The global AI market in 2021 reached a staggering value of $327.5 million. Meanwhile, 76% of businesses in a study by Algorithmia report a preference for AI learning over other IT objectives.
Clearly, AI is a topic of interest everywhere. It can maximize engagement with stakeholders while also helping companies run optimally.
What are the applications for AI in business?
Researchers are already studying the next form of AI. These changes in technology are also affecting leadership roles. Today, AI has a cross-domain presence. Here are a few areas being affected:
1. It enhances customer satisfaction.
AI delivers a unique marketing experience to customers. Many companies are investing in improving CX across the entire customer journey. One of the benefits of AI is its capacity to improve customer interaction. For instance, 82% of customers report having interacted with chatbots—a practice resulting in brand loyalty and higher conversion rates.
2. It can uncover new insights for business analytics.
Many businesses are combining AI and human decision-making to perform everyday tasks more efficiently and effectively. We already know that AI can remove manual actions with automation for flawless operations and improved productivity. But partnered with real-time data, it can also help companies monitor and simulate their processes, analyze potential outcomes and make the right decisions on time.
3. It provides automation for sales and marketing.
Utilization of AI in business accurately is growing increasingly crucial for sales and marketing teams. In its ability to automate mundane marketing tasks, it can enable the team to re-focus their time on business leads and client confirmations. It's also being utilized on social media to target advertisements based on market segmentation.
Continue reading: 
https://www.forbes.com/sites/forbesbusinessdevelopmentcouncil/2022/09/12/leadership-in-times-of-ai-driven-automation/?sh=5af4f9d227cb

A powerful new form of artificial intelligence has burst onto the scene and captured the public’s imagination in recent months: text-to-image AI.
Text-to-image AI models generate original images based solely on simple written inputs. Users can input any text prompt they like—say, “a cute corgi lives in a house made out of sushi”—and, as if by magic, the AI will produce a corresponding image. (See above for this example; scroll down for some more.)
These models produce images that have never existed in the world nor in anyone’s imagination. They are not simple manipulations of existing images on the Internet; they are novel creations, breathtaking in their originality and sophistication.
The most well-known text-to-image model is OpenAI’s DALL-E. OpenAI debuted the original DALL-E model in January 2021. DALL-E 2, its successor, was announced in April 2022. DALL-E 2 has attracted widespread public attention, catapulting text-to-image technology into the mainstream.
In the wake of the excitement around DALL-E 2, it hasn’t taken long for competitors to emerge. Within weeks, a lightweight open-source version dubbed “DALL-E Mini” went viral. Unaffiliated with OpenAI or DALL-E, DALL-E Mini has since been rebranded as Craiyon following pressure from OpenAI.
In May, Google published its own text-to-image model, named Imagen. (All the images included in this article come from Imagen.)
Soon thereafter, a startup named Midjourney emerged with a powerful text-to-image model that it has made available for public use. Midjourney has seen astonishing user growth: launched only two months ago, the service has over 1.8 million users in its Discord group as of this writing. Midjourney has recently been featured on the cover of The Economist and on John Oliver’s late-night TV show.
Continue reading: https://www.forbes.com/sites/robtoews/2022/09/11/4-hot-takes-about-the-wild-new-world-of-generative-ai/?sh=3c727ee613d9

The 21st century has made many impossible things possible. It has taken us to a day where the physically impaired walk and the deaf hears and responds. It is not a miracle, but technology is making extraordinary changes. According to the World Health Organization (WHO), about 15% of the world’s population (over one billion people) have some kind of disability. It is not a good idea to have people guide and help them throughout their life. Fortunately, technology has come to their rescue. Artificial intelligence (AI) is the development of computer systems that are able to perform tasks that normally require human intelligence. With the help of AI and its applications, people with disabilities can live normal life like everybody. Unlike others, people with disabilities see artificial intelligence as a light at the end of the tunnel. In the developing era of technology, the gap between people with disabilities and the world keeps narrowing.
Artificial intelligence directly impacts disabled people’s lives in three ways- enabling communication, enhancing accessibility, and providing the advantage to live independently. People with no disabilities might take Alexa, Echo, and Siri as a device that plays songs, book tickets, tell weather conditions, etc for us. But for people with disabilities, these voice-assisted AI technologies are one of the major advanced ways of communication. Visually impaired people use voice assistants to communicate with the world. Similarly, speech-to-text transcriptions and text-to-speech conversions are also availed for impaired people to address their physical issues. Accessibility is a major concern for people with disability. A person in a wheelchair or a visually impaired individual can’t travel to certain places without the help of others. However, an advanced navigation system tracks locations and says where a wheelchair can be easily accessible. Meanwhile, visually impaired people use recognition technology to identify what is around them, especially, signboards, traffic signal color, zebra crossing, etc. The smart home is a futuristic technology that is seeing high adoption among people in recent days. Fortunately, the AI-assisted devices in a smart home enable people with disability to live independently.
While a lot of AI applications are deployed at various places to make people with disabilities live normal life, some of the technologies have direct positive impacts on them. AI solutions leverage more than just comfort. It makes an absolute environment where impaired people can show equal potential to others. AI-powered applications are able to equate visually or physically impaired workers with the rest of the employees by giving them an opportunity to even operate in the workplace.  A sophisticated device called Orcam My Eye 2 is capable of reading books, recognizing faces, and even recognizing the value of money and some other common items. This advanced device uses technologies such as AI, OCR (optical character recognition), and machine learning. Extended Reality (XR) is an emerging umbrella term for all immersive technologies like augmented reality (AR), Virtual Reality (VR), and mixed reality (MR). By availing of XR, people with motion disabilities can carry out assignments and work tasks remotely. Robots also play a big role in helping people with disabilities. Starting from robotic arms and prosthetic legs to assistant vehicles and automatic devices mounted on wheelchairs, robotics is remarkably making its stance. ReWalk company, a well-known health technology provider makes robotic products and services that help in rehabilitation.
Continue reading: https://www.analyticsinsight.net/artificial-intelligences-impact-on-the-lives-of-people-with-disabilities/

