Lynsey Jackson was looking for a change when she quit her corporate finance job to assess her career options, before settling on a direction that would shock many.
She sees her future in blockchain technology, beginning with a diploma of applied blockchain from TAFE Queensland.
Most commonly known as the platform that hosts cryptocurrencies, blockchain is the basis of "Web3", the brave new internet held together by distributed databases, each confirming the same information.
Blockchain is a peer-to-peer security network that allows users to become part of the system.
In relation to cryptocurrencies the system validates coin ownership and transactions, as well as works to create new coins.
"Most people when I mention that I'm pivoting my career into blockchain don't really know what I'm talking about and what the opportunities are ... for the most part, people in my world are pretty unaware," Ms Jackson said.
"It can improve things like tracking and traceability and reducing fraud … We can use that sort of technology to make the world a more fair and inclusive and sustainable place for everyone."
As for what she wants to do in the industry?
"That is the million-dollar question," she said. "That's why I've enrolled in the diploma."
Ms Jackson first learned of blockchain the way most do: cryptocurrency.
According to CHOICE, one in nine Australians invested in a cryptocurrency within the last 12 months and a further 11 per cent are interested in investing.
But Ms Jackson, who "holds" investments in some of the major coins, said that isn't what drew her to study the technology.
"What's actually happening in the blockchain space is far beyond just what we know about Bitcoin and cryptocurrency and an opportunity to get rich quick," she said.
Continue reading: https://www.abc.net.au/news/2022-06-20/shell-for-date-tbc-qld-blockchain-jobs-of-the-future-julius-denn/101123884

Since the invention of Bitcoin in 2009, the global cryptocurrency market has grown at a stunning pace, attracting investors from all walks of life. But the crypto markets are still in their infancy; hardly regulated, extremely volatile, and a perfect breeding ground for scammers and cybercriminals.
As any serious trader knows, securing your cryptocurrency is absolutely imperative. So, what are the best ways to secure your crypto?
1. Trade on Reputable and Safe Exchanges
Crypto is usually bought and sold on exchanges, just like stocks are. There are hundreds of cryptocurrency exchanges, and dozens of them have high trading volume.
However, only a select few can be considered truly safe: Kraken, Gemini, Coinbase, Crypto.com, and Binance are arguably the best and safest crypto platforms out there.
Kraken is available in almost all countries and has a dedicated team of cybersecurity researchers. Gemini is regulated by the New York State Department of Financial Services and hyper-focused on security, while Coinbase and Crypto.com both showed exceptional transparency when they suffered breaches.
All the above-mentioned cryptocurrency exchanges are secure, have solid cybersecurity infrastructures, and store user crypto at dedicated facilities that are geographically distributed and heavily surveilled, some by armed guards.
2. Store Your Crypto in Multiple Cold Wallets
If you trade crypto, as opposed to just holding it, keeping most of it in exchange may seem like the best option, but it is definitely not a good idea from a cybersecurity perspective. While it is true there are safe exchanges, breaches do occur, and some platforms halt withdrawals on a whim, especially during downturns.
Clearly, the smartest option would be to store your crypto independent of exchanges: in multiple wallets, preferably cold or hardware wallets.
As safe as some software wallets are, cold wallets are superior in pretty much every way, at least when it comes to cybersecurity, since they are not even accessible via the internet.
Ideally, you should distribute most of your crypto across multiple cold wallets, and keep only a small portion of it in a software wallet, or on an exchange if you are a trader.
Continue reading: https://www.makeuseof.com/best-ways-secure-cryptocurrency/

In the early days of the internet, there was a shared understanding that this new technology would be transformational. It would change the way we communicate, work and even play. This utopian view of the internet has essentially come to fruition. But as we've become increasingly reliant on the web, we've also seen its darker side. From data breaches to election interference, it's clear that the internet is not the safe haven we once thought it was.
But what if there was a way to build a new internet? One that was secure, decentralized, democratized and had the power to transform the way we interact with each other in the digital world. This is the promise of Web3, sometimes known as the Metaverse, a term coined from the famous science–fiction novel Snow Crash, written by Neal Stephenson, which predicted virtual reality worlds as an evolution of the internet.
 
Web3 is the third generation of the internet, and it's built on the philosophy that the internet should be a decentralized network of computers rather than a centralized one. This means that there is no single point of failure and no central authority controlling the flow of information.
The Metaverse is not to be confused with Web3, which is the third stage of development of the World Wide Web. The Metaverse refers to a virtual reality-based parallel internet world where users can interact with each other and digital objects in a 3D space. It's an extension of the internet into a three-dimensional virtual world. It is an immersive, interactive, and social platform where people can create avatars to represent themselves, buy and sell virtual property, and interact with other users in real-time. Web3 is more about blockchain technology and concepts, including digital identity, smart contracts, and decentralized applications (dApps). According to Statista, the global Metaverse market is worth $47.48B in 2022 and is set to soar to $678.7 billion by 2030.
Continue reading: https://www.forbes.com/sites/markminevich/2022/06/17/the-metaverse-and-web3-creating-value-in-the-future-digital-economy/?sh=3d4eb9c27785

