How Wyoming became the promised land for bitcoin investors – MarketWatch

Wyomings economy is powered by some of the oldest industries in human history, including mining, agriculture and tourism. But in recent years the state has emerged as an unlikely champion of far newer inventions: cryptocurrencies and the blockchain technology that powers them.

Now, the Cowboy State is arguably the most crypto-friendly jurisdiction in the United States, thanks to state leaders shepherding a series of new laws.

These changes have encouraged several high-profile companies in the industry to move operations from traditional high-tech hubs like San Francisco to Wyomings capital city of Cheyenne, including crypto exchange Kraken, blockchain platform Cardano and payment protocol firm Ripple Labs. But it has also put the state on a potential collision course with federal regulators who appear far more skeptical of the costs and benefits of blockchain technology than libertarian-leaning Wyomingites.

Wyoming State Sen. Chris Rothfuss, chairman of the chambers blockchain committee, told MarketWatch that a desire to diversify the Wyoming economy has been a primary motivator of his states embrace of the crypto industry.

We do a lot of coal, oil and gas, and those dont necessarily have the bright, shiny futures they once did, the Democrat said. Were really looking for opportunities to bring advanced emerging technologies to Wyoming.

Rothfuss said that its not lawmakers like him who were responsible for driving change in Wyoming. Though the Wyoming state government has a history of business-friendly regulation, he argued that its the states residents, along with entrepreneurs who grew up in the state but left for better economic opportunities, who deserve much of the credit for driving these regulatory changes.

One such member of the Wyoming diaspora is Caitlin Long, founder and CEO of Avanti Bank & Trust, which aims to provide custodial services for institutional investors in cryptocurrencies. A Wall Street veteran with two decades of experience working for Salomon Brothers, Credit Suisse CS, +4.40% and Morgan Stanley MS, +3.40%, she became interested in bitcoin BTCUSD, +9.25% in 2012 after appreciating the potential of blockchain technology to enable faster settlement of financial transactions.

In 2017, Long attempted to endow a scholarship for female engineers at her alma mater, the University of Wyoming, using appreciated bitcoin, but found the school wasnt able to accept the donation because Wyoming laws barred the operation of crypto exchanges in the state. This episode motivated her to advocate for changes to state law regarding digital assets.

Long left Wall Street in 2016 and in 2018 volunteered to serve on the Wyoming Blockchain Taskforce, where she worked with the legislature to craft more than a dozen new laws related to blockchain and digital assets. As the project gained momentum, Long said, it attracted public attention that encouraged even greater support from lawmakers.

The legislature held hearings on the laws where a diverse set of Wyomingites showed up, some driving upwards of eight hours to be there. When the legislators walked in the room, they saw young people who were eager and anxious and wanted legal and regulatory clarity, Long said in an interview with MarketWatch.

A Digital Wild West

The laws enacted by Wyoming in 2018 and 2019 clarified the treatment of digital assets in commercial law, setting the legal foundation for so-called smart contracts, or contracts that are automatically executed by computer code on the blockchain. They also made it easier for crypto investors to set up limited liability company though which investors who live outside the state can still store their digital assets in Wyoming for legal purposes. On Wednesday, Wyomings Republican Gov. Mark Gordon signed legislation to give legal status to decentralized autonomous organizations, or member-owned communities that operate using blockchain technology.

The changes also enable Wyoming banks to serve as custodians of digital assets under a unique legal framework that enables institutional investors to retain direct ownership of digital assets through a custodian bank.

Long argues this will make Wyomings banks the place where investors prefer to store their digital wealth.

The changes also required the Wyoming Division of Banking to issue a new type of banking charter, called a special purpose depository institution, for banks that deal mostly in digital assets. Kraken Bank, a wholly owned subsidiary of cryptocurrency exchange Kraken, became the first bank to be issued this charter in September 2020. Avanti was the second, in October 2020.

David Kinitsky, chief executive of Kraken Bank, told MarketWatch that his company chose to domicile in Wyoming because its the only state offering a banking charter that outlines exactly how bank regulators will supervise a bank that holds digital assets.

Wyoming actually did the work on paper to say how exactly they expect you to operate and how they are going to come in and examine you, he said. None of the other charters in any capacity address digital assets.

Some observers, however, are concerned that Wyomings new charter will expose the national banking system to new risks. The Federal Reserve Bank of Kansas City is reviewing Krakens application to gain access to the Federal Reserves payment system, as most state-chartered banks are entitled to, which would give the bank an account at the Fed and membership in the Fedwire settlement system.

