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Machine Learning in Communication Market to Witness Astonishing Growth by 2030 | Amazon, IBM, Microsoft and more Talking Democrat – Talking Democrat

Global Machine Learning in Communication market report contains a detailed analysis of the current state and future scope along with the sales patterns, market size, share, price structure, and market progressions. The study discusses the underlying trends and impact of various factors that drive the market, along with their influence on the evolution of the Machine Learning in Communication market. This report briefly deals with the product life cycle, comparing it to the relevant products from across industries and then evaluates the snapshot given by Porters five forces analysis for identifying new opportunities in this industry. A thorough evaluation of the restrain included in this report portrays contrast to drivers which helps make strategic planning easier.

Get a Sample PDF of the report at https://www.datalabforecast.com/request-sample/372172-machine-learning-in-communication-market

Asia-Pacific region is expected to dominate the market over the forecast period owing to the increasing focus on the research, development, and manufacturing of Machine Learning in Communication in countries including China, Japan, India, and South Korea.

The report also comprises the study of current issues with end users and opportunities for the Machine Learning in Communication market. It also contains value chain analysis along with key market participants. To provide users of this report with a comprehensive view of the Machine Learning in Communication market, we have included a detailed competitive analysis of market key players. Furthermore, the report also comprehends business opportunities and scope for expansion.

List of Top Key Players in Machine Learning in Communication Market Report are:

Amazon, IBM, Microsoft, Google, Nextiva, Nexmo, Twilio, Dialpad, Cisco, RingCentral.

The qualitative data gathered by extensive primary and secondary research presented in the report aims to provide crucial information regarding market dynamics, market trends, key developments and innovations, and product developments in the market. It also provides data about vendors, including their profile details which include product specifications, applications and industry performance, annual sales, revenue, relevant mergers, financial timelines, investments, growth strategies and future developments.

The biggest highlight of the report is to provide companies in the industry with a strategic analysis of the impact of COVID-19 which will help market players in this field to evaluate their business approaches. At the same time, this report analyzed the market of leading 20 countries and introduce the market potential of these countries.

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Market Analysis and Insights: Global Machine Learning in Communication Market

In 2020, the global Machine Learning in Communication market size was USD million and it is expected to reach USD million by the end of 2030, with a high CAGR between 2022 and 2030

Global Machine Learning in Communication Scope and Market Size

The global Machine Learning in Communication market is segmented by region (country), company, by Type, and by Application. Players, stakeholders, and other participants in the global Machine Learning in Communication market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on sales, revenue and forecast by region (country), by Type, and by Application for the period 2017-2030.

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Machine Learning in Communication Market

Global Machine Learning in Communication Market Segment Analysis:

This report focuses on the Machine Learning in Communication market by volume and value at the global level, regional level, and company level. From a global perspective, this report represents the overall Machine Learning in Communication market size by analyzing historical data. Additionally, type-wise and application-wise consumption tables and figures of the Machine Learning in Communication market are also given. It also distinguishes the market based on geographical regions like North America, Europe, Asia-Pacific, Latin America, and Middle East and Africa.

By the product type, the market is primarily split into

Cloud-Based, On-Premise.

By the end-users/application, this report covers the following segments

Network Optimization, Predictive Maintenance, Virtual Assistants, Robotic Process Automation (RPA).

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This report can be customized to meet the clients requirements. Please connect with our sales team ([emailprotected]), who will ensure that you get a report that suits your needs. You can also get in touch with our executives on +1 917-725-5253 to share your research requirements.

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Machine Learning in Communication Market to Witness Astonishing Growth by 2030 | Amazon, IBM, Microsoft and more Talking Democrat - Talking Democrat

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Big Data and Machine Learning in Telecom Market 2022 Seeking Growth from Emerging Markets, Study Drivers, Restraints and Forecast Talking Democrat -…

Global Big Data and Machine Learning in Telecom Market research report is the latest evaluation of market growth. The report highlights future opportunities, analyzes market risks, and focuses on upcoming innovations. The report provides information about current market trends and development, drivers, consumption, technologies, and top grooming companies. The current trends that are expected to influence the future prospects of the Big Data and Machine Learning in Telecom market are analyzed in the report. The report further investigates and assesses the current landscape of the ever-evolving business sector and the present and future effects of COVID-19 on the market.