Artificial Intelligence has become commonplace in the lives of billions of people globally. Research shows that 56% of companies have adopted AI in at least one function, especially in emerging nations. That’s six percent more than in 2020. AI is used in everything from optimizing service operations through to recruiting talent. It can capture biometric data and it already helps in medical applications, judicial systems, and finance, thus making key decisions in people’s lives.
But one huge challenge remains to regulate its use. So, is a global consensus possible or is a fragmented regulatory landscape inevitable?
The concept of AI sparks fears of Orwell’s novel “1984” and his “Big Brother is Watching You” notion. Products based on algorithms that violate human rights are already being developed. So now is the time to talk, to put in place standards and regulations to mitigate the risk of a society based on surveillance and other nightmarish scenarios. The US and the EU can take leadership on this matter, especially since both blocks have historically shared principles regarding the rule of law and democracy. But on either side of the Atlantic, different moral values underpin principles, and they don't necessarily translate into similar practical rules. In the US emphasis is on procedural fairness, transparency and non-discrimination, while in the EU the focus is data privacy and fundamental rights. Hence the challenge of finding common rules for digital services operating across continents.
Why AI Ethics Is Not Enough
Not all uses of AI are savory or built on palatable values. AI could become ‘god like’ in nature: Left to its self-proclaimed ethical safeguards, AI has been shown to be discriminatory and subversive. Consider for a moment, the AI underlying the so-called ‘social credit’ system in China. This ranks the Chinese population whereby those considered untrustworthy are penalized for anything from jaywalking through to playing too many video games. Punishments include losing rights, such as the capability to book tickets, or limiting internet speed.
Imposing mandatory rules on AI would help prevent technology infringing human rights. Regulation has the potential to ensure that AI has a positive, not negative effect on lives. The EU has proposed an AI Act, intended to address these types of issues. The law is the first of its kind by a large regulator worldwide, but other jurisdictions like those in China and the UK are also entering the regulatory race to have a say in shaping the technologies that will govern our lives this century.
Continue reading: https://www.forbes.com/sites/hecparis/2022/09/09/regulating-artificial-intelligence--is-global-consensus-possible/?sh=20d025567035

Marketing is one of the areas of business operations where it is widely predicted that artificial intelligence (AI) will drive enormous change. In fact, a McKinsey study found that, along with sales, it is the single business function where it will have the most financial impact. This means that if you’re a marketer and you’re not using AI, you’re missing out on the benefits of what is possibly the most transformational technology.
Actually, though, the chances that there are people out there doing marketing today and not using AI in any shape or form is somewhat unlikely. This is simply because there are so many tools with AI features that we are used to using without even thinking about it. The most frequently used social and search engine advertising solutions, email marketing platforms, e-commerce solutions, and tools designed to assist with content creation all provide functionality that taps into what we refer to as “AI” in business today. To be clear, this isn’t what we think of as “general” AI – machines that have the capability to think and communicate like us and turn their hands to just about any task. In business today (and in marketing in particular), AI refers to software that helps us to carry out one particular job – such as identifying where to place advertising in order to maximize efficiency or how to personalize an email to increase the likelihood of receiving a reply – and get better and better as it is exposed to more data.
However, it’s my experience that, while there may be many tools out there and most marketers are increasingly comfortable with using them on a day-to-day basis, it’s often done in an ad-hoc manner. Many marketing departments still lack a coordinated, strategy-focused approach to implementing bigger projects. Just as importantly, many are lagging when it comes to fostering an AI-friendly, data-first culture as well as developing competencies and upskilling in order to meet the skills demand.
Paul Roetzer, founder and CEO of Marketing AI Institute and author of the new book ‘Marketing Artificial Intelligence’, told me that this is true in his experience too. In fact, when recently setting out to check up on his own hunch by searching for mentions of AI terminology in connection with 50 of the world’s top chief marketing officers, he found that only four of them had spoken publicly or been connected with their use of AI.
“My question was, who is leading this? Who is doing this within marketing?
Continue reading: https://www.forbes.com/sites/bernardmarr/2022/09/09/artificial-intelligence-and-the-future-of-marketing/?sh=7017fa8b697f