Rob Nichols, chief executive of the American Bankers Association, told the National Conference of State Legislatures earlier this month that because the SPDI charter enables crypto banks to be chartered without becoming insured by the Federal Deposit Insurance Corporation, it gives those banks a competitive advantage.

These entities see the value in getting access to Federal Reserve payments systems like the Fedwire Funds Service and the automated clearinghouse (ACH) network, but do not want to play by the same rules as traditional banks, Nichols said. Finding chartering authorities that are willing to redefine what it means to be a bank introduces risks to the financial systems safety and soundness, consumer protection laws and international reputation.

Albert Forkner, commissioner of Wyomings Division of Banking, said however that it is in part the FDICs reluctance to give any guidance to its member banks on the subject of custody of digital assets that motivated Wyoming to create this new charter. Meanwhile, he added, the charter requires banks to be fully reserved meaning it must have enough cash or cash-like securities on hand at all times to meet any possible customer withdrawal request.

These businesses felt they were being locked out of traditional banking institutions, he said in an interview with MarketWatch. So we want a non-FDIC insured bank, but the trade off is that it would be 100% reserved.

Learning from South Dakota

Forkner likened the changes that the Wyoming Division of Banking is implementing to South Dakotas decision in the early 1980s to eliminate interest-rate caps in order to attract credit card companies to the state. Amid sharply rising inflation rates in the late 1970s and early 1980s, credit card issuers like Citibank were losing money because they couldnt legally charge enough in interest to offset the general rise in prices.

The South Dakota economy was suffering from depressed agricultural prices, motivating the governor to strike a deal with Citibank to eliminate its interest rate cap in exchange for the company moving its credit-card operations to the state. Today, the financial services industry employs roughly 30,000 South Dakotans out of a labor force of roughly 430,000.

Its a useful analogy, said state Sen. Rothfuss. Thats the way that a transformative change to the states economy can happen just by listening, just trying to identify needs of a changing market and meet the needs of innovation.

Wyoming, however, does not hold its fate as a future hub for the crypto industry in its hands alone, given that the Kansas City Fed still has the power to grant or deny access to the central banks payment system.

Its borderline essential to the success of Wyomings charter for the Fed to welcome institutions like Kraken Bank into its system, Forkner said, which would enable real-time settlement of transactions and create a nearly frictionless gateway between the worlds of traditional money and cryptocurrencies like bitcoin.

Kraken Banks CEO Kinitsky said that he expects the Kansas City Fed to approve the banks application, but argued that federal regulators more broadly have been too slow to provide the crypto industry with a regulatory framework specific to this new technology.

You hear about the concept of the innovators dilemma in business, but it happens in government as well, he said. The United States is the de facto leader in financial services by some margin, so we have bigger fish to fry. When youre a smaller jurisdiction whose financial infrastructure doesnt support the global economy, its a different proposition and you can move much faster.

But Wyoming is now forcing federal regulators to at least stake out a position on these issues, and he believes the crypto economy could be a boon to the state for years to come.

Were already seeing other states borrowing liberally from the Wyoming playbook, but their moat is not whats on paper, he said. Wyomings secret sauce is they have a very supportive legislature, public opinion and governors office that view this is an important industry.

See also: Crypto for the long term: whats the outlook?

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How Wyoming became the promised land for bitcoin investors - MarketWatch

First Mideast Bitcoin ETF Aims to Raise More Than $200 Million – Bloomberg

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Canadas largest digital-asset investment fund manager 3iQ Corp. is hoping to raise more than $200 million by listing its Bitcoin exchange-traded fund in Dubai, according to its chief executive officer.

The intent of listing on the Nasdaq Dubai exchange is to get trading at all hours around the globe, said CEO Fred Pye. We trade on the North American market times and Dubai is almost perfectly opposite of what our trading hours are, he told Bloomberg TV.

3iQ was founded in 2012 and has about $1.5 billion in assets. Its 3iQ Coinshares Bitcoin ETF, which listed on the Toronto Stock Exchange last year, is now set to become the first cryptocurrency fund to go public in the Middle East.

Dubai-based Dalma Capital Management Ltd. is the syndicate manager for the offering.

The Canadian fund is also looking to work closely with lenders in the region. Not only the banks in the UAE but also potential banks from other countries in the region, Pye said.

Bitcoin surged past the $63,000 mark earlier this month, its highest ever, before paring gains. JPMorgan Chase & Co. strategists recently said if the largest cryptocurrency isnt able to break back above $60,000 soon, momentum signals will collapse.

Read: Crypto Stock Mania Tested by Sliding Prices, Bitcoin Slump

Pye is hopeful, though. Bitcoin could rise to $100,000 in the next three years because of supply scarcity, according to him.