The global Big Data and Machine Learning in Telecom market is anticipated to rise at a considerable rate during the forecast period, 2022 to 2028.

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The Big Data and Machine Learning in Telecom market report provides a thorough analysis of the key strategies with a focus on the corporate structure, RandD methods, localization strategies, production capabilities, sales, and performance of various companies. The study conducts a SWOT analysis to evaluate the strengths and weaknesses of the key players in the Big Data and Machine Learning in Telecom market. The researcher provides an extensive analysis of the Big Data and Machine Learning in Telecom market size, share, trends, overall earnings, gross revenue, and profit margin to accurately draw a forecast and provide expert insights to investors to keep them updated with the trends in the market.

Global Big Data and Machine Learning in Telecom market competition by TOP MANUFACTURERS, with production, price, revenue (value), and each manufacturer including

Top Key players of Big Data and Machine Learning in Telecom Market are:AllotArgyle dataEricssonGuavusHUAWEIIntelNOKIAOpenwave mobilityProcera networksQualcommZTEGoogleAT&TAppleAmazonMicrosoft

The leading players are focusing mainly on technological advancements in order to improve efficiency. The long-term development patterns for this market can be captured by continuing the ongoing process improvements and financial stability to invest in the best strategies.

Types covered in this report are:Descriptive analyticsPredictive analyticsFeature engineering

Applications covered in this report are:ProcessingStorageAnalyzing

Regional Analysis For Big Data and Machine Learning in Telecom MarketNorth America (the United States, Canada, and Mexico)Europe (Germany, France, UK, Russia, and Italy)Asia-Pacific (China, Japan, Korea, India, and Southeast Asia)South America (Brazil, Argentina, Colombia, etc.)The Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

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The global Big Data and Machine Learning in Telecom market size is expected to gain market growth in the forecast period of 2022 to 2028, with a Growing CAGR in the forecast period of 2022 to 2028 and will expected to reach USD million by 2028, from USD million in 2021.

The Big Data and Machine Learning in Telecom market report provides a detailed analysis of global market size, regional and country-level market size, segmentation market growth, market share, competitive Landscape, sales analysis, impact of domestic and global market players, value chain optimization, trade regulations, recent developments, opportunities analysis, strategic market growth analysis, product launches, area marketplace expanding, and technological innovations.

The content of the study subjects includes a total of 15 chapters:

Chapter 1, to describe Big Data and Machine Learning in Telecom product scope, market overview, market opportunities, market driving force and market risks. Chapter 2, to profile the top manufacturers of Big Data and Machine Learning in Telecom, with price, sales, revenue and global market share of Big Data and Machine Learning in Telecom in 2017 2021. Chapter 3, the Big Data and Machine Learning in Telecom competitive situation, sales, revenue and global market share of top manufacturers are analyzed emphatically by landscape contrast. Chapter 4, the Big Data and Machine Learning in Telecom breakdown data are shown at the regional level, to show the sales, revenue and growth by regions, from 2017 to 2021. Chapter 5, 6, 7, 8 and 9, to break the sales data at the country level, with sales, revenue and market share for key countries in the world, from 2016 to 2020. Chapter 10 and 11, to segment the sales by type and application, with sales market share and growth rate by type, application, from 2016 to 2020. Chapter 12, Big Data and Machine Learning in Telecom market forecast, by regions, type and application, with sales and revenue, from 2022 to 2028. Chapter 13, 14 and 15, to describe Big Data and Machine Learning in Telecom sales channel, distributors, customers, research findings and conclusion, appendix and data source.

Some of the key questions answered in this report:

What will the market growth rate, growth momentum or acceleration market carries during the forecast period? Which are the key factors driving the Big Data and Machine Learning in Telecom market? What was the size of the emerging Big Data and Machine Learning in Telecom market by value in 2021? What will be the size of the emerging Big Data and Machine Learning in Telecom market in 2028? Which region is expected to hold the highest market share in the Big Data and Machine Learning in Telecom market? What trends, challenges and barriers will impact the development and sizing of the Global Big Data and Machine Learning in Telecom market? What are sales volume, revenue, and price analysis of top manufacturers of Big Data and Machine Learning in Telecom market? What are the Big Data and Machine Learning in Telecom market opportunities and threats faced by the vendors in the global Big Data and Machine Learning in Telecom Industry?