Here at GoDaddy, we truly believe that diverse teams, built with all employees, build better products and make for a better place for us all to work. We strive for equality for all of our employees, regardless of gender, race, and sexual orientation. We’re among the first companies to announce and publish our gender pay parity results and have achieved pay parity in nearly all areas of our business.
One of our most prominent Employee Resource Groups (ERG for short) is GoDaddy Women in Technology (GDWIT, clearly we like acronyms here)!
This group’s sole mission is to be an inclusive community that empowers our women to connect, learn and grow. It provides a network of support, tools, learning opportunities, and visibility into what it’s like to be a woman at GoDaddy.
We connected with a few of our Women in Tech to hear about their GoDaddy Life experiences.
Why do you like being a part of GDWIT?
Alycia Leno: “ This is a place to share experiences and learn from others to help grow my career and take better care of myself.”
Jena Coffey: “GDWIT has been a way for me to engage with other women within the organization that I would not otherwise meet. When I began getting involved, I was looking for a way to feel connected while learning more about the different facets of GoDaddy. I found that and so much more! I found friends, learning opportunities, and career growth as well. I know that no matter what I am going through, either professional or personal, there is always someone in GDWIT willing to listen or share their experiences with me. All of this has given me support in ways that I never even imagined an employer could provide.”
Continue reading: https://www.yahoo.com/now/striving-close-workplace-gender-gap-140008724.html

Susan Jeffers, founder and CEO of XY Retail, founded the company when she realized that retailers, and particularly luxury retailers, were struggling to manage the post-pandemic shift back to in-store as well as facing a lack of innovation on the e-commerce side.
XY Retail is an omnichannel platform that helps luxury retail brands manage everything from in-store payments, to online orders and returns, in-store customer experiences and mobile clientelling.
XY Retail recently raised a new funding round and is already driving enormous value – for instance luxury brand ISAIA was able to reduce return times from three minutes to less than a second and improve online order fulfillment speeds by 300 percent.
“I originally from India moved to Silicon Valley, as a kid, by myself,” said Jeffers XY Retail CEO. “I love everything retail. I also got hired by another startup. I got the startup up and running, and then started my own company.
“It’s a lot of consulting with Fortune 500 companies,” Jeffers added. “I invested a lot of my time and money into understanding the technology of retail. The big hospitality guys all have this same problem. They can throw money at the problem, but if I’m in the store, I’m dealing with five different systems.
“Given the cloud economics they needed a platform like an AWS, but they couldn’t afford it,” Jeffers said. “I need a Ferrari but I can’t afford a Ferrari. The Covid-19 pandemic actually allowed us to connect the two sides, supply and demand. Covid-19 activated our growth online.
Jeffers said that for most brands and businesses, customers didn’t immediately come back to the stores. Employees have access to the data and that elevates the customer experience. But, the access to customer data, was built for in-store.
Continue reading: https://www.forbes.com/sites/sharonedelson/2022/09/08/xy-retails-susan-jeffers-helps-brands-innovate-on-the-tech-front/?sh=c23b1bb31ccd

Five years ago, Nishi Kaura’s family vacation to India included a visit to a girls orphanage. Meeting some of the girls and learning that they wanted to pursue careers in tech and achieve financial independence, Nishi was inspired to help.
She started small, with fundraising efforts and spreading online awareness about technical education for underserved groups. After raising a few thousand dollars, Nishi donated resources such as laptops and developed technical literacy curriculums to teach the girls. Nishi continued supporting the girls for the next few years by teaching technical literacy.
WHAT INSPIRES YOU TO VOLUNTEER?
After meeting the girls at the orphanage, I realized that taking collective action towards making technology equitable is so important to unlocking the futures of underserved people, especially women.
Seeing the enthusiasm in the girls’ eyes and knowing the obstacles they faced to a fulfilling and prosperous life, I was inspired to create ChiCode, a tech-forward nonprofit that aims to dismantle existing societal barriers surrounding minority groups in tech.
DESCRIBE YOUR VOLUNTEER ROLE WITH CHICODE.
I am head of the Social Media and Workshops department. I founded the podcast segment and developed the Intro to Java, Advanced Java and Slides Presentations courses.
ChiCode has worked with 300+ students from over 13+ countries with the support of ten companies. We have worked with many different underrepresented groups in tech including migrant domestic workers in Singapore, refugee women from Iran and Congo living in Greece, South Africa women, people from villages in Brazil and more.
Continue reading: https://www.pointsoflight.org/awards/a-bright-new-future-starts-by-empowering-girls-in-the-tech-space/