Right now, weve seen Bitcoin consolidate in the $50,000-$60,000 range, we expect that to continue, he said.

Before it's here, it's on the Bloomberg Terminal.

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First Mideast Bitcoin ETF Aims to Raise More Than $200 Million - Bloomberg

Women Step Up Trading in Bitcoin, Other Cryptocurrencies – The Wall Street Journal

More women are investing in cryptocurrency, as Coinbase Global Inc.s initial public offering and bitcoins recent record-setting high help bring the asset class further into the mainstream.

Several cryptocurrency exchanges and online brokerage firms are reporting an increase in the number of women trading crypto in the past year. Some are expecting that number to rise further, thanks in part to investors greater awareness of the asset class, their desire to buy into hot markets and the promise of boosting their savings. At the same time, some people who are using volatile markets to save expose themselves to the risk of having months of gains wiped out when the winds shift.

One in four customers who traded crypto so far in 2021 on the Robinhood Markets Inc. platform is a woman, said Christine Brown, chief operating officer of Robinhood Crypto. The firm said fewer women trade crypto on its platform than trade stocks and exchange-traded funds. Over the past two years, digital trading platform eToro Group Ltd. said the number of female crypto traders in the U.S. on its platform has jumped by half, to about 20% of all users in the U.S.

Women should have an equal seat at the table when it comes to cryptocurrency investing, Ms. Brown said.

Anthony Denier, chief executive at Webull Financial LLC, is surprised there arent more female crypto traders on the firms platform, owing in part to the availability of information about cryptocurrency investing online and womens increased interest in managing their portfolios. About 21% of the crypto traders on the firms platform are female, a number he said is rising.

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Women Step Up Trading in Bitcoin, Other Cryptocurrencies - The Wall Street Journal

Bitcoins nosedive: What happened and whats ahead? – Fox Business

Gibbs Wealth Management President Erin Gibbs and B. Riley National chief market strategist Art Hogan discuss cryptocurrency, insider 'sell' transactions, and which stocks to watch.

Bitcoin, the world's biggest cryptocurrency, battled back Monday following a weekend flash crash.

BITCOIN SLUMPS 14% AS PULLBACK FROM RECORD HIGH GATHERS PACE

Prices hovered near $56,000 late in the day Monday after previously plunging as much as 14% to $51,541 on Sunday, wiping out the majority of its gains from the previous week which led to a record-high value of $63,200 as tracked by Coindesk.

Bitcoin's recent gains were fueled by the historic stock market debut of cryptocurrency exchange operator Coinbase, which launched a direct listing on the Nasdaq on April 14. Shares of Coinbase, which trade under the ticker COIN, opened at $381 apiece, giving the company a valuation of about $99.5 billion.

According to cryptocurrency analytics firm Bybt, bitcoin set a new record in liquidations on Sunday, resulting in roughly one million positions worth a total of about $10 billion being wiped out.

Multiple factors are believed to be connected to bitcoin's drop.

Data website CoinMarketCap attributed bitcoin's selloff to a blackout in Chinas Xinjiang region, which reportedly powers a lot of the digital currency's mining.

Meanwhile, some reports have speculated that bitcoin's drop could possibly be connected to concerns that the U.S. Treasury may crackdown on money laundering through digital assets. A spokesperson for the Treasury did not immediately return FOX Business' request for comment.

Binance's recent quarterly burn of over 1 million BNB tokens, worth about $595 million, has also prompted fears of market uncertainty.

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Despite bitcoin's drop, many big-name crypto investors are still bullish.

On Sunday, Tyler Winklevoss, founder of Winklevoss Capital Management, along with his twin brother Cameron, and the Gemini cryptocurrency exchange, encouraged investors on Twitter to buy the dip.

Galaxy Digital CEO Mike Novogratz added in a tweet that the drop was "inevitable" but that it's nothing to worry about over the long-term.

"Markets got too excited around $Coin direct listing," Novogratz said. "Basis blowing out, coins like $BSV, $XRP and $DOGE pumping. All were signs that the market got too one way. We will be fine in the medium term as institutions coming to the space."

"In the shorter term we will need to rebuild a trading base," he added. "Market damage doesnt heal overnight. Good luck out there."

Bitcoin Foundation Chairman Brock Pierce told FOX Business in a statement Monday that while he would like to see how the market settles over the next to days, he remains extremely bullish.

"This is just normal volatility in the Bitcoin market, and the pullback only brings us back to where we were two weeks ago," Pierce said. "I still think that all of the conditions are favorable to increase in the medium-and-long term, and I am - as should others - be actively looking to invest more across the space."

