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Macro Investor Dan Tapiero on Crypto Adoption: Emerging Economies Ahead of Developed States | News – Bitcoin News

Bitcoin and gold holder Dan Tapiero, says it is still early to talk of widespread crypto adoption as the proportion of users relative to the rest of the population remains low. Tapiero makes the remarks while referring to a study, which places Nigeria at top of the list of countries with the highest number of respondents that say they own or are using cryptocurrency.

According to the study, 32% of surveyed Nigerians say they used or owned cryptocurrencies in 2020 while in Japan, which is last on the list, only 4% say they owned cryptos in 2020. The survey, which was conducted by Statista, shows that countries with emerging economies like Vietnam (21%) and South Africa (17%) have more respondents who say they used or owned cryptos in 2020. Spain (10%) is the only developed country where the percentage of respondents that own or used cryptocurrencies get to double-digit figures.

In the United States, which appeared to be the focus of Tapieros tweet, the percentage of respondents that confirm owning or using crypto is only 7%. In his tweet, Tapiero who is the Co-founder at 10T Holdings infers that the world is currently seeing the crypto which is still at the birth of a new global asset class. Some Twitter users were quick to query the methodology of the study and Tapeiro admits that there are countries that belong on this list that are not listed.

Still, another Twitter, Alexander Burgei insists that the data is really clear and that adoption is already happening but only in dysfunctional countries, as a backup to devaluating currencies. While adoption is already happening in some countries, the Twitter user says it will not be real until its taken by the Western powers and China.

Meanwhile, in an earlier tweet, Tapiero claims that it is the beginning of the end for banks and urges them to either adapt or perish.

He adds:

Time to pivot towards the digital asset ecosystem. Bitcoin is the pristine collateral at its centre. The whole new world now growing up alongside the legacy system.

Tapieros remarks come as fintech and payment firms continue to eat into the banks share of market capitalization. According to data shared by Tapiero on Twitter, fintech, and payment firms only accounted for less than 10% in 2010. This figure has grown to nearly 30% share of the market capitalization.

There are expectations that this trend is set to continue and banks that fail to embrace emerging technologies will lose influence.

Do you think cryptocurrency adoption is happening faster in some regions than in others? Tell us your thoughts in the comments section below.

Image Credits: Shutterstock, Pixabay, Wiki Commons

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Ban All Ransomware Payments, in Bitcoin or Otherwise – CoinDesk – CoinDesk

We all know its illegal to kidnap someone and ask for a ransom payment. But should it also be illegal for the victim to pay the ransom?

Earlier this month the U.S. Treasury Department did just that. It notified the world that certain ransom payments are illegal, specifically those to sanctioned ransomware operators. Should a victim pay a ransom to a sanctioned entity, that person may face a big fine.

J.P. Koning, a CoinDesk columnist, worked as an equity researcher at a Canadian brokerage firm and a financial writer at a large Canadian bank. He runs the popular Moneyness blog.

Punishing ransom victims seems heartless. But it may be one of the best ways to protect the public from extortionists. And if it wants to make a serious dent in the growing ransomware market, the Treasury Department will have to go much further than putting a few entities on its sanctions list.

On Oct. 1, the U.S. Treasurys Office of Foreign Assets Control (OFAC) published a notice reminding everyone that several ransomware operators have been put on OFACs list of sanctioned entities, otherwise known as its Specially Designated Nationals (SDN) List. The agencys letter clarifies that should a victim make a ransom payment to an OFAC-sanctioned ransomware operator, that person could be breaking the law.

The ransomware wave

Ransomware is malicious software that blocks access to a computer system by encrypting data. Once the data is locked, the ransomware operator demands the victim pay a ransom in exchange for a decryption key.

The emergence of bitcoin, a digital, uncensorable asset, has made it particularly easy for ransomware operators to profit from their attacks. The earliest bitcoin ransomware strains targeted regular consumers with $300 or $400 ransoms. In 2019, operators like Sodinokibi, Netwalker and REvil began to move on to attacking corporations, municipal governments, school boards and hospitals.