As Covid-19 overwhelmed hospitals, another deadly epidemic raged in the background. One that became exasperated by the hardships of Covid-19 and led to over 200,000 deaths in 2020 and 2021 combined: drug abuse.
Despite being on a steady decline since 2017, overdoses increased 30% from 2019 to 2020 and 15% from 2020 to 2021, with synthetic opioids like fentanyl responsible for most of those fatalities. These spiking numbers underscore another emergency that no hospital is immune from—drug diversion: the theft of medications intended for patients.
But as this crisis evolved, so did technology. Now, more hospitals are realizing the benefits of advanced computing and artificial intelligence, which may be critical in stopping drug diversion for good.
The Widespread Costs Of Drug Diversion
The drug diversion issue spans over two decades—in part due to the lack of concrete regulations from the Drug Enforcement Administration (DEA). While the DEA expects hospitals to complete an audit and report known diversion cases, no proactive monitoring is required.
But the problem is far more severe than the lack of regulations makes it seem. In fact, 10% to 15% of healthcare providers in the U.S. will misuse drugs or alcohol throughout their careers. The harm caused only spirals from there: Patients are deprived of medication, clinicians under the influence can cause harm when treating patients, they may sell drugs to third parties and some cases even become fatal. Two nurses were found dead in a Texas hospital from a fentanyl overdose that was supposed to be administered to a patient. The hospital later faced a $4.5 million fine for lack of oversight.
Continue reading: 
https://www.forbes.com/sites/forbestechcouncil/2022/09/08/combatting-drug-diversion-with-artificial-intelligence/?sh=e9f1f4d2193c

Businesses across industries are increasingly using artificial intelligence in a variety of ways to improve their internal operations, from handling repetitive tasks to interpreting data to streamlining overall processes (and more). For many companies, however, the primary benefit of AI is its potential to help them better interact with customers.
Many consumers may think companies use AI simply for their own ends—for example, most of us are aware that AI plays a role in the ads we see online. However, many businesses leverage AI’s learning abilities to try to make interactions and transactions faster and easier for the customers they serve, thereby improving the overall customer experience. Here, 12 members of Forbes Technology Council share ways AI is transforming and improving businesses’ interactions with their customers.
1. Reducing ‘Decision Overload’
AI can improve the customer experience by reducing “decision overload.” In this day and age of seemingly endless options and expectations of receiving gratification as quickly as possible, decision fatigue is a huge threat to every business. AI is being implemented to hyper-select your choices—sifting through thousands of options using its deep understanding of you as a consumer and reducing them to a manageable number. All of this is done in microseconds, behind the scenes. - Adrian Dunkley, StarApple
2. Detecting Unusual Behaviors And Events
AI helps businesses detect anomalies. When something has changed in a customer’s environment, that change can be silently detected and flagged. The clearest example is credit card fraud alerts, but it is also important to recognize if a customer’s bill is increasing above their budget. This detection service provides confidence and an opportunity for the service provider to engage with the customer to discuss the alert. - Christopher Larkin, Concord Technologies
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/09/08/12-ways-ai-is-transforming-how-businesses-interact-with-customers/?sh=577272755224

It’s 2022, and yet, I and many others who are advocates for diversity and inclusion (D&I), particularly in STEM, still have to push for this movement.
Despite visible efforts to make progress on D&I, we still haven’t moved the needle. According to a 2021 report on diversity in the United States tech industry, “68% of businesses are aware of a continuing lack of diversity in their tech teams. Of those, 46% are actively trying to address the issue.”
But even surveys on D&I in the tech industry don’t account for all under-represented groups. Just take a look at Dice’s 2021 Equality in Tech report, where they surveyed technologists on pressing issues, such as compensation and burnout. The Middle Eastern and North African (MENA) community wasn’t acknowledged. However, other underserved groups were.
This is a serious issue that by no means only applies to Dice. In fact, look at the diversity reports of most major tech companies in the U.S., and you won’t find a MENA category for their workforce statistics.
This lack of MENA representation is indicative of a more widespread problem I’ve seen in the U.S. tech industry: Companies hire people of MENA descent—after all, it’s a community filled with lots of talent, particularly when it comes to women. According to 2015 UNESCO figures, Saudi Arabia, Iran, Algeria and Oman had 65% and above of their female students “enrolled in natural science, mathematics and statistics” higher education programs.
However, these companies then don’t meaningfully invest in their employees of MENA descent. It’s not a stretch to say that people of MENA descent probably don’t even factor into corporate D&I strategies. This needs to change now—it’s 2022.
As the founder and CEO of a nonprofit focused on amplifying MENA women in the tech industry, I urge all tech companies to consider the following questions.
Continue reading: https://www.forbes.com/sites/forbesnonprofitcouncil/2022/09/07/mena-the-invisible-community-in-tech/?sh=7a119ae7725a