Despite attempts to label the blockchain as a disruptive "trust machine", the tangible business applications of this nascent technology have yet to take shape in practice and be more visible for customers.
In the food and grocery industry, however, trust has become an essential element for increasingly demanding consumers after a decade of scandals such as the horsemeat fraud in 2013 and the Pret à Manger mislabeling in 2016. This year, examples of Nestle's Buitoni Pizza and Ferrero's Kinder were found to be contaminated with E. coli.
For food-industry supply chains, the two key trust enhancers are traceability and transparency. Traceability requires cooperation and sharing of information between different actors of the supply chain, ensuring efficiency and reducing risk. Transparency includes disclosure, knowledge sharing, and clarity. It has become one of the key value drivers for food, alongside more traditional factors such as price and taste.
The blockchain functions as a distributed ledger of all transactions that have been executed between users belonging to a network, thus serving as a secure and transparent information storage and transmission technology. It thus has the potential to provide the trust enhancers required by the food industry.
Through the consensus mechanism, the blockchain network also bypasses the need for an intermediary and automates the trust in the whole system, disrupting the way transactions and processes occur compared to the current traditional system.
Continue reading: https://techxplore.com/news/2022-06-blockchain-consumer-food.html

Did you know that over 106 million people worldwide now use cryptocurrency? The most popular of them all is bitcoin! Understanding blockchains and how bitcoin works are the first essential steps to starting your journey in cryptocurrency. You have probably heard of confusing terms like ‘blockchains’, ‘cryptography’, ‘bitcoin mining’, and ‘decentralized crypto exchanges’. 
Cryptocurrency can be intimidating to get into, and a lack of knowledge might be hindering your motivation to get into bitcoin trading or mining. We compiled all the most crucial information you need to know into one, easy-to-read guide. Welcome to the ultimate resource for bitcoin beginners. Today, we will explore what the bitcoin blockchain is and how it works.
What is the blockchain?
The blockchain is a public database distributed through online networks. It was first proposed as a research project in 1991. Think of it like a ledger that stores a constantly-updating record of every bitcoin transaction. When someone exchanges bitcoin, it is going from one person’s anonymous virtual wallet to another’s. 
Unlike a normal database, the blockchain records its data in a different structure. Instead of submitting individual entries into a table format, data is collected and saved in groups, also called blocks. 
What is a block?
To answer ‘What is the blockchain’, you need to know what blocks are. Blocks are interconnected and contain information. Hence, forming a chain of blocks – or a “blockchain.”. A blockchain stores all kinds of information. Making them great for smart contracts, non-fungible tokens (NFTs), and a variety of other use cases.  
The information stored in these blocks includes the digital address of bitcoin wallets and the exact timestamp of the transaction. Bitcoin miners verify and publish the blocks. Then they are ‘stacked’ onto each other to form a new blockchain part. Once bitcoin miners deem it a safe and valid transaction, the new bitcoin block is transferred. Finally, it's recorded into the ledger for all to see.  
Continue reading: https://www.youhodler.com/blog/bitcoin-blockchain

The rise of social media has led to the emergence of a multi-billion dollar “creator economy” that makes it possible for anyone to earn a living by creating and sharing content with their fans. While it’s almost impossible to know how much money the creator economy is worth, one estimate suggests that creators could generate as much as $20 billion globally. 
That’s a lot of money, but not all of it ends up in the pockets of the creators themselves. While today’s social media sites are the ones that have given rise to a new generation of influencers, they’re also heavily criticized for leeching off many of the contemporary artists that use their platforms. The likes of YouTube, TikTok and Instagram rely heavily on creators to grow their user base and drive engagement, and yet those influencers tend to receive but a fraction of the revenue they generate.  
It’s for this reason that many creators see the rise of Web3 as an opportunity to break their reliance on the traditional, highly centralized platforms that first propelled them to fame. With Web3, blockchain and decentralization, creators can regain full ownership of the content they create and take back control of the way it’s disseminated and monetized across platforms.
The Limitations Of Centralized Social Media 
Some creators may not believe there’s any real reason to switch from tried-and-tested platforms like YouTube or Instagram. Indeed, some of the most popular creators on YouTube reportedly rake in millions of dollars a year from their endeavors. Take Logan Paul for example, who began his YouTube channel back in 2015 and quickly saw his subscriber base explode. As of January 2022, his YouTube channel had more than 23.2 million subscribers and over 5.8 billion views. While his exact earnings aren’t clear, Forbes reported in 2018 that he made $14.5 million in revenue the previous year. 
Continue reading: https://smallbiztrends.com/2022/06/web3-and-the-creator-economy.html

The creator economy is driving innovation across industries, shifting definitions of work and providing revolutionary avenues for income. This software-enabled economy allows people to make money by producing content via photos, videos or music.
The creator economy is a booming industry, which only skyrocketed further during the pandemic: tech innovation of the past decade has amplified the industry’s possibilities. On the front-end, different platforms like TikTok, Instagram, and Cameo have billions of users the world over, and have provided content creators with impressive revenue streams. On the back-end of the creator economy, supporting tools like Patreon and Kajabi enable creators to produce better content more easily. 
Within the past few months, there’s been an emergence of industry-specific social platforms, even in traditional sectors. For example, Playhouse launched “TikTok for real estate” where users can browse videos of real estate listings; Hammr enables construction workers to showcase their own construction projects on their app.
The creator economy is shifting definitions of work, but it, too, will undergo transformation with the rise of Web3. 
Shifting definitions of work 
The increasing ability of creators to monetize their content has forced fundamental changes in what “work” looks like. The creator economy, as we know it today, has gone through three phases of evolution:
Continue reading: https://venturebeat.com/2022/06/18/the-future-of-the-creator-economy-in-a-web3-world/