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The volatility comes as bitcoin and other cryptocurrencies continue to see growing acceptance.

The Bank of England recently announced it would create a Central Bank Digital Currency as well as a task force to explore its uses.

China is also working on a digital yuan, which it is reportedly considering rolling out during the 2022 Winter Olympics in Beijing. Li Bo, deputy governor of the Peoples Bank of China (PBOC) also referred to bitcoin as an "investment alternative."

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Bitcoins nosedive: What happened and whats ahead? - Fox Business

Major Developer Starts Taking Bitcoin for Rent: Will Other Landlords Follow? – Motley Fool

Rental property landlords who want to be paid are often flexible regarding how they receive their rent money: checks, money orders, online payments, credit cards, and most recently -- mobile payment processes. But is accepting a nonstandard, science fiction-sounding currency called cryptocurrency -- namely Bitcoin (CRYPTO: BTC) -- taking flexible payment options a bit too far? Find out what one major developer (a California billionaire, of course) is doing regarding accepting bitcoin for rent.

The California billionaire mentioned above is Rick Caruso, owner of a commercial real estate company. Not only does Caruso's company accept bitcoin for rent, he believes in this new currency form so much so that he invests a portion of his earnings in bitcoin and has partnered with a cryptocurrency exchange called Gemini, owned by the famous Winklevoss (formerly of Facebook (NASDAQ: FB)) twins.

Caruso is not alone in his belief in bitcoin. PayPal (NASDAQ: PYPL) has invested in it. Elon Musk's company, Tesla (NASDAQ: TSLA), buys this cryptocurrency and allows customers to use it to pay for a Tesla vehicle. Payment service company Square (NYSE: SQ) buys bitcoin. Even huge Wall Street types Morgan Stanley (NYSE: MS) and Goldman Sachs (NYSE: GS) are at least acknowledging bitcoin: They're providing methods for clients to invest in it.

The IRS is legitimizing cryptocurrencies (to ensure it gets its share) and has added a section on Form 1040 to ask if taxpayers have had any financial interest in a virtual currency.

As of March 2021, bitcoin is trading for nearly $60,000, leading many investors to believe, as Caruso does, that cryptocurrency will be part of society moving forward and play a role as early as this year. There are some big questions regarding bitcoin, though: Will it be part of our future? If so, will bitcoin be the currency selected?

Then there's Caruso's vision: an entire ecosystem designed around it, sort of in the same way the Model T car led to highways, gas stations, and even fast-food restaurants.

The vision: Imagine working for a company that pays you with a nontraditional currency, say pink painted rocks or bitcoin (the latter is better since you can use it on the blockchain). Either way, you'd then be limited on where you could spend those pink rocks or bitcoin.

But as luck would have it, your employer also owns apartments that allow payment in -- you guessed it -- bitcoin. You would then be spending your bitcoin on the very properties that issue your bitcoin paycheck. Your whole life would be a revolving "ecosystem" (Caruso's words) indebted to your employer.

Taking bitcoin in rent payments today is extremely risky. Some people, such as economist Nouriel Roubini (known as "Dr. Doom"), think cryptocurrencies are a huge bubble waiting to burst.

Bitcoin may or may not be the currency of the future. And it's not surprising that Caruso accepts it as rent. He stands to make a lot of money if bitcoin makes it. Caruso is showing confidence in the product of which he invests.

If you believe in bitcoin, you might want to allow it as rent payment, too, but if you're risk-averse, it's probably better to wait on this one.

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Major Developer Starts Taking Bitcoin for Rent: Will Other Landlords Follow? - Motley Fool

Fears Of A Major 50% Correction Send Bitcoin Crashing Under $50,000 As Ethereum, Ripples XRP And Cardano Lead $200 Billion Crypto Price Plunge -…

Bitcoin has crashed under the psychological $50,000 per bitcoin level for the first time since early March, losing 10% over the last 24 hours and taking its weekly losses to around 20%. The bitcoin price fell as low as $48,780 on the Luxembourg-based Bitstamp exchange before rebounding slightly.

Some reports said the bitcoin sell-off, which also tanked major cryptocurrencies ethereum, Ripple's XRP and cardano wiping $200 billion from the combined near-$2 trillion cryptocurrency market capitalization, was sparked by speculation that U.S. President Joe Bidens plan to hike capital gains taxes could reduce crypto investment but it follows multiple warnings in recent days bitcoin and the wider cryptocurrency market could be headed for a correction.

With bitcoin and cryptocurrency market watchers nervously eyeing price charts, Guggenheim Partners' investment manager (and long-term bitcoin bull) Scott Minerd has cautioned bitcoin is "very frothy" and could be about to experience a "major correction."

