Artificial intelligence is everywhere. But if I asked you: “What is it exactly?” could you answer confidently?
Four years ago I thought I could answer that same question. I was about to start studying machine learning and deep learning with the hopes of finding a job. I was naïve enough to think what I was seeing from the outside was what I’d encounter on the inside.
But looks are deceiving. And artificial intelligence, surrounded by hype and flooding in funding is the best example today. There are interests beyond science and engineering that blurry and obscure the real work people are doing.
The field is extremely attractive regardless. It’s growing and evolving incredibly fast and it promises to keep this pace for some time. There will be more AI-related jobs in the coming years. And, let’s be real, it’s way more exciting and interesting than most other fields out there — we’re trying to solve intelligence after all.
That’s why many of you may benefit from knowing what to expect. Here are four things I wish I knew before starting on AI. I’d have been mentally prepared for what I was about to experience and would have had a finer, deeper perspective on the present and future of the field. Enjoy!
Continue reading: https://towardsdatascience.com/4-things-i-wish-i-knew-before-starting-in-the-ai-industry-5458c6bf48b9

Artificial intelligence (AI) is one of the hottest topics in marketing right now. Raj Venkatesan and Jim Lecinski recently published a book entitled “The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing”. To better understand what an AI marketing canvas is, I sought insight from Raj Venkatesan, a professor at the Darden School of Business. In full disclosure, I work with Raj and find his research and work fascinating. Below is insight on the AI marketing canvas.
Kimberly A. Whitler: Why did you and Jim write this book?
Raj Venkatesan: We heard and experienced the rise of data and algorithms. Marketing professionals had started to pay attention to this, and they wanted to invest in this new technology. But they were struggling with the why and the how questions. They needed guidance on the ultimate objective of using AI in marketing, i.e., how is marketing—and  customer relationships—going to improve from using AI. There were books written at a very high level regarding whether machines would take over. You know, is the Matrix going to take over, or for the younger people, are we all going to be in Halladay’s game, the Oasis, like Ready Player. On the other hand, there were books written around 10 steps to better email marketing. Very granular, but again not at the strategic level a senior marketing profession would want to use AI. So, we set out writing a book, that we feel is like the goldilocks solution, not too high, and not too granular.
Continue reading: https://www.forbes.com/sites/kimberlywhitler/2021/08/21/the-ai-marketing-canvas-a-roadmap-to-implementing-artificial-intelligence-in-marketing/?sh=63f6b81271ec

Your company has a team monitoring your finances on a day-to-day basis, right? That's a standard business practice. Leaders should approach their diversity, equity and inclusion goals in the same manner. If teams aren’t monitoring their DEI metrics as regularly as the finance team, they're at risk of missing business goals.
Organizations that prioritize DEI are almost two-times more likely to meet or exceed financial goals, according to a 2021 Deloitte report.
Implementing a strong DEI strategy isn't optional. To move the needle on building a more diverse workforce, organizations need to listen to those from historically excluded groups and tailor the hiring experience to be more inclusive. Plus, to counter the unconscious bias that all humans have, companies can take extra measures to help ensure a fair and equitable experience for candidates from HEGs, such as implementing AI capabilities or anonymizing resumes.
Forty-seven percent of organizations have implemented technology to help reduce unconscious bias in their recruiting and hiring, a recent report from Talent Board and iCIMS found. Although 53% have not implemented such technology, one-third of them plan to do so in the future. These practices can help to boost organizations’ DEI results when done correctly.
Continue reading: https://www.benefitnews.com/opinion/3-ways-analytics-can-help-improve-your-recruiting-pipeline-and-meet-your-dei-metrics

Women account for only 29% of the STEM (science, technology, engineering, and math) labor force and 34.5% of STEM faculty at the nation’s colleges and universities. Women of color are even more underrepresented — making up 4.8% of the STEM workforce and 3.8% of STEM faculty. For decades, researchers have told us that “Girls and women are systematically tracked away from science and math throughout their educations, limiting their training and options to go into these fields as adults.” The challenge is how early do educators and parents need to start with girls in order to eliminate this gender gap.
Middle school student Sriya Tallapragada decided to take on this challenge. According to Sriya, “When the coronavirus pandemic shut down my school, I found myself stuck at home with nothing but my computer as company. Luckily, as a 14-year old STEM aficionado and introvert, this was all I needed. I found the large amounts of time on my hands to be the perfect opportunity to meet my goal of working to close the gender gap in STEM.”
Continue reading: https://www.forbes.com/sites/marybethgasman/2021/08/23/want-more-women-in-science-start-early-and-listen-to-girls/?sh=45e71dc77f85