The rise of artificial intelligence (AI) has influenced many sectors to embrace technology and apply some form of AI to their workflow. Because of this popularity, terms like “AI'' and “automation” can start to lose their meaning—and their purpose.
Tech solutions should help organizations accomplish their goals more efficiently. Over the past several years, the federal government has increased its focus on utilizing more advanced technology for a wider variety of complex problems. As the ecosystem of solution providers grows to foster more innovation, the question becomes whether the government is asking the right questions upfront.
The Department of Defense (DoD) is one of the most secure federal departments that works with sensitive and intelligent data. The DoD has started to look at AI solutions and in 2020, the Congressional Research Office (CRS) asked the following questions for the department:

• What types of military AI applications are possible, and what limits, if any, should be imposed?
• What unique advantages and vulnerabilities come with employing AI for defense?
• How will AI change warfare, and what influence will it have on the military balance with U.S. competitors?

These questions are important to understand how AI can be developed and how it will be used in the defense industry. The nuance of military combat requires special attention to data in order to make informed and intelligent decisions.
As an example, in our work with the Army, RGi has been working on experimental geospatial workflows for military missions including surveying, surveillance and reconnaissance. We investigate how AI specifically can provide enriched and meaningful insights that will lead to more informed, accurate and timely decisions during combat operations.
Continue reading: 
https://www.forbes.com/sites/forbestechcouncil/2022/06/17/automation-versus-ai-in-national-defense-are-we-overprescribing-ai/?sh=7ded54aa45a8

To attain true AI understanding, researchers should shift their attention to developing a basic, underlying AGI technology that replicates the contextual understanding of humans.
Industry giants like Google, Microsoft, and Facebook, research laboratories such as Elon Musk’s OpenAI, and even platforms like SingularityNET are all betting that Artificial General Intelligence (AGI) – the ability of an intelligent agent to understand or learn any intellectual task that a human can – represents the future of AI technology.
Somewhat surprisingly, though, none of these companies is focused on developing a basic, underlying AGI technology that replicates the contextual understanding of humans. That likely explains why the research being done by these companies depends entirely on an intelligence model that possesses varying degrees of specificity and relies on today’s AI algorithms.
Unfortunately, that dependence means that, at best, AI can only give the appearance of intelligence. No matter how impressive their capabilities are, they still follow predetermined scripts that contain numerous variables. As a result, even massive, highly sophisticated programs such as GPT3 or Watson only appear to exhibit understanding. In actuality, they have no understanding that words and images represent physical things that exist and interact in a physical universe. The concept of time or the idea that causes have effects is completely foreign to them.
That’s not to take anything away from what today’s AI is able to do. Google, for example, is able to search volumes of information at an incredible speed to provide the results the user wants (at least most of the time). Personal assistants such as Siri can make restaurant reservations, find and read emails, and give directions in real-time. The list goes on and on and is constantly being expanded and improved.
But no matter how sophisticated these programs are, they are still looking for input and making specific output responses that depend entirely on the data sets at their core. If you don’t believe me, ask a customer service bot a question that is “off-script,” and the bot will likely generate a response that makes no sense or no response at all.    
Continue reading: https://www.rtinsights.com/the-future-of-ai-artificial-general-intelligence/

Artificial intelligence (AI) holds great potential to revolutionize business operations. In fact, according to a study commissioned by my company, 67% of organizations expect their AI and machine learning (ML) use cases to increase over the next year. These technologies offer advantages to increase business efficiencies, generate insights, boost competitive market capabilities and deliver personalized customer experiences.
However, enterprises within highly regulated industries face particular challenges related to AI explainability. Industries such as financial services, insurance and healthcare must use transparent, auditable decision platforms to adhere to strict regulations and compliance standards. Today, there are many AI solutions to automate business processes and decisions, but few provide meaningful explainability. While rife with potential, organizations must never lose sight of the “why” behind automated decisions and predictions.
Preparing For Future Regulations
Today, there are many calls from political organizations and society for greater transparency around AI. In addition, governments and consumers seek greater visibility into the algorithms behind their credit and loan approvals, marketing offers and smart home technologies. Proposed legislation in the United States (the Algorithmic Accountability Act) and globally (the EU's Artificial Intelligence Act) seeks to establish standards for safe, ethical and transparent AI outcomes. However, governments have just begun to find ways to implement regulations on AI since use cases are still evolving and emerging.
For example, the New York City Council passed a bill aimed at AI algorithms used in employment tools. The law, due to take effect in 2023, requires employers to engage an independent auditor to evaluate AI tools used to evaluate job candidates and current employees. The law requires bias audits of AI tools used to screen job candidates or promote employees. Fines up to $1,500 will be imposed for both biased AI algorithms or lack of advance notification about the use of such tools to employees and candidates. In the near term, as regulations emerge and standards evolve, businesses should focus on ways to increase transparency to prepare for future regulations.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/06/21/preventing-harmful-ai-bias-with-fairness-through-awareness/?sh=5d3a36456c83