The bitcoin price has dropped sharply this week, losing around 20% of its value and falling under ... [+] the closely-watched $50,000 per bitcoin level. Meanwhile, other major cryptocurrencies, including ethereum, Ripple's XRP, and cardano have also crashed.

"I think we could pull back to $20,000 to $30,000 on bitcoin, which would be a 50% decline, but the interesting thing about bitcoin is we've seen these kinds of declines before," Minerd told CNBC.

Following bitcoin's massive 2017 rally, the bitcoin price dropped sharply through 2018, losing almost 90% of its value before rebounding in 2020. The bitcoin price doubled in the first three months of 2021, climbing to around $65,000 this month as Coinbase IPO mania sparked a surge of interest in cryptocurrencies.

Ahead of this latest move lower, a sudden sell-off that wiped $300 billion from the combined cryptocurrency market value last weekend left bitcoin traders and investors reeling.

However, Minerd said he thinks this week's plunge is part of "the normal evolution in what is a longer-term bull market," and expects the bitcoin price to eventually rebound far beyond its recent highpotentially climbing to over $400,000.

Bitcoin bulls point to the emergence of long-awaited institutional adoption and the sudden interest from companies keen to add bitcoin to their balance sheets as driving the latest rally, with other tokens boosted by the burgeoning decentralized finance (DeFi) market that's built on top blockchain networks like ethereum.

Some of these other major cryptocurrencies, many of which have outperformed bitcoin over the last 12 months, have dropped far further than bitcoin during the current sell-off.

Bitcoin is now down around 20% from its highs of almost $65,000 per bitcoin, dragging the wider ... [+] cryptocurrency market, including ethereum, Ripple's XRP and cardano, with it.

Ethereum, the second-biggest cryptocurrency after bitcoin, has lost around 10% over the last 24 hours. The ethereum price hit an all-time high of over $2,500 per ether token this week before giving up its recent gains. Cardano, an ethereum rival that's seen the price of its ADA token soar in recent months, is off by 12% over the last 24 hours and down just over 25% from its highs.

XRP, a top-five cryptocurrency by value controlled by the embattled company Ripple, is down 20%, adding to losses of 40% in the last week.

Dogecoin, the meme-based cryptocurrency and "joke" bitcoin rival that has soared into the cryptocurrency top five over the last couple of months as pump-and-dump groups try to push up the price, is down 25% from yesterday.

Despite the recent bitcoin and cryptocurrency price plunge, those in the crypto community remain upbeat, pointing to the technological and institutional developments made by bitcoin and crypto over the last couple of years.

"Any comparison with the crypto winter of 2018 belies the amazing growth of the digital token ecosystem," Paolo Ardoino, chief technology officer at bitcoin and cryptocurrency exchange Bitfinex, said in emailed comments.

"While this percentage may be what it was several years ago, the quantum technological leap that has taken placeboth in terms of market structure and the advances in different protocolsmay make today qualitatively different."

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Fears Of A Major 50% Correction Send Bitcoin Crashing Under $50,000 As Ethereum, Ripples XRP And Cardano Lead $200 Billion Crypto Price Plunge -...

Why is ethereum on a tear of late, outperforming bitcoin? – Mint

The crypto market generally tends to follow bitcoin, however, over the past few sessions ethereum has taken a big lead in terms of returns over the worlds biggest cryptocurrency, bitcoin.

Over the past seven sessions, ethereum has delivered a return of 5.5% against -12.4% return given by bitcoin. As of 6.50pm IST on Thursday, bitcoin was trading 1% lower at $54,914.92, while the worlds second-biggest crypto asset was more than 9% higher at $2,593.87, a fresh lifetime high.

According to experts, there are multiple factors working in favor of the altcoin. Altcoin is a cumulative term to define cryptocurrencies that came after bitcoin.

The recent price movement of bitcoin indicates consolidation. This is a healthy pullback and will provide long-term stability to the worlds largest crypto asset. Ether is rallying because of the launch of ethereum exchange-traded fund (ETF) on a Canadian exchange, which is seen as a major step towards making digital assets, mainstream. Ether is expected to break above $3,000 this month," said Shivam Thakral, CEO, BuyUcoin.

Moreover, technical factors are also not working in favor of bitcoin, which has a market capitalization of over $1 trillion.

Recently, bitcoin closed below its 50-Day simple moving average (SMA) for the first time since 8 October 2020. According to global cryptocurrency exchange, Kraken, the move lower coupled with bitcoins inability to immediately get back over the 50-day SMA suggests that the bears could be taking control of the market in the short term.