For all of us who are in a certain way related in one way or another to technology, the term Internet of things is at least known, but not all of us know exactly what it means. That is why this blog tries to cover some basic concepts on this subject, as well as advantages and disadvantages of the IoT.
According to Wikipedia: IoT is a concept that refers to a digital interconnection of everyday objects with the internet. It is, in short, the internet connection more with objects than with people. It is also often known as the internet of all things or the internet in things.
In short, IoT is something connected to a network, such as the internet, or to other machines so that they work autonomously, without requiring human intervention. The other concepts describe things that are possible thanks to the Internet of Things. The terms of home, car or anything else connected refer to that, in some way, they are connected to a network.
Is it just this? Yes, it really is. Don't be put off by the new terminology. The IoT concept is that simple, at least for consumers.
There was a time when knowing, from a distance, how many bottles of Coke were left in a vending machine was revolutionary. This is how the Internet of Things (IoT) was born: when Carnegie Mellon University students, tired of walking to the machine without knowing if there would be soft drinks, connected it to an ARPANET network. Four decades later, that discreet milestone proved prescient. Today there are about 10 billion connected objects around the world. And it's only the beginning. There will come a day when we have a 100% connected life and can remotely control everything around us. The IoT consists of connecting objects to the internet so that they interact and share information.
Continue reading: https://www.linkedin.com/pulse/iot-what-could-possibly-go-wrong-ignacio-chitnisky/?trk=articles_directory

Digital transformation has accelerated across the board. In a recent report, McKinsey referred to this technological “tipping point” as the quickening, suggesting the adoption of digital technologies has jumped forward by several years in the space of mere months. One of those technologies is edge computing, and it’s here for the long haul. From smart city infrastructure to in-hospital patient monitoring, edge computing’s potential is unfathomably immense. Yet, the technology is now becoming so accessible that the industry is exploring innovative applications a little closer to home. Could edge computing be the missing ingredient to keep children safe in the kitchen?
Gartner predicts that by 2025, more than three-quarters of all generated data will be “created and processed outside of a traditional centralized data center or cloud,” and that could now include your kitchen. The kitchen is the most complex room in any home. It’s the place where water, electricity, gas, heat, fire, and sharp objects are regularly thrown into the mix together. More than 300 children end up in hospital every day in the US alone, with burn injuries sustained in the kitchen and more than 55% of all accidents in India happen in the kitchen. It’s little wonder so many organizations continuously campaign to raise awareness about kitchen safety.
Living on the Edge
Smart technology and edge computing go hand-in-hand. As we discover bigger and better applications for artificial intelligence, augmented reality and machine learning, it follows that we also need more computing power wherever the action is happening. That’s what edge computing sets out to achieve, coupling each device with the processing power it needs to make rapid-fire calculations in near real-time, instead of having to depend on remote cloud processing. 
Continue reading: https://www.iotforall.com/careful-with-that-how-iot-is-keeping-children-safe-in-the-kitchen

Research conducted by the US National Institute of Standards and Technology (NIST) has shown that commonly available solar PV technology used indoors can power building IoT devices.
The study was aimed to test the ability of solar PV cells to absorb indoor light and opens the way for harvesting some of this light for low power devices with low capacity batteries such as smoke alarms, security cameras and temperature sensors.
The researchers tested three different materials, gallium indium phosphide (GaInP) and gallium arsenide (GaAs), which are geared toward white LED light, and silicon, a less efficient but more affordable and commonplace material.
The modules were tested with white LED light with a fixed intensity comparable to light levels in a well-lit room. For the silicon and GaAs PV modules, the indoor light proved less efficient than sunshine, but the GaInP module performed far better under the LED than sunlight.
Continue reading: https://www.powerengineeringint.com/news/solar-pv-can-power-indoor-iot-devices-study/

BEIJING   -  China is willing to share its experience and help integrate information technology and agriculture to being about green revolution in Pakistan.
Facing the common challenge of climate change, pandemic, and population growth, a smarter agriculture is the way forward for many countries including China.
“The integration of information technology and agriculture will bring about the third green revolution: agricultural digital revolution,” said Zhao Chunjiang from China’s National Engineering Research Centre for Information Technology in Agriculture. “By 2025, China’s digital agro economy will exceed a USD 100 billion.”
In the past, farmers laboured for hours in the fields. But now farm work can be done with internet systems, said a staff member of the exhibitor, Ningxia Green Pioneer (Lvxianfeng) Agricultural Mechanical Services Company, which has transformed local farming model with drones, precision hole-sowing machine, driverless harvesters and plant protecting devices, remote surveillance equipment, etc supported by the Internet of things, cloud technology, big data, etc.
“Spraying at a speed of 4.5 meters a second, each drone can complete what was used to be done by 25-30 workers per day, saving 80 percent water, 30 percent cost of plant protection, and 20 to 25 percent pesticides,” company staff introduced to China Economic Net (CEN). “They can be used in rice, wheat, and maize. Take rice as an example, about USD 60 can be saved for each hectare.” 
Continue reading: https://nation.com.pk/23-Aug-2021/digital-farming-essential-for-smart-agriculture-revolution-in-pakistan