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At last, the Big Data and Machine Learning in Telecom Market report includes investment come analysis and development trend analysis. The present and future opportunities of the fastest growing international industry segments are coated throughout this report. This report additionally presents product specification, manufacturing method, and product cost structure, and price structure.

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Cryptocurrency Prices, Charts, and Crypto Market Cap …

What is cryptocurrency market cap?

Market cap is one of the most popular metrics in the industry that is used to gauge the value of an asset. The market cap of a cryptocurrency is calculated based on the coin's total circulating supply multiplied by the current price. For detailed examples on how the market capitalization of a coin is calculated, please view our methodology page.

As a financial metric, market cap allows you to compare the total circulating value of one cryptocurrency with another. Large cap cryptocurrencies such as Bitcoin and Ethereum have a market cap of over $10 billion. They typically consist of protocols that have demonstrated track record, and have a vibrant ecosystem of developers maintaining and enhancing the protocol, as well as building new projects on top of them. From a trading perspective, large caps would typically be hosted on more exchanges, have higher liquidity, and are less volatile when compared against other mid and small cap cryptocurrencies.

While market cap is a simple and intuitive comparison metric, it is not a perfect point of comparison. Some cryptocurrency projects may appear to have inflated market cap through price swings and the tokenomics of their supply. As such, it is best to use this metric as a reference alongside other metrics such as trading volume, liquidity, fully diluted valuation, and fundamentals during your research process.

Yes, you can check crypto prices on mobile by using the CoinGecko app on iOS and Android.

Candlestick charts give an overview to traders on the price movement based on previous trends. The body of the candlestick shows where the price of a coin opened and closed for the particular period of time which the candlestick represents. If the candle is green in a crypto chart, it represents positive changes in price while red candle represents negative changes in price. The shadow indicates the high price and low price for the period.

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Cryptocurrency Taxes: What Advisors Need to Know – Barron’s

Tax season is here and advisors with clients who sold crypto in 2020 will probably get plenty of questions. The tax laws can be complex and fuzzy.

Heres what you need to know:

Is cryptocurrency taxable? Since 2014, the IRS has considered cryptocurrency to be property, not a virtual currency. This means that a transaction can result in a taxable gain or loss.

What is a cryptocurrency capital gain or loss? It is similar to a stock transaction. The gain or loss is the price you sold the cryptocurrency for, minus the cost basis.

For example, suppose you buy one Ethereum coin for $2,500. After a few months, the value soars to $3,500. You exchange your Ethereum coin for $3,500 of another cryptocurrency. In this case, you will have a capital gain of $1,000.

This is a short-term gain because you held onto the Ethereum coin for less than a year, and your taxes will be at your ordinary income tax rates. If you held for over a year, the transaction would have been taxed as a long-term capital gain, which has a maximum rate of 23.8%.

You can subtract your total losses from the total gains each year, thereby reducing gainsand taxes on gains. And you can deduct up to $3,000 in net losses against your ordinary income. If you have losses above this amount, you can carry them forward to future years.

How do you report a transaction on your tax return? Some cryptocurrency exchanges send you a 1099-B that lists the cost basis and net gains and losses from your transactions. With this information, you will fill out Schedule D and Form 8949 for your 1040 return. If an exchange does not issue a 1099-B, then you will need to track the information using your own records.

This can easily get complicated. For example, suppose you spend $100,000 on cryptocurrency. Then during the yearas the price appreciatesyou sell some to buy a Tesla, some other cryptocurrencies, fast food, clothes, and so on. All these are likely taxable transactions.

Any new rules? President Bidens $1.2 trillion infrastructure bill includes provisions to require exchangesby 2023to report cryptocurrency transactions and include them on 1099-B forms. The goal is to generate $28 billion in tax revenues during the next decade.

The bill also will require exchanges to report identifying information about crypto sellers for amounts over $10,000. The provision will go into effect in 2024.

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Should clients be worried about the IRS? Definitely. The 2021 Form 1040 has the following question: At any time during 2021, did you receive, sell, exchange, or otherwise dispose of any financial interest in any virtual currency? In other words, the IRS is getting more aggressive with enforcement. The agency has already had success in obtaining client information from exchanges.

If you do not properly report your crypto gains, you could be subject to back taxes, interest, penalties and even jail time.