Until it closes above the 50-day SMA, one can expect bitcoin to remain rangebound between $51.000 and $58,000 historical relevant support and resistance levels, respectively, Kraken said in a note.

According to experts, this divergence between ether and bitcoin over the last few days has both short-term and long-term forces behind it. Over the past year, a lot of investors who got into bitcoin have become aware of ethereum and started diversifying their crypto portfolios. Thats why youve seen ether in a general strong uptrend since early 2020. That trend has gotten stronger as the news of Eth 2.0 has become better known. That innovation is going to lower fees and open up many new opportunities for innovation," said Vikram Rangala, chief operating officer of ZebPay.

While bitcoins most well-known use case is as a store of value, ethereum has several use cases. Its a software platform for things like non-fungible tokens and financial services, among others.

Investors are learning that. In March, with the Coinbase IPO and other bullish bitcoin news, some investors may have sold their ether to move into bitcoin. Now that this bitcoin rally seems to be ending, people are taking profits and moving value back into their long-term ether investments," Rangala added.

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Why is ethereum on a tear of late, outperforming bitcoin? - Mint

UK to explore issuing its own digital currency amid bitcoin boom – CNBC

Fifty and twenty pounds bank notes and a bitcoin logo are seen in this photo illustration.

Omar Marques | SOPA Images | LightRocket via Getty Images

LONDON Britain is the latest country to join a global race toward central bank digital currencies.

"We're launching a new taskforce between the Treasury and the Bank of England to coordinate exploratory work on a potential central bank digital currency," U.K. Finance Minister Rishi Sunak said at a fintech industry conference on Monday.

In a separate statement, the Bank of England said such a currency would be a "new form of digital money issued by the Bank of England and for use by households and businesses" that exists alongside cash and bank deposits rather than replacing them.

The U.K. government hasn't yet decided whether to introduce a digital version of the British pound, but said it would explore the "objectives, use cases, opportunities and risks" involved if it were to proceed. The Bank of England will also set up a unit within the institution dedicated to exploring a central bank digital currency.

It comes as several central banks race to figure out their own strategies for central bank digital currencies, or CBDCs. The rise of bitcoin and other cryptocurrencies has given new impetus to such initiatives, as well as the broader trend of declining cash usage.

Bitcoin surged to a record high of $64,829 last week ahead of the highly-anticipated debut from cryptocurrency exchange Coinbase. But the world's most popular digital coin sank sharply over the weekend due to fears around regulation.

A spike in the value of meme-inspired token dogecoin, meanwhile, has led to concerns of a potential bubble in the cryptocurrency market. As of Monday, bitcoin was trading at about $56,740, up 3% in the last 24 hours.

Another factor driving central banks' work on CBDCs is private stablecoin projects such as the Facebook-backed Diem Association and a controversial token known as tether. Such currencies attempt to peg their market value to some external reference, such as the U.S. dollar, to avoid volatile price swings that are common in most cryptocurrencies.

China appears to be charging ahead of other major countries on CBDCs. The People's Bank of China has been carrying out a number of tests with the digital currency in major cities and a top official said Sunday that thecentral bank could trial the digital yuan with foreign visitors at the 2022 Beijing Winter Olympics.

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UK to explore issuing its own digital currency amid bitcoin boom - CNBC

Everything You Need to Know About Adversarial Machine Learning – Analytics Insight

Machine learning is a key aspect of Artificial Intelligence. However, one area that has always been an issue to worry about is adversarial attacks. It is because of this that the models trained to work in a particular way fail to do so and act in undesired ways.

Computer vision is one of those areas that has grabbed eyeballs from everywhere around. This is the area where the AI systems deployed aid in processing the visual data. What attackers do here is add a layer of noise to the images. This further makes matters worse as adding noise leads in misclassification. A defence method against such an adversarial attack is randomized smoothing. This is a method wherein the machine learning systems become resilient against imperceptible perturbations.

However, it has been observed that despite randomized smoothing, machine learning systems could fail. Here are some aspects of Adversarial machine learning.

This makes into the list of the most common techniques to target the data that forms the base of training the models. Data poisoning is where corrupt data is inserted into the dataset. Doing so, training the machine learning model is compromised. In some cases, such techniques are seen to trigger a specific undesirable behaviour in a computer vision system whereas in some it has been observed that the accuracy of a machine learning model is reduced drastically. What is an area of concern here is that it becomes virtually impossible to detect all these attacks because their modifications are not visible to the human eye.