Google Wing delivery drones could soon be picking up packages from Australian shops rather than asking retailers to co-locate in the tech giant’s distribution centres.
Jesse Suskin, the business’ head of government relations, hinted the significant development could happen within six months and said the “complicated” challenge is now “solvable”.
Wing launched commercially in Canberra and Logan in 2019 and currently allows for the delivery of packages that weigh less than 1.5 kilograms from a variety of vendors who sell household and perishable goods, including coffees and sandwiches.
Australia has quietly become the epicentre of Google’s global plans for conquering the drone delivery industry in recent years, with Wing conducting more deliveries here than in any other country worldwide.
Continue reading: https://australianaviation.com.au/2021/08/exclusive-google-drones-to-pick-up-packages-from-australian-shops/

In the world of cryptocurrencies, every time a transaction takes place it gets logged in to a blockchain — a distributed ledger that makes the information globally available on a real-time basis. That does not mean a user or investor gets an automatic update about each successful transaction. It's more like the data is stored and updated on the digital ledger but anyone who wants to check details has to look for it. But how do you do that? That is done with the help of tools that work as a sort of “Google” for cryptocurrency.
What about cross-platform data? Meaning if a Bitcoin blockchain user wants to check the details of a transaction related to, say, the Ethereum blockchain, how to do it? That can also be done by the same process. These tools are called blockchain explorers. Most of them provide services for more than one blockchain.
What are blockchain explorers?
Simply put, a blockchain explorer is a type of software that pulls data from a blockchain and creates a database for users to search for particular information from the available resource. They allow users to see details related to various cryptocurrency transactions, including the amount transacted, the source and the destination of the transfers, and the status of transactions.
Continue reading: https://gadgets.ndtv.com/cryptocurrency/features/cryptocurrency-transactions-blockchain-explorer-data-search-bitcoin-ethereum-cardano-2516328

Bitcoin and blockchain first initially suggested in 2008 by an individual using the nickname Satoshi Nakamoto, who detailed whether cryptography and an openness smart contract might be coupled to create a digital payment software. At initially, bitcoin's extraordinary volatility and many governments' views regarding its difficulty limited its growth slightly, but the benefits of the ledger, bitcoin's operating system, drew increased attention. Among the benefits of blockchain technology are its bitcoin transaction, decentralization, capacity building, tamper-resistant design, and availability. As a result, the advancement of blockchain technology has been gradual.
Blockchain technology is now classified as Bitcoin 1.0, 2.0, through 3.0, depending on its intended use. The Supplement contains more information on the three decades of cryptocurrencies. From digital money to banking, bitcoin has progressively expanded into medicare, project management, research and analysis, industrial IoT, and copyright infringement. In addition, numerous academic areas have examined blockchain technology. For instance, several academics have examined the blockchain's operating systems, including tiered applications, mentoring networks, authentication, infinite scalability, and negotiation methods. The purpose of this research is to undertake a thorough and impartial evaluation using information collected and evaluated. In addition, numerous experts have investigated the additional value of blockchain technology.
They argue that human tasks may be successfully reduced by using blockchain technology to speed transactional and settlement procedures. For example, in the health care industry, blockchain technology may be critical for centralizing research data, preventing prescription medicine fraud, and lowering administrative costs. In the music business, blockchain technology can dramatically enhance the quality and availability of copyright data and the transparency of the value chain. Finally, swan illustrates the financial benefits of cryptocurrency via four representative application fields: software platform repositories, acceleration computing, long-tail customized telecommunication providers, and enfranchisement and social banking.
Continue reading: https://www.state-journal.com/sponsored/how-blockchain-technology-is-beneficial-for-business/article_8fef491c-041a-11ec-9ae3-a366762bfb18.html