The ransoms have gotten much larger. This summer, the University of Utah paid $457,059 in bitcoin for a decryption key. CWT, a travel company, paid $4.5 million to Ragnar Locker ransomware operators in July. The list of victims grows longer by the hour.

The damage involves more than just the ransom fee. Many organizations bravely refuse to give in to the ransomware operators demands. Rebuilding their network often costs more than the actual ransom payment. The crippled system will likely remain down for days, even weeks. The Government of Nunavut, a Canadian territory, couldnt serve citizens for almost a month after it refused to pay Dopplemayer ransomware operators.

A collective action problem

Societys response to ransomware is an example of a collective action problem. The public would be better off if everyone cooperated and refused to pay money to ransomware operators. With no incoming ransom income, the ransomware business would be unprofitable, attacks would cease and the collateral damage would stop.

Unfortunately, spontaneous cooperation between thousands of corporations, governments, and nonprofits is difficult to achieve. Any attempt to boycott ransom payments must rely on appeals to solidarity. But organizations will face pressure from shareholders or citizens to recover as quickly as possible, and so they will secretly pay. If 10% or 20% of victims defect from the boycott and pay the ransom, then the ransomware industry will be profitable and so everyone suffers as the blight continues.

Banning ransomware payments may not be the perfect option for stopping the growing ransomware wave, but it may be the best option weve got.

One way to fix the collective action problem is for the government to help push the public towards the best solution. The government can do this by declaring ransom payments illegal, and setting a penalty for rule breakers. The punishment for breaking the law would be a $20 million fine, or something like that.

Now when a ransomware operator attacks, all the victims cooperate by default. No, we cant pay you. If we do, well have to pay an even larger fee to the government. Ransom payments will stop, ransomware operators will cease their attacks and the damage ends.

The market for bribes as an analogy

Using the government to arrive at the best solution to a collective action problem isnt without precedent. Another type of shady payment, the payment of bribes, provides a useful analogy.

If companies must habitually bribe foreign government officials for contracts, then that drives up the costs of doing business. The public would be better off if everyone refused to pay a bribe. But cooperation is difficult.

Until the 1970s and 80s, foreign bribes were valid tax deductions in many countries. But efforts like the U.S.s Foreign Corrupt Practices Act of 1977 (FCAP) made it unlawful to bribe foreign government officials. Multinationals can now push back against bribery requests by pointing to FCAP. This helps push society arrive at the no-bribe solution.

The U.S. Treasurys recent clarification about the illegality of certain ransom payments only goes part of the way. It prohibits payments to a few bad actors, but there are many ransomware operators that do not appear on OFACs SDN list. To help solve the collective action problem, OFAC would have to be more proactive in designating ransomware operators.

Sussing out the names and identities of all the producers and distributors of ransomware seems like an impossible task, however. It would be much easier to declare a blanket ban on all ransomware payments, just as how FCAP bans bribery. Ransom bans arent without precedent. In response to a wave of kidnappings by organized crime, Italy prohibited ransom payments in 1991. Colombia and Switzerland have also made ransom payments illegal. The Group of Seven has a long-standing policy of refusing to pay ransoms for hostages of terrorist groups.

The knock against prohibiting either bribes or ransom payments is that it forces the market to become more opaque. If it is legal to make a bribe, then the bribe payer can report the bribe taker. This serves to limit the market for bribes. Ban bribes and the bribe payer is incentivized to cooperate with the bribe taker to keep things secret.

This is why Kaushik Basu, the former chief economist at the World Bank, has long advocated for legalizing bribe payments.

As for ransomware, victims who pay a ransom can report the attack to law enforcement agencies like the Federal Bureau of Investigation without fearing a fine. This allows the FBI to follow up. But if it is illegal to pay a ransom, then victims that choose to pay will keep their actions a secret. Lacking accurate data, the FBI will do a poorer job of defending against ransomware.