WASHINGTON, DC – The US Department of the Treasury’s Office of Foreign Assets Control recently sanctioned a technology called Tornado Cash, on the grounds that it “has been used to launder more than $7 billion worth of virtual currency since its creation in 2019.”
Such enforcement measures are nothing new. But what makes this case unique is that Tornado Cash is a piece of open-source software.
Essentially an automated tool, Tornado Cash mixes digital assets and redistributes them to preserve privacy. While we don’t know everything about Tornado Cash or why it was created, we do know that large sums of digital assets linked to illicit activity have moved through the protocol since it was launched, including millions stolen by North Korean hackers. Any American who uses the service now faces up to 20 years in prison.
Some believe that such sanctions are necessary to prevent money laundering, while others see them as a sign of government overreach. But whatever one’s perspective, it’s worth asking why there was a need for a protocol like Tornado Cash in the first place. The short answer is that our financial system is failing to balance privacy and security. Fortunately, this is a challenge that web3 (blockchain) technologies could help to resolve.
As a senior adviser to two US secretaries of state, I spent time in dozens of countries examining how different systems affect individual rights and democracy, and helping to design technologies and applications to strengthen open societies. In the course of this work, I have seen today’s finance systems failing by virtually every measure. More than a billion people worldwide – including millions in the US – lack access to basic financial services. Many cannot pay their bills or send money to family because they don’t have a bank account or identification, and others simply don’t trust financial institutions.
Continue reading: https://www.project-syndicate.org/commentary/web3-improve-financial-system-for-privacy-security-and-law-enforcement-by-tomicah-tillemann-2022-09

The blockchain and crypto sector is undoubtedly going through difficult times, with the market falling $2 trillion since its November 21 peak. An overwhelming negative sentiment is shrinking the industry’s resources while weekly outflows amount to $102 million.
The Crypto Fear & Greed Index shows that investors remain “fearful” of the current bear market conditions. But history teaches us that this lack of hype and market exuberance actually provides fertile conditions for developing innovative technological solutions.
When the DotCom Bubble burst in the early 2000s, companies like Amazon, e-Bay, Google, Facebook, and Cisco all survived the crash. Indeed, they emerged from the crash stronger because their developers continued building instead of allowing volatile markets and negative sentiment distract them. Similarly, crypto projects like Tron, ChainLink, Polkadot, and EOS, were able to survive the 2017 ICO craze and the crypto winter that followed.
Bear markets have historically filtered out opportunists and stupid capital to make way for real innovators delivering scaleable market solutions and longer-term investor growth.
Nevertheless, bear markets also entail a shortage of capital as investor disappear or sit on the sidelines and liquidity disappears from the market. Only a handful of serious project developers, entrepreneurs, and long-term investors stay back to support each other.
These stakeholders require a space where they can connect, collaborate, and build cutting-edge technologies to sustain themselves and the industry overall. Incubators, launchpads, and accelerators become crucial resources for entrepreneurs, companies, and developers during a bear market.
Incubating Startups, Accelerating Growth
Incubators can be essential to a company's long-term survival and success. The National Business Incubator Association reports that 87 percent of incubated startups continue to survive after five years—twice the success rate of startups that develop completely on their own. Moreover, 84 percent of incubated companies share the incubator’s community, creating a wide but well-knit network of entrepreneurs, advisors, developers, and investors, however, community support is just one aspect of incubators.
Continue reading: https://www.forbes.com/sites/lawrencewintermeyer/2022/09/08/web3-developers-can-thrive-in-the-bear-market-with-the-right-support-services/?sh=3ae3522a1a1f
 

Over my 20-plus year career, I have worked for a variety of media companies across a range of industries including telecom, video gaming and music. The common thread across all of these industries is that they were fundamentally transformed by the digital revolution.
Nowadays, no one thinks twice about listening to music on YouTube or buying albums on iTunes. (Full disclosure: YouTube and Apple are commercial partners to my company for music distribution.) However, I can still remember when buying CDs (or even tapes!) at a record store was the norm and digital distribution was a new, confusing and even intimidating idea to the average consumer. I see many similarities between the emergence of the internet in the 2000s and the early applications of blockchain in 2022.
In this piece, I will outline a few ways that blockchain is already being used within the industry, in the hopes of providing a jumping-off point for professionals to begin exploring this emerging space.
Blockchain-Based Crowdfunding
Traditionally, fans have supported artists by buying their records, streaming their music, going to their concerts and buying their merch. All of these actions have two things in common: Someone other than the artist typically ends up with most of the money, and there is no further engagement or connection between the fan and the artist. Consumers put money in, the revenue goes to a company and some percent of that revenue trickles down to the artist. The end.
My company and others are working on blockchain based crowdfunding platforms to provide a powerful solution to this problem. Cryptocurrency can facilitate the direct transfer of value between fans and artists, while the use of NFTs and smart contracts ensure that there is an accurate record of all transactions and the rules governing these transactions are enforced. The way in which the end user benefits varies from platform to platform, but in every case the artist receives funding, and the fan receives some benefit in return.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/09/07/how-blockchain-could-transform-the-music-industry/?sh=3b0269b36192