Artificial intelligence (AI) is to business what telescopes are to star gazing—an incredible technological boost that magnifies, clarifies and illuminates business decisions. AI-enabled technology drives everything from algorithms that filter spam emails to complex systems that can drive cars without human intervention.
Advances in AI over the past decade have been nothing short of astounding. Thanks to advances in computing power and the ever-increasing data available to train models, growth in AI and machine learning (ML) has been exponential. Machines can now teach themselves to play and beat the best players in the world in skilled games like chess, Go and countless other digital strategy games. And of greater consequence, machines have even proven better than humans at detecting early-stage lung cancer.
As these tools become ever more ubiquitous, there are fewer and fewer areas where their impact has not been felt. Business is certainly no exception. An increasing number of managerial tasks can now be handled or assisted by AI-based solutions. It is incumbent on managers to evaluate and understand this new technology and how it could be incorporated across their organizations.
The business world has become increasingly digital. This has allowed for the collection of greater amounts of data than ever before. This data is the fuel that powers ML and enables companies of all sizes to lean more and more on data-driven decision-making processes. In the best run businesses, managers have found ways to collaborate with their robot counterparts to drive the greatest results.
Continue reading: https://www.forbes.com/sites/forbesfinancecouncil/2022/06/21/using-artificial-intelligence-to-improve-business-decisions/?sh=536a0f81b494

More than ever, organizations are putting their confidence – and investment – into the potential of artificial intelligence (AI) and machine learning (ML). 
According to the 2022 IBM Global AI Adoption Index, 35% of companies report using AI today in their business, while an additional 42% say they are exploring AI. Meanwhile, a McKinsey survey found that 56% of respondents reported they had adopted AI in at least one function in 2021, up from 50% in 2020. 
But can investments in AI deliver true ROI that directly impacts a company’s bottom line? 
According to Domino Data Lab’s recent REVelate survey, which surveyed attendees at New York City’s Rev3 conference in May, many respondents seem to think so. Nearly half, in fact, expect double-digit growth as a result of data science. And 4 in 5 respondents (79%) said that data science, ML and AI are critical to the overall future growth of their company, with 36% calling it the single most critical factor.
Implementing AI, of course, is no easy task. Other survey data shows another side of the confidence coin. For example, recent survey data by AI engineering firm CognitiveScale finds that, although execs know that data quality and deployment are critical success factors for successful app development to drive digital transformation, more than 76% aren’t sure how to get there in their target 12–18 month window. In addition, 32% of execs say that it has taken longer than expected to get an AI system into production. 
AI must be accountable
ROI from AI is possible, but it must be accurately described and personified according to a business goal, Bob Picciano, CEO of Cognitive Scale, told VentureBeat.
“If the business goal is to get more long-range prediction and increased prediction accuracy with historical data, that’s where AI can come into play,” he said. “But AI has to be accountable to drive business effectiveness – it’s not sufficient to say a ML model was 98% accurate.” 
Instead, the ROI could be, for example, that in order to improve call center effectiveness, AI-driven capabilities ensure that the average call handling time is reduced. 
“That kind of ROI is what they talk about in the C-suite,” he explained. “They don’t talk about whether the model is accurate or robust or drifting.” 
Shay Sabhikhi, cofounder and COO at Cognitive Scale, added that he’s not surprised by the fact that 76% of respondents reported having trouble scaling their AI efforts. “That’s exactly what we’re hearing from our enterprise clients,” he said. One problem is friction between data science teams and the rest of the organization, he explained, that doesn’t know what to do with the models that they develop.
“Those models may have potentially the best algorithms and precision recall, but sit on the shelf because they literally get thrown over to the development team that then has to scramble, trying to assemble the application together,” he said. 
At this point, however, organizations have to be accountable for their investments in AI because AI is no longer a series of science experiments, Picciano pointed out. “We call it going from the lab to life,” he said. “I was at a chief data analytics officer conference and they all said, how do I scale? How do I industrialize AI?” 
Continue reading: https://venturebeat.com/2022/06/17/the-truth-about-ai-and-roi-can-artificial-intelligence-really-deliver/