What about wash sales? The wash-sale rule prevents investors from engaging in short-term stock trading to harvest tax losses. For example, if you sell a stock at a loss and then quickly buy it back, the IRS will deny the deduction. You have to wait at least 30 days to buy back the same stock or a security that is substantially similar.

A loophole exempted cryptocurrency transactions from the wash rule. This could change in 2022, according to pending legislation.

Tom Taulli is a freelance writer, author, and former broker. He is also an enrolled agent, which allows him to represent clients before the IRS.

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An unknown buyer used $4.3 million in cryptocurrency to buy a billion-year-old space diamond from Sotheby’s – Yahoo Tech

A member of the Sotheby's auction house team holds the "Enigma" black diamond on February 04, 2022 in London, England. Photo by Leon Neal/Getty ImagesPhoto by Leon Neal/Getty Images

Sotheby's sold a billion-year-old black diamond from space for $4.3 million worth of cryptocurrency.

Named the Enigma, the diamond is 555.55 carats with 55 facets, aka flat surfaces.

The diamond was found near the Earth's surface where it may have formed from meteoric impacts.

A billion-year-old diamond from space sold at auction for $4.3 million worth of cryptocurrency.

Sotheby's announced Wednesday that the Enigma an extremely rare, black 555.55-carat diamond sold to an unidentified buyer who paid in cryptocurrency. The Enigma, according to the Guinness World Record Book, is the largest cut diamond in the world.

While most diamonds are uncovered deep within the Earth, the Enigma is an "extremely rare carbonado," which is a type of diamond discovered near the Earth's surface and believed to have extraterrestrial origins, the London-based auction house said.

"It is thought that this specific type of black diamond was created either from meteoric impacts producing natural chemical vapor deposition or an extraterrestrial origin - from supernovae explosions that formed diamond-bearing asteroids which ultimately collided with the Earth," Sotheby's said.

On Twitter, crypto entrepreneur Richard Heart made a video claiming he was the buyer of the rare space diamond. He said once the payment goes through, he'll rename the item the HEX.com diamond, a reference to a crypto platform he's part of.

In its rough original form, the diamond weighed more than 800 carats. It took three years to get it into its current form with 55 facets, aka flat surfaces, weighing exactly 555.55-carats and having a high degree of polish, Sotheby's said. The Enigma's chosen shape is a Hamsa, a Middle Eastern palm symbol representing protection, blessings, power, and strength.

The nearly 300-year-old auction house has been diving into the crypto world. Last year, it began accepting cryptocurrencies as a form of payment in an effort to expand its client base and has been auctioning digital collectibles known as NFTs.

Crypto enthusiasts have a propensity for big items. The Wall Street Journal in its report said the auction house sold a 100-carat diamond for $12.3 million in crypto in July. Also last year, crypto Twitter rallied around tiny cubes of Tungsten that are extremely dense. They even bid for the opportunity to touch a 2,000-pound Tungsten cube once a year.

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An unknown buyer used $4.3 million in cryptocurrency to buy a billion-year-old space diamond from Sotheby's - Yahoo Tech

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Top cryptocurrency prices today: Bitcoin, Ethereum, Dogecoin fall up to 5% – Economic Times

New Delhi: Most of the top 10 cryptocurrencies by market value were trading lower in Wednesday's trade, with the biggest falls seen in BNB and Cardano.

Among key cryptos, Bitcoin was down 1.18 per cent at $43,406.01. The largest cryptocurrency in m-cap was still up 12 per cent in the last seven days.

Ethereum was quoting at $3,080.69, down 1.84 per cent.

Polkadot and Dogecoin, number 11 and 12 in m-cap terms, were also down 5 per cent each.

The global crypto market cap stood at the $1.97 trillion mark, down 2 per cent. The total crypto market volume jumped 8.67 per cent to $102.96 billion.

Meanwhile, the non-fungible tokens (NFT) community has said that the government was being unfair to the emerging digital asset class by lumping it in with cryptocurrencies in the recently announced digital asset tax regime.

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Top cryptocurrency prices today: Bitcoin, Ethereum, Dogecoin fall up to 5% - Economic Times

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I-Team: Woman Warns Others After Losing $2.5M In Cryptocurrency Romance Scam – CBS Boston

BOSTON (CBS) Cindy Tsai says it started with a seemingly innocent message. A man who called himself Jimmy texted her on WhatsApp. Are you Linda from the pet store? Cindy said. And I messaged back and said wrong number.