The US Department of the Treasury’s Office of Foreign Assets Control recently sanctioned a technology called Tornado Cash, on the grounds that it “has been used to launder more than US$7 billion worth of virtual currency since its creation in 2019”.
Such enforcement measures are nothing new. But what makes this case unique is that Tornado Cash is a piece of open-source software.
Essentially an automated tool, Tornado Cash mixes digital assets and redistributes them to preserve privacy. While we don’t know everything about Tornado Cash or why it was created, we do know that large sums of digital assets linked to illicit activity have moved through the protocol since it was launched, including millions stolen by North Korean hackers. Any American who uses the service now faces up to 20 years in prison.
Some believe that such sanctions are necessary to prevent money laundering, while others see them as a sign of government overreach. But whatever one’s perspective, it’s worth asking why there was a need for a protocol like Tornado Cash in the first place. The short answer is that our financial system is failing to balance privacy and security. Fortunately, this is a challenge that Web3 (blockchain) technologies could help to resolve.
As a senior adviser to two US secretaries of state, I spent time in dozens of countries examining how different systems affect individual rights and democracy, and helping to design technologies and applications to strengthen open societies. In the course of this work, I have seen today’s finance systems failing by virtually every measure.
Continue reading: https://www.scmp.com/comment/opinion/article/3191766/financial-services-must-harness-blockchain-balance-digital-security

A look at why gas fees can be so expensive and the different ways platforms and users are tackling the high costs.
High transaction fees have been a long recurring issue for users on popular blockchain networks like Ethereum and Bitcoin during periods of increased demand. However, there are protocols, platforms and methods that help users to reduce costs.
What are transaction fees?
Transaction fees are fees that users pay to send a transaction or interact with a smart contract on a blockchain network. While gas fees can refer to transaction fees on any blockchain, the term is mainly used to describe the Ethereum network transaction fees.
Transaction fees are paid in small fractions of the network’s native cryptocurrency. For example, with Bitcoin (BTC), users will pay in Satoshi’s (very small fractions of BTC), and with Ether (ETH), they will pay in gwei.
There are two main reasons users need to pay fees when sending a transaction. The first reason is to pay miners or validators (also known as nodes) for securing the network. Proof-of-work (PoW) blockchains have miners who validate transactions by using their computing power to solve complex algorithms. In contrast, proof-of-stake (PoS) blockchains have validators who stake their tokens to secure the network.
In return for securing the network and ensuring that no fraudulent transactions are placed, these nodes are compensated with transaction fees on the blockchain. Network validators make it possible for the blockchain to operate in a decentralized manner without having to rely on centralized entities to ensure that no malicious activity takes place on the network.
Continue reading: https://cointelegraph.com/news/how-high-transaction-fees-are-being-tackled-in-the-blockchain-ecosystem

WeatherXM has deployed over 700 decentralized weather stations around the world to harvest local data, which provides station owners with utility tokens in return.
Blockchain and crypto are coming to a local weather station near you — or at least that’s what one group of Athens-based engineers is trying to accomplish. WeatherXM is using a combination of blockchain-based data verification with crypto incentives to get people worldwide to capture their local weather data for more accurate forecasting.
Cointelegraph sat down with WeatherXM co-founders, CEO Manolis Nikiforakis and chief technology officer Nikos Tsiligaridis for an interview in Athens, Greece. They talked about how Web3 tools provide the best solution to the lack of quality and the quantity of available weather data.
The company is deploying a new infrastructure of community-powered weather stations built with blockchain-based oracle hardware. It creates smart contracts of information gathered from localized weather stations, from which decentralized weather data is produced. The smart contracts verify both the location of the station and the nonfungibility of data collected from the location. 

“Then we monetize those services and put the value back into the original people who created the data in the first place, which are the weather station owners, who we call weather miners,” says Nikiforakis.

Click to expand...

The native utility tokens of the network are WXM and Data Credits (DC).
Continue reading: https://cointelegraph.com/news/blockchain-and-crypto-find-use-case-in-community-powered-weather-forecasting

According to Jason Thibeault of the Streaming Video Technology Alliance, advances in edge computing have changed the streaming ecosystem in ways that require cooperation between CDN competitors in order to best serve the needs of their end users

In Episode 7 of the Cutting Edge podcast, Leonard Lee explains the meaning of peer-to-peer edge computing, its potential applications and the inevitability of widespread adoptions as the technology grows more economically viable.
Highlights
00:23 – Leonard Lee introduces today’s topic of discussion: Peer-to-peer edge computing.
What Is Peer-to-Peer Edge Computing?
00:44 – With all the talk of “cloud,” edge computing is usually assumed to involve offloading or downloading from a cloud or Edge server to an endpoint client.
01:12 – Lee describes Peer-to-peer edge computing as “an archetype of distributed computing architecture that shares functions or workloads across peer devices.”
01:57 – Peer-to-peer edge computing allows the sharing of resources to perform more collaborative functions without tapping into edge architecture.
What Are Some Good Examples of Peer-to-Peer Edge Computing?
02:53 – Lee explains the AI concept “Swarm Intelligence.” One application of peer-to-peer computing in transportation can be seen in smart vehicle “platooning,” wherein a group of vehicles coordinate their positions relative to one another on a road to enhance fuel efficiency and safety.
03:30 – Lee details “CV to X,” or “cellular vehicle to everything” communications.
04:12 – Further applications of peer-to-peer edge computing include smart intersections, which share real-time contextual information to improve traffic efficiency and pedestrian safety.
Key Takeaways for the C-Suite
04:50 – As more intelligent end-point devices populate the edge, applications relying on time-sensitive synchronized actions through coordinated devices become more effective and viable.
Continue reading: https://accelerationeconomy.com/edge-computing/how-peer-to-peer-edge-computing-could-impact-traditional-infrastructures/