It has been established that minimizing the empirical error wouldnt be that effective as the models are still vulnerable to adversarial attacks. Random smoothing is a technique that serves to be useful here. The technique works by cancelling out the effects of data poisoning by establishing an average certified radius (ACR) during the training of a machine learning model. Now here is the catch when a trained computer vision model classifies an image correctly, then adversarial perturbations within the certified radius will not affect its accuracy. However, larger the ACR, it becomes a little difficult to make the adversarial noise visible to the human eye.

This is yet another research paper wherein the researchers came up with a new data poisoning method called Poisoning Against Certified Defenses (PACD). This method employs bi-level optimization, a technique that has two major objectives to serve: one, to create poisoned data for models that have undergone robustness training, and the other to pass the certification procedure. This process takes a set of clean training examples and gradually adds noise to them until they reach a level that can circumvent the target training technique. When the target model is trained on the tainted dataset, its ACR is reduced drastically. Using PACD, the researchers have been successful in producing clean adversarial examples. Simply put, the perturbations are not visible to the human eye.

The researchers wanted to check whether a poisoned dataset targeted at one adversarial training technique would prove to be effective against others. On that note, it was found that PACD transfers across different training techniques.

The future

Adversarial attacks are presenting new challenges for the cybersecurity community. Hence, the coming years would see a lot of challenges in this area. Though PACD is effective, sound knowledge of the target machine learning model before formulating the poisoned data is the need of the hour. Yet another area of concern is the cost of producing the poisoned dataset. If all of this is taken into account, the future can see promising results for sure.

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Everything You Need to Know About Adversarial Machine Learning - Analytics Insight

Why AI That Teaches Itself to Achieve a Goal Is the Next Big Thing – Harvard Business Review

Lee Sedol, a world-class Go Champion, was flummoxed by the 37th move Deepminds AlphaGo made in the second match of the famous 2016 series. So flummoxed that it took him nearly 15 minutes to formulate a response. The move was strange to other experienced Go players as well, with one commentator suggesting it was a mistake. In fact, it was a canonical example of an artificial intelligence algorithm learning something that seemed to go beyond just pattern recognition in data learning something strategic and even creative. Indeed, beyond just feeding the algorithm past examples of Go champions playing games, Deepmind developers trained AlphaGo by having it play many millions of matches against itself. During these matches, the system had the chance to explore new moves and strategies, and then evaluate if they improved performance. Through all this trial and error, it discovered a way to play the game that surprised even the best players in the world.

If this kind of AI with creative capabilities seems different than the chatbots and predictive models most businesses end up with when they apply machine learning, thats because it is. Instead of machine learning that uses historical data to generate predictions, game-playing systems like AlphaGo use reinforcement learning a mature machine learning technology thats good at optimizing tasks. To do so, an agent takes a series of actions over time, and each action is informed by the outcome of the previous ones. Put simply, it works by trying different approaches and latching onto reinforcing the ones that seem to work better than the others. With enough trials, you can reinforce your way to beating your current best approach and discover a new best way to accomplish your task.

Despite its demonstrated usefulness, however, reinforcement learning is mostly used in academia and niche areas like video games and robotics. Companies such as Netflix, Spotify, and Google have started using it, but most businesses lag behind. Yet opportunities are everywhere. In fact, any time you have to make decisions in sequence what AI practitioners call sequential decision tasks there a chance to deploy reinforcement learning.

Consider the many real-world problems that require deciding how to act over time, where there is something to maximize (or minimize), and where youre never explicitly given the correct solution. For example:

If youre a company leader, there are likely many processes youd like to automate or optimize, but that are too dynamic or have too many exceptions and edge cases, to program into software. Through trial and error, reinforcement learning algorithms can learn to solve even the most dynamic optimization problems opening up new avenues for automation and personalization in quickly changing environments.

Many businesses think of machine learning systems as prediction machines and apply algorithms to forecast things like cash flow or customer attrition based on data such as transaction patterns or website analytics behavior. These systems tend to use whats called supervised machine learning. With supervised learning, you typically make a prediction: the stock will likely go up by four points in the next six hours. Then, after you make that prediction, youre given the actual answer: the stock actually went up by three points. The system learns by updating its mapping between input data like past prices of the same stock and perhaps of other equities and indicators and output prediction to better match the actual answer, which is called the ground truth.

With reinforcement learning, however, theres no correct answer to learn from. Reinforcement learning systems produce actions, not predictions theyll suggest the action most likely to maximize (or minimize) a metric. You can only observe how well you did on a particular task and whether it was done faster or more efficiently than before. Because these systems learn through trial and error, they work best when they can rapidly try an action (or sequence of actions) and get feedback a stock market algorithm that takes hundreds of actions per day is a good use case; optimizing customer lifetime value over the course of five years, with only irregular interaction points, is not. Significantly, because of how they learn, they dont need mountains of historical data theyll experiment and create their own data along the way.