As the infrastructure bill that brought a great deal of attention to Washington D.C. on the regulatory oversight of crypto, the 117th Congress now has seen 18 bills that have been introduced that directly impact cryptocurrencies, blockchain technology, or central bank digital currencies.
Last Congress, the main focus was around the introduction of Facebook’s new Libra project - renamed Diem - with an intense focus on the potential impact of stablecoins. Back in 2019, the Blockchain Association did an outstanding effort on the Hill with helping to differentiate between Bitcoin and other more centralized cryptocurrencies.
Additionally, the birth of a digital dollar or central bank digital currency (CBDC) made a splash in the crypto community, while Coin Center, the leading think tank in Washington D.C. on policy matters related to cryptocurrency, presented the dangers of losing privacy in moving forward with a U.S. digital dollar.
This article seeks to lay out for those newly interested in crypto regulation what some of the legislation is about that has been introduced. The sections will be divided into bills that cover bills that aim at providing regulatory clarity for crypto, the technology underlying bitcoin called blockchain, and consideration of a U.S. CBDC.
Continue reading: https://www.forbes.com/sites/jasonbrett/2021/08/22/congress-has-introduced-18-new-bills-on-crypto-and-blockchain-in-2021/?sh=1e518035263b

It’s not a secret AI Is everywhere, but it’s not always clear when you’re interacting, not to mention which particular technique is working. But one subset is easy to recognize. If the experience is intelligent and includes photos and videos, or is somehow visual, computer vision may be working behind the scenes.
Computer vision is a subfield of AI, especially machine learning. If AI allows machines to “think,” computer vision allows them to “see.” More technically, it enables machines to recognize, understand, and respond to visual information such as photos, videos, and other visual inputs.
In the last few years, computer vision has become a major driver of AI. This technique is widely used in industries such as manufacturing, e-commerce, agriculture, automotive and medical. Power everything from interactive Snapchat lenses to sports broadcasts, AR-based shopping, medical analytics, and self-driving capabilities. And by 2022, the global subfield market projection It is expected to reach $ 48.6 billion annually, up from just $ 6.6 billion in 2015.
The story of computer vision follows the story of the entire AI. A slow rise full of technical hurdles. A big boom made possible by a large amount of data. Rapid proliferation. And there is growing concern about bias and how technology is being used. To understand computer vision, it is important to understand how computer vision works and is used, and both the challenges it has overcome and the challenges it still faces.
Continue reading: https://illinoisnewstoday.com/how-computer-vision-works-and-why-it-suffers-from-prejudice/343390/

"Life is like a game of chess, where every move you make has an impact on the rest of your game," Kathy Gong Xiaosi said, looking radiant. Sitting in the open area outside her office in downtown Beijing, Gong, once the youngest national chess champion, recounted how her third startup survived a near collapse.
Called Wafa Games, her company uses cutting-edge tech to create fun and dignified gaming experiences. Venturing into the gaming industry requires massive investments and courage to withstand the risk of bankruptcy. But Gong chose to go against the grain.
The 35-year-old woman from the southwestern city of Chengdu founded the company in 2017 with a partner she got to know through playing games. "I'm a gamer, but I found most games boring or even disagreeable since female characters are designed mainly to appeal to male players, with scant clothing and sexualized bodies." For decades, most video games around the world have portrayed female characters as manifestations of male fantasies with hourglass curves and skinny waists. In hot pants or tiny skirts, they prance around to help, support and take care of their male teammates. Either that or they are framed as ditzy love interests needing to be rescued.
Gong developed her deep affection for games during a lonely period while studying in New York, so she decided to fight against this stereotype by creating well-rounded female protagonists, especially for women gamers such as her. "I like hardcore games where you use strategic thinking as you do on the chessboard," she said.
Continue reading: https://news.cgtn.com/news/2021-08-23/No-game-no-life-A-young-woman-s-trailblazing-entrepreneurship--12XitKkZQ9G/index.html

Artificial intelligence has been a steady presence in businesses around the world for quite some time now. The transformative powers and abilities of AI have boosted the ease of business operations as well as the ROI for organizations. Now, edge AI represents the next phase of the technology’s development.
Most filmmakers and authors face a problem commonly known as the sophomore slump while attempting to create a follow-up to their first movie or book. The dreaded slump is associated with the inevitable dip in quality that usually accompanies their second film or novel, especially if the debut effort was genuinely amazing. After all, how do you top something that was (and continues to be) loved by the masses and critics alike? It is hard to improve a project or concept that is near-perfect in every way. A concept that has changed the game with its levels of innovation and ingenuity. In other words, a concept such as artificial intelligence. Despite its few weaknesses, AI continues to have a positive impact on the work quality and productivity in several organizations around the world. Automation on a large scale can be achieved by AI-powered systems in any industry, be it healthcare, national defense, or e-commerce.
So, what is edge AI? It consists of AI models and algorithms that process data locally on a standalone hardware device. In short, AI technology is local, smaller in size, and more accessible for common people. The AI algorithms in such devices use data generated locally for real-time machine learning purposes. The data to be processed locally is sent and received through transmitted signals and sensors on such devices. Such 'endpoint' AI systems do not need to be digitally connected to a cloud for performing tasks and operations locally. Instead, they possess the ability of processing data and making decisions independently. As stated earlier, edge computing, which brings the powers of AI to your personal devices, needs the presence of inbuilt microprocessors and receptors to attain processable data.
Continue reading: https://www.linkedin.com/pulse/edge-ai-next-step-evolution-naveen-joshi/?trk=articles_directory