Edge computing is the next step forward beyond cloud computing. More organizations are looking to bring the cloud closer or distribute their computing resources across broader networks as data demands rise. This shift to the edge has many advantages, but it can also be a complicated transition.
The first step to making the most of the edge is understanding the different types of edge computing. Edge networks come in various shapes and sizes, each with unique advantages and disadvantages. Global spending on edge computing is expected to reach $176 billion this year, so learning which of these best fits your needs and goals is critical.
Edge Types by Technology
There are many ways to classify edge technologies and networks. As a result, there’s no conclusive answer to how many types of edge computing exist or what those categories are.
One of the easiest ways to divide edge is by the systems and platforms on which the computing happens. Here are some of the most common categories by that definition.
Cloud Edge
The cloud edge is the first type of computing under this classification system. As the name implies, these networks more closely resemble traditional cloud computing. They use large data centers, but unlike conventional approaches, these centers are relatively close to end-users and often serve purpose-built applications.
These systems offer impressive latency improvements while maintaining the conventional cloud’s capacity. While 58% of cloud users in some scenarios could achieve latencies under 10 milliseconds with nearby edge data centers, only 29% can do the same with a traditional cloud data center.
However, these deployments can be more expensive and aren’t accessible to everyone, as they rely on available data centers in your area. Consequently, they’re best suited for larger enterprises or operations with high data demands nearby existing infrastructure.
Continue reading: https://www.enterprisenetworkingplanet.com/data-center/types-of-edge-computing/

Software application developers are often thought of as loners, mavericks and reclusive types, fond of working in solitary environments — if there were a parallel for life out on the edge, programmers would already embody it, giving software engineers a natural affinity for coding in edge computing environments.
All developers are the same. It’s a contentious statement, but at least it does apply if we agree that all software application developers are creatures of habit: They all have an exhaustive approach to detail, they share a naturally analytical brain type adept at problem solving, and most have a slightly unnerving predilection for soda and pizza.
But of course, all developers are not the same. Some are focused on upper “presentation layer” interfaces, some are networking specialists, some are core platform gurus focused on functionality and performance, while still others are systems architects, penetration testers, data science champions and so on.
But developers are not only classified by nature of their engineering specialism, they are also distinguished by virtue of the implementation surface that their work is applied to. Some will focus on smartphones, some on desktops, some on embedded systems and some on cloud-native applications that could potentially span every domain.
Embedding the evolving edge
Within that last cadre of coders, we find the oft-unloved embedded computing stalwarts. Close in mindset to edge developers, embedded developers are not quite the same, as they have had their role quite historically defined to focus on everything from home heating systems to fitness trackers and perhaps even your television remote control.
But as we know, those embedded devices themselves are now straddling the Internet of Things. Airport kiosk computers are processing in real-time, in-car systems are now hooked up to a web connection, transit and fare collection machines have an intermittent link to the cloud, and factory robots and medical systems now operate in an always-on, always-connected data plane.
Some embedded computing will still be known as embedded computing, but many of these devices — and, specifically, the sensors and gauges within them — will now form the structure of what we refer to as the computing edge. This is how edge is different to embedded and different to distributed computing. These are not just machines that are moving out of the data center, these are machines doing a specific job.
Continue reading: https://www.techrepublic.com/article/edge-computing-developer/

All kinds of devices and systems are using edge computing systems in the business world and the everyday. The edge is changing how everyone processes data, but it is facing some key challenges. Here’s a look at the hurdles it must overcome and the trends pushing it forward.
What is edge computing?
Imagine pressing your thumb to the touch ID sensor on your smartphone and waiting five or 10 minutes for it to unlock. Thanks to edge computing, this isn’t necessary. It’s a vital part of all sorts of systems and devices today, from cellphones to automation control systems in manufacturing plants.
Edge computing essentially consists of keeping computing devices as close to sensors and systems as possible. For instance, instead of having an automation system send information to a data center for processing, it’s done immediately by computing infrastructure just a few feet away. The idea is to reduce the time required to process and react to data as much as possible.
Edge computing challenges
Edge computing is a revolutionary technology, but it is still relatively new. Engineers and programmers are still working out a few key challenges.
Security
Security is a major concern today for all types of technology. Cyberthreats have been rising over recent years alongside the cost of successful attacks. In 2021, there was a 105% global increase in ransomware attacks alone. The range of these cyberattacks is growing, with targets no longer limited to big-name brands or large data centers.
Hackers also tend to take advantage of newer technologies, betting that they are less likely to have adequate security infrastructure. Edge computing can make systems more secure by keeping processing local. However, the infrastructure and devices themselves need their own security measures. This includes access control, traffic monitoring, and data backup and protection protocols.
In the future, edge computing devices and processors must have dedicated security protocols built in and may even need their own onboard antivirus and anti-malware software. Encryption from sensors and devices to edge computing processing may also help.
Hardware
Another major challenge facing edge computing is hardware. Edge computing requires some baseline infrastructure to operate successfully, such as adequate bandwidth and data storage space.
With computing going on locally and running so quickly, edge computing needs plenty of bandwidth to avoid experiencing bottlenecks. It also leads to large amounts of information being processed locally that must be stored. It could remain at a large data center if it were still being processed there. That may not be an ideal solution for edge computing, though.
Continue reading: https://www.techrepublic.com/article/trends-challenges-edge-computing/