That text quickly escalated into the two sharing personal information and Cindy telling Jimmy she was recently diagnosed with terminal cancer. Cindy says, Jimmy was attentive, good looking and was a comfort for her during a difficult time. Cindy says she was also going through a divorce and in her mind the friendship became a relationship.

It didnt take long before Jimmy began showing Cindy how much money he was making trading in cryptocurrency and offered to help her invest on the platform he was using. At first Cindy was skeptical. I basically said, look I dont need a financial advisor, I am not giving you a dime, she said.

But Jimmy told her that she would control her own account and he wouldnt get any of the money. Thats when Cindy says her interest was piqued. Using the link Jimmy gave her, Cindy set up the account.

Matthew Giacobbi, the Special Agent in Charge of the FBIs Boston Division, says these are growing schemes. Once the victim clicks on the link, it takes them to a spoofed site or close to a legitimate site that traders in cryptocurrency use and that looks very real but it is not. Theyve become very sophisticated at making these websites look real when theyre not, Giacobbi said.

Cindys investment started out small but over a few months grew to $2.5 million. All of that money is now gone. The FBI estimates in 2021, 24,000 people fell victim to these types of scams losing about a billion dollars.

Giacobbi says with cryptocurrency, once you give someone your digital wallet and key, that money is gone instantly, and it is very difficult for law enforcement to track.

Cindy says she became suspicious after having a hard time withdrawing money. The site wanted hundreds of thousands of dollars for taxes and also wanted to charge her to expedite her withdrawal. By then it was too late.

A global victims support group says with predators on every social media site anyone can unwittingly become a victim. Grace Yuen with the Global Anti-Scam Organization says everyone has insecurities and when the predators find it, thats when they get you. Thats what makes it so insidious, Yuen said.

Cindy whos a lawyer, admits she saw the red flags. Its interesting the disconnect between your logical self and your emotional self once you have that relationship, she said. I was the most vulnerable in my entire life and I desperately wanted to believe him. My mission is to let everyone know, whether people judge me or dont judge me I want to raise awareness.

Cindy did file a report with the FBIs Internet Crime Complaint Center. The FBI tells us the best way to protect yourself from becoming a victim, dont invest with people you only met online, do your homework, dont click on hyperlinks and never give your banking information or digital wallet to anyone. And if you believe you have been scammed report it to the FBI.

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I-Team: Woman Warns Others After Losing $2.5M In Cryptocurrency Romance Scam - CBS Boston

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Cryptocurrency has taken the idolatry of wealth to a new level of sinfulness – America Magazine

On Feb. 1, a cryptic gold cube worth nearly $12 million appeared in New Yorks Central Park. On display for one day only, the cube was an art installation by artist Niclas Castello. Made exclusively of pure 24-karat gold and weighing a staggering 400 pounds, it came with its own security team to guard it.

If you thought the Castello Cube, as it is called, is a statement on wealth disparity, you could easily be forgiven. New York State has the highest income inequality in the country: In 2020, the average income in Manhattan for the top 1 percent was 113 times that of the bottom 99 percent. And according to the 2020 Census, approximately 129 homeless people live in Central Park. Surely a $12 million cube in the middle of the park has to be some kind of critique about the way we overlook poverty and fetishize wealth?

Unfortunately not. The cube is an advertisement for Mr. Castellos new cryptocurrency, named after himself: CastCoin. The installation isnt about wealth disparityjust wealth. After being on display in the park for less than 24 hours, the Castello Cube was carted off to a Wall Street dinner party reportedly filled with celebrities.

Cryptocurrency is a digital currency that uses blockchain technology and therefore is decentralized, creating an online exchange that is not reliant on a government or bank to uphold its value. Bitcoin was the first and most famous cryptocurrency, but today there are thousands, with Castellos CastCoin being one of the latest. Some hope that crypto will usher in a more democratic future where currencies and transactions can be certified without any backing institution. But those hopes for the future overlook that crypto raises some serious ethical questions. Much like the Castello Cube itself, cryptocurrency does not hold up to a deeper look.