Enterprises have long sought AI for its ability to supercharge a workforce, picking up slack through automated tasks and a cost-effective option for repetitive labor, compared to humans. 
The next act in enterprise AI sees the technology becoming a standalone maker. The technology generates synthetic data to train its own models or identify groundbreaking products as solutions mature and adoption widens, as showcased in Gartner's Hype Cycle for Emerging Technologies 2021 report, published Monday.
Called "Generative AI,", the technology is set to reach the plateau of productivity in the next two to five years. Commercial implementations of generative AI are already at play in the enterprise and, as the technology advances through the hype cycle, non-viable use cases will fade, according to Brian Burke, research VP at Gartner.
Generative AI works by using algorithms to create a "realistic, novel version of whatever they've been trained on," Burke said. Algorithms can identify new materials with specific properties and technologies that generate synthetic data to augment research, among other use cases.
Continue reading: https://www.ciodive.com/news/gartner-hype-cycle-2021-generative-AI/605338/

By 2030, AI will likely no longer be getting adopted with simple scenarios and applications. It will be expected to detect life-threatening diseases in the nascent stage, predict weather conditions of a large area over several months and become a digital collaborator to the human race. These are just a few possibilities of the potential impact of AI on life and work in the coming years. The pace of change has been unprecedented in the sector, and it promises to continue in the same vein in the years to come.
With rapid learning and adoption, AI is no longer a crystal ball technology but something that humans now interact with in nearly every sphere of life. In fact, the transformation led by AI has been so pervasive that it is deeply influencing user experience and how humans interact with brands and technologies. The way things are trending, AI will soon become an undeniable part of human life and society.
This widespread adoption and a variety of new use cases will come from the rapidly evolving nature of AI. It is already achieving faster computation, higher accuracy and lower computation and infrastructure costs. Today, AI is evolving across all three dimensions — compute, data and algorithm — which sets the context for its adoption across all realms of life and work by 2030. Here is the direction that I see AI moving within these categories.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2021/08/23/the-possibilities-of-ai-in-2030-transformation-across-dimensions/?sh=fa0186a6b67a

As power grids fill up with renewable energy, electric vehicle charging stations and customer-owned generation, they will become too complex and fast-moving for their human operators to keep up with, a group of international researchers warns.
The humans will need help from smart machines — high-performance computers running decision making software systems built with artificial intelligence — according to researchers at France’s grid operator RTE, the U.S. Electric Power Research Institute (EPRI) and other partners.
With the proliferation of low-carbon options, "the grid becomes exponentially more challenging to operate," said Jeremy Renshaw, EPRI’s AI director. "Grid operators are already stretched to the limit. Getting AI resources to help is going to be critical."
That judgment has been reinforced, Renshaw says, by an ongoing international competition called L2RPN (for "Learning to Run a Power Network") challenging AI developers to invent software that keeps a simulated power grid from crashing in emergencies.
The stakes are high: Maintaining grid stability is already a knife-edge task as operators juggle climate hazards, cyberthreats, and an avalanche of connected devices like rooftop solar panels and smart appliances. But in the conservative electric power industry, AI will have to prove itself, Renshaw said. “It’s going to be anywhere from five to 15 years before we see widespread adoption,” Renshaw said in an interview with E&E News.
In the meantime, the race is on to create AI programs savvy enough to steer the future grid. The second round of the L2RPN competition last year attracted 300 contestants worldwide, including teams from the U.S., China, Russia, Colombia and Singapore. A new, expanded round is underway.
More interest in embedding advanced computer decision making into the grid was evident in a recent virtual EPRI conference that brought together a cross-section of U.S. utilities and developers of computer systems, EPRI says.
But entrusting computers and AI to make split-second operating decisions in grid emergencies is still a tall order, Renshaw said.
"It’s very optimistic to say we’d be ready to deploy [that capability] in five years. This is really cutting-edge stuff,” he said.
“Trustworthiness in AI is a huge issue,” said Massachusetts Institute of Technology professor Koroush Shirvan, speaking at the EPRI conference in May.
Continue reading: https://www.eenews.net/articles/wanted-superhuman-ai-to-master-a-greener-grid/