Many artificial intelligence (AI) algorithms are used to classify, organize or reason about data. Generative algorithms create data using models of the world to synthesize images, sounds and videos that often look increasingly realistic. The algorithms begin with models of what a world must be like and then they create a simulated world that fits the model. 
Generative AIs are frequently found in various content creation roles. They’re used by movie makers to either fill narrative gaps or, sometimes, carry much of the storyline. Some news organizations generate short snippets or even entire stories about events, especially highly structured sports or financial reports. 
Not all generative algorithms produce content. Some algorithms are deployed in user interfaces to enhance the screen or user interfaces. Others help the blind by generating audio descriptions. In  many applications, the techniques assist rather than take center stage. 
The algorithms are now common enough that developers make artistic decisions about their goals. Some aim for the most realistic output and judge it by how indistinguishable the people or animals may be from photographic footage of actual creatures. Others think like artists or animators and want to produce a more stylized product that is obviously not real but more like a cartoon. 
What are the dangers of generative AIs?
Some generative AI algorithms are good enough to deceive. These results, sometimes called “deep fakes,” may be used to masquerade as another person and commit all manners of fraud in their name. Some may try to imitate a person and withdraw money from a bank. Others may try to place words in another person’s mouth to frame them for a crime like libel, slander or more.
One particularly salacious approach involves generating pornography that seems to include another person. These results may be used for blackmail, coercion, extortion or revenge. 
Can the results of generative AIs be distinguished from real images?
The results of modern algorithms are often very realistic but a trained eye can usually spot small differences. This is harder with some of the best algorithms that are often found in the best computer graphics for Hollywood movies with large budgets.
Continue reading: https://venturebeat.com/2022/06/17/what-is-generative-artificial-intelligence-ai/

If it sometimes seems like the odds are stacked against women in business, then the figures back it up: globally, women make up over 50% of the population but own only 1% of the total wealth. This spurs many women to turn to self-employment and entrepreneurship, seeking loans for their nascent businesses. But again, women have been shown, according to a United Nations Economic Commission for Europe (UNECE) study, to only have access to 3% of bank loans. 
WEgate, the European gateway for women's entrepreneurship, published its 2021 WEbarometer report and confirmed UNECE’s findings. Less than 25% of its respondents rated the environment for accessing finance as good or better, many of them self-fund or get finance from family sources and very few of the survey’s 316 respondents across 25 countries found that maternity leave legislation is supportive of women starting a business in their country.
Other bars are access to flexible working and child care. Working mothers report child care concerns as a top reason for voluntarily leaving the workforce with 34% stating that childcare expense or availability was a leading factor, according to a report from McKinsey. 
But it is of long-term benefit to tech companies to make sure that women are properly included in the workplace. Equality, diversity and inclusion at work leads to more innovation and better business performance up to 87% of the time – researchers have found that when diverse workplace teams of three or more people make decisions, they outperform individual decision-makers. Diverse teams make decisions faster too, up to a 60% improvement on decision-making.
Continue reading: https://tech.eu/2022/06/17/why-female-friendly-tech-matters

If you’re a human being, you’ve likely felt like an impostor at one time or another. As adults, as professionals, as women and especially as women in tech. (Shout-out to Product and UX women, too.)
Women account for just 16% of senior-level technology jobs in the U.S. and only 10% of executive positions, according to the Quantifying Gender Gap study by Entelo, a company helping recruiters find under-represented job candidates.
I’ve heard variations of the impostor question over and over since I worked my way into my first leadership role. My go-to answer for women wondering how to get over impostor syndrome is, "use your voice."
One of my favorite movies, As Good As It Gets, summed it up best when, out of sheer exasperation, Greg Kinnear’s character tells Jack Nicholson’s, “The best thing you have going for you is your willingness to humiliate yourself.”
I’m certainly not suggesting that you purposely embarrass yourself in front of a room full of coworkers, but I am encouraging you to take a risk, speak up and give your opinion when it isn’t asked for.
Go ahead and ask that question you think everyone else already knows the answer to. In small conversations and big meetings I remember that quote, even more so in times when I'm riddled with self-doubt and — let’s be honest, ladies — that’s most of the time.
You may be wondering, why bother? It’s true that staying under the radar can be comforting. By doing the minimum your role requires you can still keep those paychecks rolling in. Not taking a risk can be a safe way to avoid failure. It’s also a good way to ensure nothing extraordinary happens, either.
If you’re driven to make a difference while climbing the corporate ladder, make yourself heard. Sometimes it might backfire, but I guarantee it will be beneficial more often than not.
Here's what else I’ve learned clawing my way through difficult situations. Perhaps sharing will help you avoid some of that clawing. And please share your own experiences of successes and setbacks — and questions about challenging situations — in the comments section. Or email me at [email protected]
Continue reading: https://www.forbes.com/sites/katiedelgado/2022/06/16/how-to-beat-impostor-syndrome/?sh=39ac71d23916  

As Web3 becomes a major new industry in the startup technology sector, the question is increasingly asked, as it has been with each prior cycle of digital innovation: How it will involve business and IT?
With all the innovations in the world, it can be difficult to separate the signal from the noise when it comes to often controversial subjects like cryptocurrency, blockchain, or NFTs. While not getting much respect in certain quarters, there is also little doubt that the technology innovations underpinning these trends have formed a major bow wave of innovation under the general rubric of Web3.
Cryptocurrency, blockchain, and NFTs have undergone numerous hype cycles and investment rounds already. Despite travails, the industry has steadily grown year after year, even as significant parts of it are currently undergoing one of the largest downturns to date. But these cycles now appear inevitable in a world where exponential technologies tend to accelerate and magnify major events. The question now is if Web3 has become important to the enterprise.
I now believe that the evidence is in: Web3 is an important category of technology to the business world. Should the average organization be investing in understanding and realizing Web3's dense layers of highly sophisticated ideas and technologies? Is it significant and inevitable enough now to warrant concerted investment and innovation? Let's take a closer look at what's happening in the space.
Web3 has grown up
One test of a technology trend is its venture capital activity, which attracts the current generation of up-and-comers and leading talent to fresh, green-field opportunities. Here is where Web3 currently has some impressive proof points: The respected venture capital firm Andreessen Horowitz is already into its fourth and largest-ever Web3-related fund, Crypto Fund 4, which raised an  unprecedented $4.5 billion last month for a gamut of blockchain-related investments that will flesh out "the next generation of computing." Another proof point is the number of decentralized apps or 'Dapps', which are used in Web3 ecosystems. These recently crossed the 4,000 mark and are growing fast, according to the State of the Dapps industry tracker. There are other proof points.
Continue reading: https://www.zdnet.com/article/how-decentralization-and-web3-will-impact-the-enterprise/