The other knock against banning ransomware payments is the perceived inhumanity of it. Try telling a mother or father that it is illegal for them to pay a ransom to free their kidnapped child. The same goes for ransomware. A school board that has been crippled by ransomware can immediately resume classes by paying a $20,000 bitcoin ransom. But under a prohibition, children may have to go a week or two without classes as the school board rebuilds its systems.

There are also civil liberties concerns. Businesses will argue that a ban on ransoms infringes on their ability to control their property.

Bitcoin isnt Green Dot

When extortionists find profitable ways to bilk the public, one way to fight them is to make changes to the underlying payments platform that the scammers are using. Internal Revenue Service scammers converged on Green Dot MoneyPak cards in the mid 2010s as a useful way to extort innocent Americans. The chosen solution wasnt to tell victims that paying ransom was illegal. Rather, Green Dot Bank pulled the product for a year and reprogrammed it. And it worked. Criminals have moved on from using MoneyPaks to do IRS scams.

Unlike MoneyPaks, bitcoin cant be reprogrammed. That leaves society with one less option for protecting itself from ransomware attacks. And so the no payment solution to the collective action problem beckons. Banning ransomware payments may not be the perfect option for stopping the growing ransomware wave, but it may be the best option weve got.

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Hotel Bitcoin ATMs on the Rise With Addition of Swiss Hotel Dolder Grand | News – Bitcoin News

The number of hotels with a bitcoin ATM on-site is growing in Switzerland. The latest announcement came from The Dolder Grand, a luxury hotel and spa in Zurich, which recently installed a crypto ATM supporting four cryptocurrencies.

The Dolder Grand announced Monday that a cryptocurrency ATM has been installed at the hotel for guests to buy and sell cryptocurrencies on-site. The announcement states:

As of now, guests of the Zurich Hotel Dolder Grand can buy and sell cryptocurrencies on site conveniently at the crypto ATM. This is made possible by a device from the Swiss cryptocurrency financial specialist Vrdex Suisse.

Hotel guests can use the machine to buy four cryptocurrencies bitcoin, bitcoin cash, litecoin, and ethereum with Swiss francs and euros. They can also sell BTC for Swiss francs.

The Dolder Grand started accepting bitcoin for overnight stays, food, drinks, and spa treatments last year. According to the announcement:

The demand for cryptocurrencies has increased significantly since the outbreak of the coronavirus crisis. Many use the Vrdex machines to gain initial experience with cryptocurrencies.

The crypto ATM installed at The Dolder Grand is operated by Vrdex Suisse, which has the largest network of cryptocurrency ATMs in Switzerland. Founded in 2017, Vrdex is a spin-off from Bitcoin Suisse AG. Based in Zugs crypto valley, the company is a regulated Swiss financial intermediary.

Vrdex Suisse has installed crypto ATMs at about 70 locations in Switzerland. According to the cryptocurrency ATM tracking website Coinatmradar, there are currently 102 crypto ATMs in Switzerland, making it the country with the sixth-highest number of cryptocurrency ATMs.

Besides The Dolder Grand, other hotels that have a Vrdex Suisse cryptocurrency ATM installed include Hotel 46a, Parkhotel, Htel Rgina, Hilton Zurich Airport, and Hotel Hecht Gottlieben. The company says that hotel guests actively take advantage of the opportunity to easily buy and sell cryptocurrencies at ATMs.

Do you think all hotels should have a bitcoin ATM? Let us know in the comments section below.

Image Credits: Shutterstock, Pixabay, Wiki Commons, The Dolder Grand

Disclaimer: This article is for informational purposes only. It is not a direct offer or solicitation of an offer to buy or sell, or a recommendation or endorsement of any products, services, or companies. Bitcoin.com does not provide investment, tax, legal, or accounting advice. Neither the company nor the author is responsible, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with the use of or reliance on any content, goods or services mentioned in this article.