The data race is not only heating up but rapidly shifting toward real-time data, according to a new report by data management firm DataStax.
This was the conclusion of the “The State of the Data Race 2022” report based on an in-depth survey of more than 500 technology executives and technical practitioners in the U.S. about their data strategies.
According to DataStax, real-time data is the data that powers in-the-moment use cases such as recommendations and personalization, or always-up-to-date inventory and logistics.
Benefits of real-time data
The report found that real-time data leads to increased revenue growth and improved developer productivity.
Specifically, almost four out of five (78%) of all respondents agreed that real-time data is a “must-have,” not a “nice-to-have.” Moreover, 71 percent of all respondents said that they can tie their revenue growth directly to real-time data.
The advantages of real-time are even more pronounced in organizations that excel at leveraging data to create new products and revenue streams.
For organizations that make real-time data a strategic focus, 42 percent experience a transformative impact on revenue growth, compared to only 18 percent of those organizations that don’t prioritize real-time data.
Other transformative impacts experienced by real-time data leaders include improved customer satisfaction (34%) and increased market share (31%).
The effects of real-time data go beyond improving revenues. When asked how the use of real-time data has impacted developers’ jobs, two-thirds (66%) of organizations with a strategic focus on real-time said that developer productivity improved.
Continue reading: https://www.cdotrends.com/story/17147/study-finds-link-between-use-real-time-data-revenue-growth?refresh=auto

Machine learning (ML) is at the peak of popularity right now. This branch of artificial intelligence is attracting more and more investments, and its market value is growing at a rapid pace.
As a result, from over $21 billion in 2022, the machine learning market will likely reach more than $209 billion in 2029! It’s an indicator of annual growth of almost 39%.
Even though many businesses are actively adopting this innovation to keep up with the competition, some companies are still hesitant. Today we’ll convince you why business owners should step out of their comfort zone and hire a machine learning developer.
We’ll discuss ML in general and provide the reasons and benefits of implementing this innovation into your business processes. Today’s article will also explain what skills a decent machine learning engineer should have.
What Is Machine Learning?
Machine learning is often confused with artificial intelligence or used interchangeably. These terms certainly relate to the same field, but let’s figure out what ML means.
Machine learning is a branch of artificial intelligence and the most common application of AI. These are algorithms that enable software products to perform a given task more precisely or forecast outcomes more accurately. It becomes possible thanks to this technology’s ability to process data: the more data available to ML, the more accurate the predictions and performance of tasks.
ML is the technology thanks to which artificial intelligence can work. Machine learning is a way to teach machines to process, analyze information, and draw conclusions based on it.
A recommendation engine is the most typical use case for ML. It’s software that analyzes data and makes assumptions. In addition, machine learning is used to detect software threats, fraud, spam filtering, or business process automation.
Continue reading: https://business-review.eu/tech/what-5-benefits-a-machine-learning-developer-can-bring-to-your-business-235046

Artificial Intelligence (AI) is enabling Print Service Providers (PSPs) to make some exciting changes to their production processes. It is helping them reevaluate their operation and introduce performance benefits that future-proof their business. The impact AI can have was recently discussed by my colleague Clive Stringer in this blog. He highlighted how an AI solution can drive continual improvement through a core set of capabilities that grow as it learns the types of print jobs being run. Traditional software by contrast can complete only what it is programmed to perform. Clive explored how AI powers growth through pattern recognition and learning by correction. It can handle much broader capabilities than traditional or rules-based programs and is able to learn from mistakes. He also considered how AI responds to new, unexpected, situations, making it ideal for real world applications where anything can happen. The operation-wide ability to learn and revise processes is a core benefit of Ricoh’s brand new Pro VC70000e. The high speed inkjet press produces exceptional quality, image driven, customized marketing, direct mail, and publishing applications. The Ricoh Pro Scanner Option and RICOH Supervisor in Ricoh’s Automation Suite simplify operation and give greater feedback to help shape key business decisions. The Ricoh Pro Scanner Option, also available for the Ricoh Pro VC70000 and Ricoh Pro VC60000  high speed inkjet presses, identifies details that improve performance and consistency. It decreases manual touchpoints and increases overall efficiency through predictive analytics. It monitors production to check on the machine’s condition and the quality and accuracy of the printed content. It looks for ways to improve future production including monitoring if preventative maintenance should be planned, and helps automate a variety of labor intensive and time consuming tasks, such as printhead cleaning, paper profiling and even daily startup routines.
Continue reading: https://www.labelandnarrowweb.com/contents/view_experts-opinion/2022-09-07/why-its-time-to-future-proof-with-artificial-intelligence/