The cliché is that the only things unavoidable in life are death and taxes. We can probably add new technology to the list, too. Artificial intelligence (AI), the metaverse, autonomous vehicles, flying cars – they’re all coming.
Lawmakers, if they want to be on top of a paradigm shift, should approach tech regulation in a way that is thoughtful, perceptive and comprehensive. But reaching consensus in our statehouses is challenging and finding any sort of common ground in Washington, D.C., is virtually impossible.
Can the Metaverse be Regulated? What Crypto Community's Reaction to Biden’s Executive Order Tells Us
Making matters worse, a comprehensive approach to tech policy typically occurs only after some crisis forces legislators’ hands and the media is all over them, only increasing the risk that the law is hasty or ill-conceived.
While new regulatory frameworks will be needed in some areas of Web3 – the version of the internet driven by blockchain – there are other areas where innovators and investors can move the ball forward on the basis of existing laws and regulations, all the while simplifying the task for policymakers.
So let’s talk about technological neutrality.
By “technological neutrality” in the context of Web3 and tech innovation, we mean this: If new technology enables activities that are mostly the same as existing activities, let’s start with an assumption that the law treats the two activities similarly.
Said differently, wherever possible, the law should be neutral to the tech and any variations in legal treatment should come from (and be tailored to) material variations in the business or risks associated with the technology.
U.S. President Joseph Biden’s recent executive order on crypto, while leaving a whole lot unsettled, gives an implicit nod to this approach when declaring, “same business, same risks, same rules.” The crypto community will likely hate the approach the Securities and Exchange Commission (SEC) takes, but at least it’s now in a context we can all understand.
In Web3 and crypto, regulators and innovators alike have at times gotten this backward. For instance, in the midst of the initial coin offering (ICO) boom; an SEC chair once said every ICO token he had seen was a security. That suggested, although digital tokens on distributed ledgers are infinitely variable and could represent anything from book club points to stock in a corporation, legal risks in Web3 stem from the technology rather than what lawyers call a substantive activity.
Continue reading: https://www.coindesk.com/layer2/2022/06/16/the-case-for-technological-neutrality-in-web3/

Kevin Owocki is the founder of Gitcoin, a funding platform for Web3 projects that are building for the public good. He’s on a mission to accelerate funding toward the most impactful world-positive projects. To that end he’s written a book called GreenPilled: How Crypto Can Regenerate the World.
I recently sat down with Kevin to discuss the book and his journey as a founder in Web3. This interview was condensed and edited for clarity. If you’d like to see the full video interview, click here.
 
Kyle Westaway: What is the Green Pill, and why should I take it?
Kevin Owocki: It’s up to you whether or not you want to take it. But the green pill is a story of how crypto can regenerate the world.
How do we build a world in which we've solved our contemporary challenges with sustainability? I believe that crypto can be sort of a shelling point to build more information-age institutions that deliver funding to everyday people and help support our commons. What if we could use blockchain technology to create more coordination and solve coordination failures? That’s the idea behind the book GreenPilled: How Crypto Can Regenerate the World.
I'm the founder of Gitcoin, which has delivered $63 million worth of funding for open source software projects for our digital infrastructure. So, we're actually putting these ideas into practice at Gitcoin. The book is intended to educate people about how they can put it into practice in their own projects.
Westaway: Help me understand quadratic funding.
Owocki: Gitcoin grants are built on top of this mechanism called quadratic funding, which sounds scary, but it's actually very simple. It is a way of matching contributions from the crowd with a pot of matching funds. Every quarter on Gitcoin grants, we have $3 million that we're giving away, and we're matching contributions from the crowd.
The way quadratic funding works is that dollars matched are based off of the number of contributions to a project as opposed to the total amount raised. So, if you had a grant that raised $100 from 100 contributors and I had a grant that raised $100 from one contributor, you would actually get 99% of the matching pool because you're supported by a broader base of contributors. This is really powerful. Even $1 contributions can be matched with $10, $100 or sometimes even $1,000 from the matching pool because of the quadratic funding formula.
Continue reading: https://www.forbes.com/sites/kylewestaway/2022/06/16/how-crypto-can-regenerate-the-world/?sh=5d6274892fd3