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World Gold Council Survey Shows Cryptocurrency Investment the 5th Most Popular in Russia – Bitcoin News

According to a recent research survey, cryptocurrency investment is a touch more popular than gold in Russia. An organization called the World Gold Council surveyed 2,023 investors and cryptocurrency turned out to be the fifth-largest investment next to gold.

The World Gold Council (WGC) is considered an authority on the gold industry as the market development organization works with all types of industry leaders in the precious metals field. WGC also manages the very popular web portal gold.org and it often publishes research studies concerning safe-haven investments.

Just recently, WGC published a report concerning gold investments in Russia and the study also touched upon cryptocurrency investments as well.

The WGC surveyed 2,023 Russian investors that stem from all around the country. 68% of the surveyed participants said gold is seen as an effective store of value.

Most Russian investors believe [gold] holds its long-term value and protects against currency and inflation fluctuations, the WGC study details. In a chart that highlights the investments in Russia over the past 12 months, cryptocurrency investment vehicles represent a higher percentage than gold.

Cryptocurrency is listed as the fifth-most popular investment vehicle with a percentage rating of around 17%. Meanwhile, gold is roughly 16% among the 2,021 WGC survey participants.

Ahead of cryptocurrency investments include things like savings accounts, foreign currencies, real estate, and life insurance respectively. Below cryptocurrencies and gold on the WGC list are investments like collectibles, gold coins, stocks, and government-issued bonds.

Additionally, the WGC authors wrote that crypto investment is taking place in Russia even though regulations are quite gray in the region.

The rise of cryptocurrencies demonstrates that there is a desire for choice and appeal among retail investors. As the Russian investment market takes shape, opportunities for different investment products will emerge and gold will need to respond, the WGC authors said.

What do you think about the WGC report which shows cryptocurrencies as being Russias fifth-most popular investment? Let us know in the comments section below.

Image Credits: Shutterstock, Pixabay, Wiki Commons, WGC report

Disclaimer: This article is for informational purposes only. It is not a direct offer or solicitation of an offer to buy or sell, or a recommendation or endorsement of any products, services, or companies. Bitcoin.com does not provide investment, tax, legal, or accounting advice. Neither the company nor the author is responsible, directly or indirectly, for any damage or loss caused or alleged to be caused by or in connection with the use of or reliance on any content, goods or services mentioned in this article.

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Ethereum Q3 Volume Dwarfs Bitcoin’s, Fueled by DeFi – Decrypt

In brief

The Ethereum blockchain is now processing more than twice the daily transaction volume of the Bitcoin blockchain, riding a massive wave of growth in stablecoins and the DeFi apps that use them.

A new report from crypto research firm Messari on Q3 activity in DeFi and stablecoins has revealed that the current rolling 30-day average for Ethereum is around $7 billion; Bitcoins is under $3 billion.

If current rates hold, Ethereum is on track to see more than $1 trillion in annual transaction volume, a major reversal from 2019, when Bitcoin transaction volume was more than double that of Ethereum.

Though Bitcoins price has climbed over the last three months from the mid-$9,000s to above $13,000, Bitcoin volume has remained mostly steady since October 2019, indicating that attention has shifted toward Ethereums unstoppable decentralized application platform, and away from the more straightforward store of value utility offered by Bitcoin as digital gold.

The Messari report pegs the impressive growth in Ethereums transaction volume on the accelerated use of stablecoins, most commonly used in interactions with DeFi applications. DeFi stands for decentralized finance, a group of blockchain-based applications running primarily on the Ethereum chain. DeFi apps use automatically executed blocks of code known as smart contracts to perform financial operations like issuing loans or generating interest on user deposits.

Many DeFi loans are issued in stablecoins, or crypto tokens pegged to an asset such as the US dollar; doing so makes financial reckoning more compatible with existing calculations on aspects like interest rates or liquidity ratios.