They can therefore be used to automate a process, like placing items into a shipping container with a robotic arm; or to optimize a process, like deciding when and through what channel to contact a client who missed a payment, with the highest recouped revenue and lowest expended effort. In either case, designing the inputs, actions, and rewards the system uses is the key it will optimize exactly what you encode it to optimize and doesnt do well with any ambiguity.

Googles use of reinforcement learning to help cool its data centers is a good example of how this technology can be applied. Servers in data centers generate a lot of heat, especially when theyre in close proximity to one another, and overheating can lead to IT performance issues or equipment damage. In this use case, the input data is various measurements about the environment, like air pressure and temperature. The actions are fan speed (which controls air flow) and valve opening (the amount of water used) in air-handling units. The system includes some rules to follow safe operating guidelines, and it sequences how air flows through the center to keep the temperature at a specified level while minimizing energy usage. The physical dynamics of a data center environment are complex and constantly changing; a shift in the weather impacts temperature and humidity, and each physical location often has a unique architecture and set up. Reinforcement learning algorithms are able to pick up on nuances that would be too hard to describe with formulas and rules.

Here at Borealis AI, we partnered with Royal Bank of Canadas Capital Markets business to develop a reinforcement learning-based trade execution system called Aiden. Aidens objective is to execute a customers stock order (to buy or sell a certain number of shares) within a specified time window, seeking prices that minimize loss relative to a specified benchmark. This becomes a sequential decision task because of the detrimental market impact of buying or selling too many shares at once: the task is to sequence actions throughout the day to minimize price impact.

The stock market is dynamic and the performance traditional algorithms (the rules-based algorithms traders have used for years) can vary when todays market conditions differ from yesterdays. We felt this was a good reinforcement learning opportunity it had the right balance between clarity and dynamic complexity. We could clearly enumerate the different actions Aiden could take, and the reward we wanted to optimize (minimize the difference between the prices Aiden achieved and the market volume-weighted average price benchmark). The stock market moves fast and generates a lot of data, giving the algorithm quick iterations to learn.

We let the algorithm do just that through countless simulations before launching the system live to the market. Ultimately, Aiden proved able to perform well during some of the more volatile market periods during the beginning of the Covid-19 pandemic conditions that are particularly tough for predictive AIs. It was able to adapt to the changing environment, while continuing to stay close to its benchmark target.

How can you tell if youre overlooking a problem that reinforcement learning might be able to fix? Heres where to start:

Create an inventory of business processes that involve a sequence of steps and clearly state what you want to maximize or minimize. Focus on processes with dense, frequent actions and opportunities for feedback and avoid processes with infrequent actions and where its difficult to observe which worked best to collect feedback. Getting the objective right will likely require iteration.

Dont start with reinforcement learning if you can tackle a problem with other machine learning or optimization techniques. Reinforcement learning is helpful when you lack sufficient historical data to train an algorithm. You need to explore options (and create data along the way).

If you do want to move ahead, domain experts should closely collaborate with technical teams to help design the inputs, actions, and rewards. For inputs, seek the smallest set of information you could use to make a good decision. For actions, ask how much flexibility you want to give the system; start simple and later expand the range of actions. For rewards, think carefully about the outcomes and be careful to avoid falling into the traps of considering one variable in isolation or opting for short-term gains with long-term pains.

Will the possible gains justify the costs for development? Many companies need to make digital transformation investments to have the systems and dense, data-generating business processes in place to really make reinforcement learning systems useful. To answer whether the investment will pay off, technical teams should take stock of computational resources to ensure you have the compute power required to support trials and allow the system to explore and identify the optimal sequence. (They may want to create a simulation environment to test the algorithm before releasing it live.) On the software front, if youre planning to use a learning system for customer engagement, you need to have a system that can support A/B testing. This is critical to the learning process, as the algorithm needs to explore different options before it can latch onto which one works best. Finally, if your technology stack can only release features universally, you need likely to upgrade before you start optimizing.

And last but not least, as with many learning algorithms, you have to be open to errors early on while the system learns. It wont find the optimal path from day one, but it will get there in time and potentially find surprising, creative solutions beyond human imagination when it does.

While reinforcement learning is a mature technology, its only now starting to be applied in business settings. The technology shines when used to automate or optimize business processes that generate dense data, and where there could be unanticipated changes you couldnt capture with formulas or rules. If you can spot an opportunity, and either lean on an in-house technical team or partner with experts in the space, theres a window to apply this technology to outpace your competition.

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Why AI That Teaches Itself to Achieve a Goal Is the Next Big Thing - Harvard Business Review