It's safe to say that the cryptocurrency industry is rife with cybercriminals looking to get their hands on your data and your money. Unfortunately, there are numerous ways a cybercriminal can swindle their way towards a payout, one of which is an eclipse attack.
So, what exactly is an eclipse attack?
What Is an Eclipse Attack?
On a typical cryptocurrency blockchain (or peer-to-peer network), an array of different users in different locations, known as nodes, contribute to the network by verifying transactions. Different kinds of consensus mechanisms are used here to ensure that transactions are legitimate, which makes these networks so secure.
Because every node holds some power within a network, and because one node can only connect with a limited number of other nodes at any given time (due to bandwidth limitations), it can be exploited by a malicious individual for illicit purposes.
In an eclipse attack, a singular node is targeted and surrounded by malicious nodes only. This means that all of their outgoing data will be received by malicious nodes, and the same nodes will send all their incoming data.
When a node's communications are successfully flooded by the attacker nodes, a false environment can be created (so long as the node connects with the malicious nodes upon its reconnection with the blockchain network). The unsuspecting victim node assumes that this false environment is legitimate and carries on acting as usual. However, the node's view of the network is distorted.
Continue reading: https://www.makeuseof.com/what-is-an-eclipse-attack/

Significant changes are afoot in the advertising industry. In the last month alone, Netflix announced it may enter the ad business, lawmakers introduced bipartisan bills to throttle Google’s digital ad dominance and Facebook rolled out changes to help advertisers achieve more precision in their targeting. As major players prepare, advertisers have an opportunity to manage these changes in a way that optimizes ad spending and addresses the problem of bias in ad technology.
Bias is a well-known issue for the ad industry, and the programmatic technologies the companies have adopted to supercharge marketing campaigns may not be improving matters. Nearly $1 trillion of digital media flows through programmatic engines that segment and target specific audiences, sometimes missing large consumer groups in the process. Not only can that contribute to improper bias, but it’s also an inefficient way to spend your ad dollars. 
The industry needs to do better, and we need to start now.
Why now? Marketers are rebuilding their technology infrastructures to benefit from artificial intelligence (AI). Netflix already relies heavily on AI to personalize content, and Nike uses it to sell to consumers directly. These developments require that marketers create a foundation of trust with consumers, and to keep pace with the industry, it must be done in a way that scales. 
Continue reading: https://venturebeat.com/2022/06/16/ai-could-mitigate-bias-in-advertising-tech/

With the advent of digitalization, new age technology such as Artificial Intelligence and Machine Learning have taken center stage. Artificial intelligence has a wide range of applications in businesses, including streamlining job processes and aggregating business performance. Researchers are unsure what artificial intelligence means for business in the future. AI is expected to move digital technology away from the two-dimensional screen and into the three-dimensional physical environment that surrounds a person.
While mainstream society’s acceptance of AI is a new phenomenon, the concept is not. Artificial intelligence has numerous applications in business. In fact, most of us have daily interactions with AI in some form or another. Artificial intelligence is already disrupting virtually every business process in every industry, from the mundane to the breathtaking. As AI technologies proliferate, they are becoming increasingly important for maintaining a competitive edge.
Artificial Intelligence: An essential weapon
The term “artificial intelligence” refers to any type of computer software that performs human-like activities such as learning, planning, and problem-solving. Now businesses have to delve deeper to determine which type of AI is prevalent in business and ways that help to boost the performance of business.
Continue reading: https://timesofindia.indiatimes.com/blogs/voices/how-ai-help-companies-to-become-high-performance-businesses/

Artificial intelligence (AI) is taking the business world by storm with its capability to collect, filter and react to data rapidly and in many different ways.
Applying AI technology to law firms involves the use of computers, algorithms and big data to assist, support, collaborate or even duplicate lawyers’ behaviors and decisions so that law firms can function competently, successfully and with foresight in their business environment.
The interconnected world enhanced by technologies such as AI brings many positive changes for the ways in which law firms communicate with their customers, clients and business partners, offering the advantage of providing more an efficient and effective service without compromising quality.
Although AI has not yet been developed to a level where AI-empowered legal advice could fully replace human legal practitioners, the adoption of AI has the potential to reduce transaction costs and improve the accessibility of legal advice through the use of automated assistants, digital hubs or software to offer AI-powered legal services for vulnerable clients.
In collaboration with the Hungarian digital law firm SimpLEGAL, InvestCEE LegalTech Consultancy issued “AI in Legal Services – A Practical Guide” in December 2021, suggesting that AI offers new opportunities for digitalizing legal services.
Continue reading: https://www.legalfutures.co.uk/blog/using-artificial-intelligence-in-the-legal-profession

