarity. Just as humans squint their eyes to adjust their focus, this technology take detailed estimates of darker regions in a scene and computationally lightens the images.
Continue reading: https://www.mbtmag.com/home/article/21710722/autonomous-drones-could-speed-search-rescue-efforts

Recently, the central government notified the new Drone Rules 2021, giving significant clearances and liberalising procedures for drone attainment and usage. Compared to the previous rules, Drone Rules 2021 have abolished several requirements and approvals to encourage the growth of India’s drone industry. 
Prior to this, the framework required drone operators and manufacturers to fill 25 forms, which are now reduced to five, and the total number of fees for drone operations has been reduced from 72 to four. With the new rules in place, security clearance and extensive approvals comprising unique authorisation number, operator permits, drone port authorisation, among others are no longer required. 
Industry players in the drone market are exploring new opportunities, which will enhance their business growth. “The current framework is what it should have been in the beginning so it's a very welcome change. I think the basic principle that it operates on is the premise of trust, self -certification, and non-intrusive monitoring,” says Rahul Sankhe, President and Co-founder at SenseHawk, in a panel discussion with YourStory’s Daily Dispatch. 
Continue reading: https://yourstory.com/2021/09/new-drone-rules-dunzo-sensehawk-skye-air-mobility/amp

In front of a packed Mirage Theater in Las Vegas, the Federal Aviation Administration (FAA) administrator, Stephen Dickson, delivered a riveting speech in which he recounted the comprehensive chronology that has taken our industry this far and then outlined his agency’s plans for short-, medium-, and long-term regulation.
“I want to thank all of you for being here, your presence, your leadership, your engagement, speak volumes to me, and it's so important to the innovation that's going on right now. Over the last 18 months as we all know a lot of these events have had to go virtual,” Administrator Dickson said. “But our work to move forward together to safely scale and integrate routine drone operations into the National Airspace has continued to move at a rapid pace. In many respects, you know, I truly think this is the most exciting period in aviation aerospace history.”
Administrator Dickson systematically addressed various aspects of current regulation and offered the riveted audience a blueprint of the Agency’s plans for the drone industry.
“At the FAA, we're focused on establishing drone policy that ensures safe integration into the Airspace System. But at the same time, doesn't stifle the advances in the innovation that we see happening in places like Georgia Tech and from many of the folks in this room. The public perception, though, fully expects all aspects of aviation to be as safe as commercial airlines have become.” Dickson said.
When addressing the role his agency is playing in the massive deployment of unmanned vehicles into the national airspace (NAS), Dickson detailed his vision for his administration.
“My role as FAA administrator is to figure out how to support these emerging technologies, while maintaining the unwavering safety commitment that the public has come to expect from the Agency. Finding this balance is especially challenging, because it crosses so many domains, regulations, infrastructure, technology, operations, and societal perceptions. So, we are taking a systems approach and an enterprise-wide approach in which we can no longer give approvals and look at issues by individual FAA lines of business, we really have to take a holistic enterprise approach to these issues.”
Continue reading: https://www.commercialuavnews.com/regulations/faa-administrator-stephen-dickson-addresses-the-drone-community-at-commercial-uav-expo-americas

One of the big concerns about drone delivery concerns the spinning rotors, which are a huge potential liability to people, pets, and property if things go awry. But what if delivery drones didn't have to land?
That's the concept behind A2Z Drone Delivery, LLC's tethered freefall drone delivery mechanism, which is the backbone of its new drone, called the RDSX commercial delivery UAV. We've written about A2Z before and found the system novel. with the rollout of its commercial drone, the company is now formally entering the logistics sector, providing an interesting case study for the near future of drone delivery.
"Residential drone delivery pilot programs are coming online throughout the United States right now, and much of the industry is anxiously awaiting the large-scale regulatory approval that will see residential deployments rapidly expand," said Aaron Zhang, founder of A2Z Drone Delivery, LLC. "While the raw technical capabilities for these deliveries already exist, a key benchmark for regulatory approvals will be addressing the consumer comfort with UAVs being rolled out into daily life. Our tethered freefall delivery capability integrated with the RDSX offers a way to mitigate some of those consumer concerns."
Read more: https://www.zdnet.com/article/tethered-drone-delivery-from-150-feet/

I’m hugely passionate about artificial intelligence (AI), and I'm proud to say that I help companies use AI to do amazing things in the world.
But we must make sure we use AI responsibly, so we can make the world a better place. In this post, I’m going to give you some tips for making sure you apply AI ethically within your organization.
How Do We Use Artificial Intelligence Ethically?
1. Start with education and awareness about AI.
Communicate clearly with people (externally and internally) about what AI can do and its challenges. It is possible to use AI for the wrong reasons, so organizations need to figure out the right purposes for using AI and how to stay within predefined ethical boundaries. Everyone across the organization needs to understand what AI is, how it can be used, and what its ethical challenges are.
2. Be transparent.
This is one of the biggest things I stress with every organization I work with. Every organization needs to be open and honest (both internally and externally) about how they’re using AI.
Continue reading: https://www.forbes.com/sites/bernardmarr/2021/09/10/how-do-we-use-artificial-intelligence-ethically/?sh=1b4e166279fd