An Empty Obsession

Online, the Castello Cube is billed as being made of solid gold and appears to tower high above the lawn. But this is just hype. The cube is solid gold, insofar as it is made of gold and nothing else. But it is not, in fact, a solid cubethe inside is hollow, and the walls only a quarter of an inch thick. Its also much smaller than it appears online, only about a foot and a half tall, in fact. (To have to speak of only that much pure gold is a condemnation of the work in and of itself.)

Its an excellent metaphor for cryptocurrencies. The outside glitters; the inside is empty. It looms large online but amounts to little in the real world. Crypto has soared in popularity: A 2021 survey found that 13 percent of Americans had traded in crypto in the past 12 months, with another 11 percent reporting they were likely to invest in the next year. A 2021 survey by Pew Research found that 43 percent of men aged 18 to 29 report having invested in cryptocurrency. Some see it as a get-rich-quick scheme, a high-stakes, high-reward trading opportunity that can easily bestow millions. Cryptocurrency is famed for its volatility. In April 2011, one Bitcoin cost $1; in April 2021, the same cost almost $65,000; today its worth is about $40,500.

For others, it is as much of a cultural movement as a financial one, becoming something of a lifestyle with financiers and tech fans. Advertisements for cartoon dog-themed cryptocurrency shine over Times Square, and figures like Elon Musk use their cults of personality to encourage their followers to buy in. R/CryptoCurrency on Reddit, which describes itself as The leading community for cryptocurrency news, discussion, and analysis, has 4.4 million members, obsessively watching and discussing the crypto market.

Our New Golden Calf

In the apostolic exhortation Evangelii Gaudium, Pope Francis warned of the dangers of idolizing money like this. He writes:

Idolatry of money has been a problem for as long as money has existed. But part of what makes crypto different is the way its extreme volatility rewards constant anxious monitoring and encourages obsession not only with investing but with pressuring others to invest as well. Because there is a limited amount of Bitcoin, for example, higher demand for it drives higher prices.

Cryptocurrency has been regarded as democratizing finance because it gives anybody with a computer the ability to get in on the ground floor of an investment that can then take off astronomically. But the dark side of this democratization is that it has spread an obsession with consumption and unhealthy market watching to ever-larger populations than ever before.

And while cryptocurrencies make some people rich, their environmental effects ultimately impoverish all of us. Cryptocurrency is created through an electronic process called mining, which uses computers to solve complex equations and create small amounts of the digital currency. Some cryptocurrencies have a cap on how many units can be mined, which makes the equations progressively more complex, requiring increasing amounts of energy and computational power to continue to mine. (If trying to understand this makes your head hurt, dont worrymine does, too.)

The Bitcoin mining process alone has usedmore electricity than some small countries, including Ukraine, Norway, Sweden and the United Arab Emirates. One single Bitcoin transaction uses enough energy to power an average U.S. household for 75 days. And much of the energy used to power Bitcoin mining and transactions comes from burning fossil fuels. Its impact on the climate is immense. As the environment continues to deteriorate, crypto miners continue to use staggering amounts of resources to create digital monopoly money.

The fact of the matter is that crypto is bad for us. Crypto is what leads to a $12 million hollow box made out of gold being displayed in public parks. The greater risk, however, is that it will lead to such a fixation on wealth that we wont see the poverty around us. That it will lead us to forget our common home and ignore how we are destroying our climate. In the words of Pope Francis, that it will reduce us to mere consumers.

Nine countries have banned cryptocurrencies outright, with another 42 enacting regulations and policies that ban it implicitly. We can stop believing in cryptocurrency and reject its power over us and over our climate. Its time to throw the golden calf back into the fire it came from.

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What is quantum entanglement? All about this ‘spooky’ quirk of physics – Interesting Engineering

If you know anything about quantum mechanics, there's a good chance you've heard of quantum entanglement. This feature of quantum mechanics is one of the most extraordinary discoveries of the 20th century and is one of the most promising avenues of research for advanced technologies in communications, computing, and more.

But what is quantum entanglement and why is it so important? Why did it freak Albert Einstein out? And why does it appear to violate one of the most important laws of physics?

Any time you discuss quantum mechanics, things are going to get complicated, and quantum entanglement is no different.

The first thing to understand is that particles exist in a state of "superposition" until they are observed. In a very common demonstration, the quantum particles used as qubits in a quantum computer are both 0 and 1 at the same time until they are observed, whereby they appear to randomly become a0 or 1.