There’s a joke in Silicon Valley about how AI was developed: Privileged coders were building machine learning algorithms to replace their own doting parents with apps that deliver their meals, drive them to work, automate their shopping, manage their schedules, and tuck them in at bedtime.
As whimsical as that may sound, AI-driven services often target a demographic that mirrors its creators: white, male workers with little time and more disposable income than they know what to do with. “People living in very different circumstances have very different needs and wants that may or may not be helped by this technology,” says Kanta Dihal at the University of Cambridge’s Leverhulme Centre for the Future of Intelligence in England. She is an expert in an emerging effort to decolonize AI by promoting an intersectional definition of intelligent machines that is created for and relevant to a diverse population. Such a shift requires not only diversifying Silicon Valley, but the understanding of AI’s potential, who it stands to help, and how people want to be helped.
Biased algorithms have made headlines in many industries. Apple Health failed to include a menstrual cycle tracking feature until 2015. Leaders at Amazon, where automation reigns supreme, scrapped efforts to harness AI to sift through resumes in 2018 after discovering their algorithm favored men, downvoting resumes with all-female colleges or mentions of women’s sports teams. In 2019, researchers discovered that a popular algorithm used to determine whether medical care was required was racially biased, recommending less care for Black patients than equally ill white patients because it calculated patient risk scores based on individuals’ annual medical costs. Because Black patients had, on average, less access to medical care, their costs were artificially low, and the algorithm faultily associated Blackness with less need for medical treatment. 
Industries like banking have been more successful than others in implementing equitable AI (think: creating new standards for the use of AI and developing systems of internal checks and balances against bias), according to Anjana Susarla, the Omura-Saxena Professor in Responsible AI at Michigan State University. Health care and criminal justice, where algorithms have shown racial bias in predicting recidivism, are more troubling examples. Susarla says decolonizing AI will require the collective oversight of boards of directors, legislators, and regulators, not to mention those who implement and monitor the day-to-day outcomes of AI in every industry—not just the techies behind the tools.
“You have to have some separation between the person who created the AI and the person who can take some responsibility for the consequences that will arise when they are implementing it,” Susarla says.
Continue reading: https://neo.life/2022/06/what-will-it-take-to-decolonize-artificial-intelligence/

The first job for many artificial intelligence (AI) algorithms is to examine the data and find the best classification. An autonomous car, for example, may take an image of a street sign; the classification algorithm must interpret the street sign by reading any words and comparing it to a list of known shapes and sizes. A phone must listen to a sound and determine whether it is one of its wake-up commands (“Alexa,” “Siri,” “Hey Google”). 
The job of classification is sometimes the ultimate goal of an algorithm. Many data scientists use AI algorithms to preprocess their data and assign categories. Simply observing the world and recording what is happening is often the main job. Security cameras, for example, are now programmed to detect certain activity that might be suspicious. 
In many cases, the classification is just the first step of a larger algorithm. The autonomous car will use the classification of a street sign to make decisions about stopping or turning. A smart vacuum cleaner may watch for pets or children, and it’ll turn off or shut down if one is detected. 
What are the types of classification algorithms used in artificial intelligence?
There is a wide range of algorithms that vary between general approaches able to train themselves to answer any type of question and also focused applications that work on particular domains. For example, optical character recognition algorithms are used to convert paper scans into digital documents by classifying each letter in the image. 
Other algorithms are designed to work with numerical data. They may divide the range of potential answers into sections representing each possible potential answer. A simple algorithm for classifying pets as either dogs or hamsters may be successful, examining the weight alone. Any pet weighing more than one pound would be classified as a dog and anyone weighing less than a pound would be classified as a hamster. 
Continue reading: https://venturebeat.com/2022/06/16/what-is-artificial-intelligence-classification/

Since their first use in the mid-1800s, unmanned aerial vehicles have been utilized for security, photography, safety, and many other applications. However, warfare and military units worldwide are primarily responsible for drone technology advancements over time. You may be surprised to learn that the first unmanned drone tech ever used was in 1849 by the Austrian Navy. The Austrians used 200 incendiary balloons to capture Venice. By the early 1900s, the United States military was exploring drone tech for target practice.
Drone technology has come a long way since then. In the 1980s and ‘90s, the U.S. military heavily invested in drone technology. By the mid-90s, the U.S. had developed the infamous Predator program, the unmanned aerial vehicles with anti-tank missiles attached to their wings. Predator drones were heavily used in the wars in Afghanistan and Iraq, and they’re what most people picture when they think of military drones.
The Federal Aviation Administration issued the first commercial drone permit in 2006, paving the way for non-military uses of aerial drones. Corporations and government agencies quickly began testing drones for things like border patrol, disaster relief, and pipeline inspections. But, it wasn’t until Amazon announced it would use drones for delivery that the general in 2013 when the public started taking notice. The first FAA approved drone delivery that happened in the U.S. contained medical supplies and took place in 2015.
The drone industry has grown tremendously in recent years, as the FAA reports that in 2021, nearly 900,000 drones were registered in the U.S. alone. Commercial real estate has found exciting uses for drones, and since the tech has become more affordable, real estate professionals have used them more and more. Thirty-seven percent of real estate agents said drones were the most impactful technology they used in 2021, according to a report from the National Association of REALTORS®.
Most impactful emerging technologies

Drone technology helps commercial real estate teams in marketing, maintenance, construction and development, and other ways. Real estate professionals need to be aware of various regulations regarding drones, and, often, hiring companies that do the flying for them is best. But once the details and specifics are ironed out and drones are ready for take-off, benefits can be numerous.
Here are 4 ways drones are changing the commercial real estate industry:
Continue reading: https://www.propmodo.com/4-ways-drones-are-changing-the-commercial-real-estate-industry/