When a company is formulating a blockchain solution to fill its supply chain needs, inevitably the decision must be made as to what type of blockchain is best suited for the project.  Therefore, it is essential to have a clear understanding of the options available for  blockchain structures.  Not all types of blockchains are appropriate for supply chain information management.
Permissionless vs. Permissioned Blockchains
All types of blockchains can be characterized as permissionless, permissioned, or both.   Permissionless blockchains allow any user to  pseudo-anonymously join the blockchain network (that is, to become " nodes" of the network) and do not restrict the rights of the nodes on the blockchain network.
Conversely,  permissioned blockchains restrict access to the network to certain nodes and may also restrict the rights of those nodes on that network.  The identities of the users of a permissioned blockchain are known to the other users of that permissioned blockchain.
Permissionless blockchains tend to be more secure than permissioned blockchains, because there are many nodes to  validate transactions, and it would be difficult for bad actors to collude on the network.  However, permissionless blockchains also tend to have long transaction processing times due to the large number of nodes and the large size of the transactions. 
On the other hand, permissioned blockchains tend to be more efficient.  Because access to the network is restricted, there are fewer nodes on the blockchain, resulting in less processing time per transaction. 
Like so many things, pros come with cons, and the reduced processing time in permissioned blockchains is no exception: the  centralization of permissioned blockchains to some  central authority (be it a government, a company, a trade group, or some other entity or group that is granting the permission to nodes and creating the restrictions of the blockchain) makes it a less secure system that is more prone to traditional hacking vulnerabilities.  The fewer nodes there are on a blockchain, the easier it is for bad actors to collude, so private blockchain administrators must ensure nodes adding and verifying  blocks are highly trusted.
Types of Blockchains
There are four types of blockchain structures:

1. Public Blockchains
   [/LIST=1]
   Public blockchains are permissionless in nature, allow anyone to join, and are completely  decentralized.  Public blockchains allow all nodes of the blockchain to have equal rights to access the blockchain, create new blocks of data, and validate blocks of data. 
   To date, public blockchains are primarily used for exchanging and mining  cryptocurrency.  You may have heard of popular public blockchains such as Bitcoin, Ethereum, and Litecoin.  On these public blockchains, the nodes "mine" for cryptocurrency by creating blocks for the transactions requested on the network by solving cryptographic equations.  In return for this hard work, the miner nodes earn a small amount of cryptocurrency. The  miners essentially act as new era bank tellers that formulate a transaction and receive (or "mine") a fee for their efforts.
   1. Private (or Managed) Blockchains
      [/LIST=1]
      Private blockchains, which may also be referred to as managed blockchains, are permissioned blockchains controlled by a single organization. In a private blockchain, the central authority determines who can be a node.  The central authority also does not necessarily grant each node with equal rights to perform functions.  Private blockchains are only partially decentralized because public access to these blockchains is restricted.  Some examples of private blockchains are the business-to-business virtual currency exchange network Ripple and Hyperledger, an umbrella project of open-source blockchain applications.
      Both private and public blockchains have drawbacks - public blockchains tend to have longer validation times for new data than private blockchains, and private blockchains are more vulnerable to fraud and bad actors. To address these drawbacks,  consortium and  hybrid blockchains were developed. 
      Continue reading: https://www.mondaq.com/unitedstates/fin-tech/1103736/types-of-blockchain-public-private-or-something-in-between

Blockchain is a type of database composed of a growing list of records, individually known as blocks, that are chained together through computer cryptography. The goal of blockchain is to allow for the recording and distribution of digital information that is unable to be tampered with.
Unlike a typical database where data is electronically stored in a “table” format, data within a blockchain is stored within its connected blocks, with each block containing information about the block that came before it. It is this characteristic that creates a resistance to modification of a blockchain’s data, because a change to one block’s information would require the alteration of all subsequent blocks created. And although blockchains are not entirely unalterable, as a collectively agreed-upon update to the network may be known as a “fork,” blockchains are designed to be foundationally secure.
Blockchains are typically managed through a peer-to-peer network of computers working together to serve as a publicly distributed ledger of data (or transactions). Every node in the network follows a specific protocol which the entire blockchain adheres to in order to validate new blocks and communicate with each other.
What does blockchain have to do with cryptocurrencies?
Although blockchain comes up in nearly every conversation involving cryptocurrencies, the two terms cannot be used interchangeably. Rather, blockchain is the network and platform through which cryptocurrency is transacted and generated. For example, the ether (ETH-USD) cryptocurrency operates through the ethereum blockchain.
Blockchain technology had been discussed in scientific literature for nearly two decades before the advent of cryptocurrencies such as bitcoin (BTC-USD) and ether — the two largest by market cap — with cryptocurrencies becoming one of the first and most widely known applications of blockchain. In 2009, an individual or group of individuals using the pseudonym “Satoshi Nakamoto” invented the first cryptocurrency through the bitcoin blockchain to serve as a public ledger for transactions of bitcoin.
One of the most significant solutions that a digital currency through blockchain technology provides is an answer to the double-spending problem. In addition, it provides this solution along with all of its functionality without the need for a trusted central authority or server. As mentioned previously, because a blockchain network consists of computer nodes which can be located anywhere in the world, blockchains, and therefore cryptocurrencies, operate as completely decentralized platforms.
Continue reading: https://finance.yahoo.com/news/blockchain-what-is-it-and-what-does-it-have-to-do-with-crypto-171503722.html