Most stablecoin loans are issued with cryptocurrency holdings put up within DeFi apps as collateral, requiring the value of the underlying crypto assets to remain above a certain threshold to avoid a margin call, in which part of the crypto collateral is sold to pay off a portion of the outstanding loan.

Of all stablecoins, by far the most numerous is Tether, a centralized, at times controversial, dollar-pegged token with more than $16 billion currently in circulation. Its no surprise, then, that Messari research found Tether to be the most-transacted stablecoin in the crypto landscape. Tether, however, isnt just the most traded stablecoinMessari found that over the summer, it grew to surpass even Bitcoin with a rolling 30-day average transaction volume of nearly $3.5 billion.

DAI, a product of DeFi lending service MakerDAO, also had a strong Q3, growing its supply more than 600% from the start of July through September according to the Messari report.

Unlike Tether, which issues new Tether stablecoins in partnership with large-scale customers like crypto exchanges, DAI is generated through MakerDAO users taking loans against their crypto holdings in a decentralized system. DAI is thus more resistant to censorship or control by its issuing entity, but it also requires different incentives to keep the tokens stable at $1, like community-controlled interest rates.

While different stablecoins take different approaches to deliver security and utility to their users, its clear the emerging asset class will play a key role in the ongoing development of the crypto economy. Stablecoins could have the potential to crowd out cash as the best way to transact on a day-to-day basis, provided similar tokens distributed and controlled by national central banks dont eventually make them redundant.

As Ethereum transaction volume takes off, Bitcoins simple design could hold the original cryptocurrency backor it could just as likely follow the DeFi herd, as cross-cross chain transfers that allow access to Bitcoin value in DeFi apps become increasingly common.

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Crypto fans rejoice: Bitcoin rallies to the brink of $12,000 – Aljazeera.com

The worlds largest digital currency rose as much as 3.4 percent on Monday to about $11,835.

Bitcoins biggest rally in more than a week has pushed it to the brink of $12,000, a key level watched by chartists and technicians.

The worlds largest digital currency rose as much as 3.4% on Monday to around $11,835. Crypto fans are closely watching the $12,000 level as a major hurdle to cross before it can embark on a bigger rally.

The Bloomberg Galaxy Crypto Index, which tracks some of the largest digital coins, also rose, gaining 4.5% at one point. Dash and Monero were among the biggestadvancers, each rising more than 5%.

On Monday, the International Monetary Fund hosteda virtual panelon cross-border payments and digital currencies which featured BIS General Manager Agustin Carstens as well as the Federal Reserve Chairman Jerome Powell, among others. Powell said the central bank is evaluating the costs and benefits of a digital currency but has not decided yet on whether to issue one. He also nodded to Facebook Inc.s Libra as a catalyst for focusing more attention on the issues.

The discussion at least partly helps explain Bitcoins move higher as it was closely watched by the crypto community, said Mati Greenspan, founder ofQuantum Economics.

Comments from Jerome Powell and the other participants made it clear just how far apart the various countries are when it comes to CBDCs, said Greenspan, referring to central bank digital currencies. Many on social media were quick to point out that a truly global and decentralized digital currency already exists.

The coins trading Monday also helped it buck a recenttrendof moving in tandem with U.S. equities, whereby it was often rising when they were and falling on risk-off days. The S&P 500 Index dropped as investorsweighedthe latest progress on a new government spending bill meant to help shore up the economy.

Many analysts remain bullish on the cryptocurrency, heartened by its limited supply and comforted by greater institutional acceptance in recent weeks. Square Inc., for instance, said earlier this month that it has made an investment of about $50 million in Bitcoin.

We see Bitcoin emerging as a relative oasis of calm and outperformance, wrote Mike McGlone, an analyst with Bloomberg Intelligence, in a note. There should be little doubt technology and digitization will continue advancing, yet Bitcoins supply will keep shrinking, supporting its price.