Now, in simple terms, quantum entanglement is when two particles are produced or interact in such a way that the key properties of those particles cannot be described independently of each other.

For example, if two photons are generated and are entangled, one particle may have a clockwise spin on one axis so that the other will necessarily have a counterclockwise spin on that same axis.

In and of itself, this is not that radical. But because particles in quantum mechanics can also be described as wave functions, the act of measuring the spin of a particle is said to "collapse" its wave function to produce that measurable property (like going from both 0 and 1 to only 0 or only 1).

When you do this to entangled particles, however, we get to the really incredible part of quantum entanglement. When you measure an entangled particle to determine its spin along some axis and collapse its wave function, the other particle also collapses to produce the measurable property of spin, even though you did not observe the other particle.

If a pair of entangled particles are both 0 and 1, and you measure one particle as 0, the other entangled particle automatically collapses to produce a 1, entirely on its own and without any interaction from the observer.

This appears to happeninstantaneouslyand regardless of their distance from each other, which originally led to the paradoxical conclusion that the information about the measured particle's spin is somehow being transmitted to its entangled partner faster than even the speed of light.

Not only is quantum entanglement real, but it's also an important component of emerging technologies like quantum computing and quantum communications.

In quantum computing, how can you operate on qubits in a quantum processor without observing them and therefore collapsing them into plain old digital bits? How do you detect errors without looking at the qubits and destroying the whole mechanism that makes quantum computing so powerful?

The quantum entanglement of several particles in a row is vital to putting enough distance between qubits and the outside world to keep the vital qubits in superposition long enough for them to perform computations.

Quantum communications is another area of research that hopes to take advantage of quantum entanglement to facilitate communication, though it doesn't mean that faster than light communication is on the horizon (in fact, such a technology is likely impossible).

To some degree, yes.

When most people discuss quantum entanglement, they use an example of two entangled particles behaving in a certain way to demonstrate the phenomenon, but this is very much a simplification of an incredibly complex quantum system.

The reality is that a given particle can be entangled with many different particles to varying degrees, not just the "maximally entangled" state where two particles are one to one correlated to one another and only to each other.

This is why measuring one part of an entangled pair doesn't automatically guarantee that you will know the state of the other particle in real-world applications, since that other particle has other entanglements it is maintaining as well. It does give you a better than random chance of knowing the other particle's state though.

Quantum entanglement, or at least the principles that describe the phenomenon, was first proposed by Einstein and his colleagues Boris Podolsky and Nathan Rosen in a 1935 paper in the journal Physical Reviewtitled "Can Quantum-Mechanical Description of Physical Reality Be Considered Complete." In it, Einstein, Podolsky, and Rosen discussed that an especially strong correlation of quantum states between particles can lead to them having a single unified quantum state.

They also determined that this unified state can result in the measurement of one strongly correlated particle having a direct effect on the other strongly correlated particle without regard to the distance between the two particles.

The purpose of the Einstein-Podolsky-Rosen paper wasn't to announce the "discovery" of quantum entanglement, per se, but rather to describe this phenomenon that had been observed and discussed and argue that there must be a missing component of quantum mechanics that hasn't been discovered yet.

Since the strong correlation phenomenon they described violated laws laid down in Einstein's relativityand appeared to be paradoxical, the paper argued there must be something else that physicists were missing that would properly place the quantum realm under the umbrella of relativity. That "something else" still hasn't been found almost a century later.

The first use of the word "entanglement" to describe this phenomenon belongs toErwin Schrdinger, who recognized it as one of quantum mechanics' most fundamental features and argued that it wasn't a mystery that would soon be resolved under relativity, but rather a strong break from classical physics entirely.

Famously, Einstein described quantum entanglement as "spooky action at a distance," but he actually described it as more than just a weird quirk of ghostly particles with instantaneous knowledge of each other.

Einstein actually saw quantum entanglement as a mathematical paradox, an inherent contradiction in mathematical logic that shows that something about the arguments being made must be wrong.

In the case of the Einstein-Podolsky-Rosen paradox, as it came to be called, the arguments are that the fundamental rules of quantum mechanics are completely known and that general relativity is valid. If general relativity is valid, then nothing in the universe can travel faster than the speed of light, which moves at 186,000 miles per second.