Watts Innovations has turned to a development made in Zurich for its new heavy lift drones by the name of PRISM Sky. According to a press release, the drones are connected to the open source software developed by Auterion.
With the integration of the Auterion Suite, users can monitor the status of their fleet in real time. For example, they are provided with predictive maintenance recommendations based on flight data. Overall, the software helps to minimize risks and increase efficiency.
Introducing PRISM Sky & KONTACT: an NDAA Compliant Drone Solution. Powered by Auterion
Watts Innovations is based in Baltimore, Maryland, and specializes in the development and production of industrial drones. According to the press release, the company’s new heavy lift drone is versatile and can be deployed in a variety of scenarios across a wide range of industries.  It will be launched on the market at the end of 2021.
Auterion, which is a spin off from Swiss Federal Institute of Technology in Zurich (ETH), has already impressed major companies such as Amazon and DHL with its open source platform. In addition, the US Department of Defense also uses the software developed by the start-up.
Read more: https://www.greaterzuricharea.com/en/news/us-heavy-lift-drones-take-skies-auterion

If you don’t like the current BVLOS rules, you’re not alone. FAA Administrator Steve Dickson doesn’t like them either.
Dickson led a keynote speech on Tuesday at Day 1 of the AUVSI XPONENTIAL 2021 conference in Atlanta, Georgia. His speech was named “Policy Leading to Trusted Integration,” and while the tone was largely hopeful, Dickson took a bit to acknowledge that the current BVLOS rules are far from ideal in enabling the drone industry to prosper.
“They’re not up to the task,” Dickson said in his speech in reference to current BVLOS rules. “For one thing, approving operations on a case-by-case basis is not a feasible or efficient way forward. It’s not feasible or efficient for the agency. It’s not efficient for manufacturers. And it doesn’t give us the kind of certainty that we really need to scale operations around the national airspace.”
Dickson also acknowledged that regulation is often seen as a “drag” on the drone industry’s momentum.
But for what it’s worth, he gave some reason to why things might feel slow for what is otherwise a fast-moving industry: safety. Safety has always been at the forefront of the FAA. And Dickson said that in order to enable the drone industry to advance, the public must trust the drone industry, which requires no safety mishaps. He said in his speech that — since taking the reigns at the FAA back in 2019 — he’s “become a firm believer that smart and fair regulation” will aid in the safe integration of drones into the airspace. And with that, attention to safety can never be relaxed, he said.
“The public fully expects all aspects of aviation to be as safe as commercial airlines,” Dickson said. “Businesses and operators who don’t understand that reality are not going to be in business for long.”
Luckily, drones have had few mishaps that could potentially erode the general public’s trust. And while COVID-19 was certainly brutal for the drone industry, in some ways its contactless, inherently-social-distanced setup helped improve its position in the eyes of the public. Companies like Zipline used drones to distribute medications and PPE between hospitals. Walmart, Quest Diagnostics and drone delivery company DroneUp teamed up to send COVID-19 at-home self-collection testing kits to homes in Las Vegas. Even something as simple as Google-sister company Wing’s coffee deliveries could make someone’s day if they can’t leave their home.
“With that backdrop, we’ve now built a solid foundation for what I think are some amazing things to come,” Dickson said. “We’ll be working on rules for BVLOS, beyond visual line of sight, and that’s really the holy grail of scalable drone operations.”
FAA chief Dickson came by way of a leadership role at Delta Air Lines, where he had spent the past nearly three decades. He graduated from the Class of 1979 at the United States Air Force Academy as well as Georgia State University College of Law. While on active duty, he flew the T-38 Talon supersonic jet trainer and F-15 Eagle fighter jet.
Continue reading: https://www.thedronegirl.com/2021/08/20/faa-chief-current-bvlos-rules/