According to IMARC Group’s latest report, titled “Drones Market: Industry Trends, Share, Size, Growth, Opportunity and Forecast 2021-2026,” the global drones market exhibited strong growth during 2015-2020. Looking forward, the market is expected to grow at a CAGR of around 17% during 2021-2026.
We are regularly tracking the direct effect of COVID-19 on the market, along with the indirect influence of associated industries. These observations will be integrated into the report.
Drones, or unmanned aerial vehicles (UAV), are unpiloted aircraft generally used for defense and military purposes. They can be flown for longer distances, rely on sensors and LIDAR detectors, without the need for a pilot to navigate it. Nowadays, drones are also used for recreational purposes and in the business community due to the enhanced safety and efficiency levels. They find application in monitoring, surveying, mapping, precision agriculture, aerial remote sensing, and product delivery.
Request Free Sample Report: https://www.imarcgroup.com/drones-market/requestsample
Market Trends:
The global drone market is primarily driven by rising demand for small military drones among the defense forces, coupled with the increasing use of drones in commercial applications. They are also utilized in agricultural activities, including livestock monitoring, irrigation management, and fertilization. Furthermore, extensive global investments and regulatory changes are increasing the revenue and profit opportunities for drone manufacturers, solution providers, operators, and distributors, which is positively influencing the growth of the market.
Ask Analyst and Browse Full Report with TOC & List of Figure: https://bit.ly/2XYgKNu
Find more here: https://midwestxpositor.news/uncategorized/34153/drones-market-is-expected-to-grow-at-a-cagr-of-around-17-during-2021-2026/

Over the past few years, the internet has closely followed along as Boston Dynamics’ Spot has more or less “grown up.” We’ve collectively watched in awe as Spot and its robotic predecessors learned to withstand a push or a shove, navigate dangerous terrains, and eventually dance like BTS.
For the general public, Spot’s robotic dance montages are what the robot is best known for. But is Spot more than a neat (albeit expensive) commercial toy? The commercial drone market provides one answer.
The Path to Drone Development In 2016, the analyst firm Gartner predicted that commercial UAVs were just barely rounding the corner of “peak inflated expectations”, with 5-10 years of development still to come before the technology reached mainstream adoption. By 2017, Gartner concluded that drones had effectively rounded the corner, with the adoption time frame essentially halving to 2-5 years.
Quite rapidly (though less publicly than the perception of ground robots), drones went from being freelance videographer toys and neighborhood nuisances to essential inspection tools for enterprise businesses like construction, energy and agriculture. The number of use cases for drones also grew as drone hardware became more advanced and reliable. Advanced aerial mapping, crop monitoring, public safety uses, disaster response, and consumer drone deliveries all seemed to be on the table as the drone industry matured.
Today, there are over 350,000 registered commercial drones in the U.S., with some of the largest fleets, such as that of agricultural giant Corteva, numbering in the hundreds. Adoption has been primarily driven by the various safety and efficiency benefits that drones provide to industrial jobsites.
These hundreds of thousands of drones are now conducting programmed crop scans, completing exterior building inspections, and performing thermal scans of solar farms with routine swiftness. They are keeping workers safely away from disaster areas or dangerous construction tasks (i.e., inspecting roofs, scaling scaffolding), saving time, resources and human well-being. However, the industry would not have gotten to this point without the help of advanced software solutions.
Continue reading: https://www.roboticsbusinessreview.com/opinion/what-is-the-future-of-robotics-the-commercial-drone-market-provides-one-answer/

Ty Reed, a junior at Cambridge High School, is making money by commercially flying a drone after completing a drone class in school.
"I saw that (the class) was going to be about flying drones and being able to fly remoted controlled things have always interested me," Ty said on why he took the class. "I thought it would be a cool experience to get go out and fly drones at school and it would be a good experience."
As part of the class, Ty obtained his FAA (Federal Aviation Administration) certification to operate drones.
To get the certification, he had to complete the drone course offered through the school and complete the required FAA test at the airport.
"It took a lot of studying and a lot of preparation but I passed it and got my license," Ty said.
The Drone Commercial License allows him to earn money while flying drones.
Continue reading: https://www.aviationpros.com/aircraft/unmanned/news/21237557/high-school-student-earns-faa-certification-to-fly-drones

This article was written by Bob Friday, Vice President and Chief Technology Officer of Juniper’s AI-Driven Enterprise Business.
In a recent survey of 700 IT pros around the world, 95% said they believe their companies would benefit from embedding artificial intelligence (AI) into daily operations, products, and services, and 88% want to use AI as much as possible. When was the last time you heard that many people agree on anything?
Yes, AI is all the rage because it is the next step in the evolution of automation in doing tasks on par with human domain experts whether it is driving a car or helping doctors diagnose disease. But make no mistake while we are starting to see the fruits of AI here and there: By and large, the industry and most organizations are still in the early days of AI adoption. And as with any new momentous technology, organizations need to develop an adoption strategy specific to their organization to get the full benefits of AI automation and deep learning technology.
The complication as Gartner put it: “How to make AI a core IT competency still eludes most organizations.”
But failing to learn how to leverage the benefits AI/ML will leave an organization at a competitive disadvantage in terms of customer experience and operational efficiency. So, what’s the way to get there? Here are three common traps that companies should steer clear of as they get themselves AI-ready.
Continue reading: https://venturebeat.com/2021/09/09/three-traps-companies-should-avoid-in-their-ai-journeys/