If quantum mechanics were fully understood, then the rules governing the strong correlation between particles are complete and our observations tell us everything we need to know.

Since quantum particles are "of the universe" they ought to be governed by the speed of lightjust like everything else, but quantum entanglement not only appears to instantaneously share information between particles that could theoretically be on opposite ends of the universe. Even weirder, this information might even travel back and forth through time.

Quantum entanglement through time would have all kinds of implications for the nature of causality, which is about as fundamental a law of physics as it gets. It doesn't work the other way around, effects can't precede their cause, but some scientists think that those rules might not apply to the quantum realm any more than the speed of light would.

This last point is still mostly speculative, but it has some experimental basis, and it just further complicates the paradox that Einstein, Podolsky, and Rosen proposed in their 1935 paper.

Quantum entanglement is important for two major reasons.

First, quantum entanglement is such a fundamental mechanism of the quantum world while also being one that we can directly interact with and influence.It may provide a key way to harness some of the most fundamental properties of the universe to advance our technology to new heights.

We know how to entangle particles and do so regularly both in laboratories and in real-world applications like quantum computers.Quantum computers in particular demonstrate the potential of quantum mechanics in modern technology, and quantum entanglement is the best tool we have for actually leveraging quantum mechanics in this way.

The other major reason why quantum entanglement is important is that it is a signpost that points towards something truly fundamental about our universe. It is as clear a demonstration as you can get that the quantum world is almost a purer form of the universe than the one we can see and that obeys laws that we can explain.

If all the universe is a stage and matter is the actors, then quantum entanglementand quantum mechanics more broadlymay be the line riggings that lift the curtains, the switches that turn the lights on and off, or even the costumes that the actors wear.

If we watch a play, there are two ways to appreciate it. You can see past the theater and the set pieces to appreciate the story that the play conveys, or you can appreciate the quality of the performance, the staging, and the execution.

You might see two very different things by watching the exact same performance, and quantum mechanics appear to give us a different way of seeing the same universe we've always seen, and quantum entanglement may be the key that gets us backstage.

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Einstein Finally Warms Up to Quantum Mechanics? The Solution Is Shockingly Intuitive – SciTechDaily

Einstein was no stranger to mathematical challenges. He struggled to define energy in a way that acknowledged both the law of energy conservation and covariance, which is general relativitys fundamental feature where physical laws are the same for all observers.

A research team at Kyoto Universitys Yukawa Institute for Theoretical Physics has now proposed a novel approach to this longstanding problem by defining energy to incorporate the concept of entropy. Although a great deal of effort has gone into reconciling the elegance of general relativity with quantum mechanics, team member Shuichi Yokoyama says, The solution is shockingly intuitive.

Einsteins field equations describe how matter and energy shape spacetime and how in turn the structure of spacetime moves matter and energy. Solving this set of equations, however, is notoriously difficult, such as with pinning down the behavior of a charge associated with an energy-momentum tensor, the troublesome factor that describes mass and energy.

The research team has observed that the conservation of charge resembles entropy, which can be described as a measure of the number of different ways of arranging parts of a system.

And theres the rub: conserved entropy defies this standard definition.

The existence of this conserved quantity contradicts a principle in basic physics known as Noethers theorem, in which conservation of any quantity generally arises because of some kind of symmetry in a system.

Surprised that other researchers have not already applied this new definition of the energy-momentum tensor, another team member, Shinya Aoki, adds that he is also intrigued that in general curved spacetime, a conserved quantity can be defined even without symmetry.

In fact, the team has also applied this novel approach to observe a variety of cosmic phenomena, such as the expansion of the universe and black holes. While the calculations correspond well with the currently accepted behavior of entropy for a Schwarzschild black hole, the equations show that entropy density is concentrated at the singularity in the center of the black hole, a region where spacetime becomes poorly defined.

The authors hope that their research will spur deeper discussion among many scientists not only in gravity theory but also in basic physics.

Reference: Charge conservation, entropy current and gravitation by Sinya Aoki, Tetsuya Onogi and Shuichi Yokoyama, 2 November 2021, International Journal of Modern Physics A.DOI: 10.1142/S0217751X21502018

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Einstein Finally Warms Up to Quantum Mechanics? The Solution Is Shockingly Intuitive - SciTechDaily

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