Let me admit that I’m not sure what to make of Apple’s new patent filing (number 20210259045) for “authorization revocation for unmanned aerial vehicles.” I THINK it involves the ability to keep drones from flying over your property and/or accessing your Wi-Fi or cellular network. Read on and see what you think.
BACKGROUND OF THE PATENT FILING
According to techniques described in the patent filing, an unmanned aerial system traffic controller deployed in a cellular network may receive an request from a third party. That requests may be to revoke authorization for a currently registered and authorized wireless device that’s part of an unmanned aerial system connected with the cellular network. 
Based on the request, the cellular network may revoke authorization for the wireless device. The wireless device in the unmanned aerial system could be an unmanned aerial vehicle (drone) or an unmanned aerial controller. In the case of an unmanned aerial vehicle, the wireless device may be aerial or may be grounded when its authorization is revoked. 
If the wireless device is aerial, or possibly even if grounded, the unmanned aerial system traffic management function may navigate the wireless device to a desired location. This command could also include landing the wireless device. This may be accomplished by providing command and control messages from the unmanned aerial system traffic management function to the wireless device.
Continue reading: https://appleworld.today/2021/08/19/apple-patent-seems-to-involve-the-ability-to-boot-drones-from-your-property-or-network/

Every time you search for something in Google, artificial intelligence is working behind the scenes to generate responses to your query.
A deep learning system called RankBrain has changed the way the search engine functions. In many cases, RankBrain handles search queries better than traditional algorithmic rules that were hand-coded by human engineers, and Google realized a long time ago that AI is the future of their search platform. AI will try to understand exactly what we are searching for and then deliver personalized results to us, based on what it knows about us.
You may not realize it, but AI is already deeply integrated into many of the Google products you are using today. Here are a few examples:
“Hey, Google…”
Google Assistant is an AI-powered voice assistant for smartphones, smart home devices, cars, televisions, and wearables. Just like other virtual assistants, Google Assistant can manage your calendar, check the weather, play your favorite music, and find nearby restaurants to satisfy your culinary cravings.
So much of virtual assistant technology hinges on the assistant being able to understand what you’re saying, so Google is using machine learning to reduce language hiccups that can be frustrating for users.
For instance, your Google Assistant can learn how to accurately pronounce your contacts’ names without needing to record your voice. AI also helps Assistant understand context and process words in relation to all the other words in a sentence, so it can respond with almost 100% accuracy to things like alarm and timer commands.
AI and machine learning are also helping Google improve the quality of your conversations you can have with your trusted sidekick. Google Assistant uses your previous interactions to understand context and respond with appropriate follow-up questions, so you can have more natural, back-and-forth conversations.
Finding Your Way with Artificial Intelligence
Navigation has also been transformed by artificial intelligence. Using historic location data and recent search queries, Google Maps’s Driving Mode already anticipates your destination and helps you navigate there using the quickest route possible.
Continue reading: https://www.linkedin.com/pulse/how-does-google-use-artificial-intelligence-ai-bernard-marr/

Elon Musk wants Tesla to be seen as “much more than an electric car company.” On Thursday’s Tesla AI Day, the CEO described Tesla as a company with “deep AI activity in hardware on the inference level and on the training level” that can be used down the line for applications beyond self-driving cars, including a humanoid robot that Tesla is apparently building.
Tesla AI Day, which started after a rousing 45 minutes of industrial music pulled straight from “The Matrix” soundtrack, featured a series of Tesla engineers explaining various Tesla tech with the clear goal of recruiting the best and brightest to join Tesla’s vision and AI team and help the company go to autonomy and beyond.
“There’s a tremendous amount of work to make it work and that’s why we need talented people to join and solve the problem,” said Musk.
Like both “Battery Day” and “Autonomy Day,” the event on Thursday was streamed live on Tesla’s YouTube channel. There was a lot of super technical jargon, but here are the top four highlights of the day.
Tesla Bot: A definitely real humanoid robot
This bit of news was the last update to come out of AI Day before audience questions began, but it’s certainly the most interesting. After the Tesla engineers and executives talked about computer vision, the Dojo supercomputer and the Tesla chip (all of which we’ll get to in a moment), there was a brief interlude where what appeared to be an alien go-go dancer appeared on the stage, dressed in a white body suit with a shiny black mask as a face. Turns out, this wasn’t just a Tesla stunt, but rather an intro to the Tesla Bot, a humanoid robot that Tesla is actually building.
Continue reading: https://techcrunch.com/2021/08/19/top-five-highlights-of-elon-musks-tesla-ai-day/