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The Importance of Funding Quantum Physics, Even in a Pandemic – Inside Philanthropy

Lets get subatomic. In philanthropic circles, arcane topics such as theoretical physics and quantum mechanics have a tough time attracting significant funding. Grantseekers can find it challenging to convey to potential donors the importance of subjects that are not only outside the ken of most non-scientists, but which may not seem as pressing as emergencies like global pandemics, poverty or climate change. Even within science funding, public and private, the life sciences dominate.

But the Perimeter Institute, a center for theoretical physics based in Waterloo, Ontario, has been successfully attracting funding through a pioneering public-private funding model. We wrote about Perimeter and its approach last year in the wake of the 20-year-old institutes contribution to developing the worlds first image of a black hole.

In short, Perimeter draws a blend of support from government, industry and private funders, and has become a worldwide leader in advancing talent and new discoveries in theoretical physics.

Just last week, Perimeter announced its new Clay Riddell Centre for Quantum Matter, a research hub where scientists will study the subatomic world of quantum mechanics to understand and discover new states of matteryou know, states of matter other than the familiar solid, liquid, gas and plasma that you learned about in high school. (Dont ask us to explain plasma.)

The new center is the culmination of a 10-year, $25 million investment in quantum matter research, made possible by a $10 million founding donation from the Riddell Family Charitable Foundation. Clay Riddell, who died in 2018, was a Canadian entrepreneur and philanthropist. Physicists believe that study of quantum science and matter will eventually lead to useful technologies and abilities that stretch the imagination.

That the theoretical science of today leads to the technologies of tomorrow is a key message in basic scienceand especially funding for basic science, explained Greg Dick, Perimeters executive director of advancement and senior director of public engagement. Consider the theory of special relativity and curved space: One hundred years after Einstein proposed it, Dick said, special relativity is a necessary element of GPS navigation systems in cars and other settings. The theories of quantum mechanics led in just a few decades to the computer age. And before all that, the theories of magnetism and electricity eventually translated into practically every single thing we use every day.

When electricity and magnetism were discovered, the problem of the day was air pollution in New York City from the manure that horse hoofs pulverized into dust, said Dick. But fortunately, people were thinking about esoteric questions of electricity and magnetism, and that changed society.

In other words, society can ill afford to stop funding basic and theoretical science. The exciting thing is that the time from new theory to useful technology is getting shorter, Dick said. Perhaps in a decade, the study of quantum matter could lead to solutions for next-generation quantum computers, medical diagnostics, transportation, superconductors for energy grids and cryptography for data security and communications.

But just as likely, said Dick, the study of quantum matter will enable the creation of exotic materials and technologies no one currently expects or imagines.

And this brings us to why the coronavirus pandemic, which has demanded so much of the worlds attention, is helping science grantseekers connect with funders.

Obviously, when COVID started, there was a pause (in fundraising), but interestingly, COVID has also moved the relevance and value of foundational science to the forefront of peoples minds, said Dick. Yes, the theoretical physics that we do is nuanced, but COVID has put science on a pedestal. Its actually easier to have that conversation about the value of science.

Whatever their understanding of physics, prospective donors can easily grasp the importance of the basic research that has enabled todays search for treatments and vaccines for COVID-19.

In a related manner, the COVID-19 pandemic changed the nature of the social interactions with potential donors, said Dick. In the past, wed host big events and parties, but now, the pivot to digital communication has really opened up new ways to connect with supporters. Those person-to-person video calls can actually enable more personal and deeper conversations, he said.

Perimeter was established in 1999, seeded with $100 million from Mike Lazaridis, the founder of the Blackberry smartphone pioneer Research In Motion. Bringing the public along as enthusiastic partners was always a requirement, said Dick. Mikes vision right at the beginning was world-class research, for sure, but he also wanted that message of foundational science baked into Perimeter from the very beginning.

As a result, Perimeter also offers classroom-ready educational resources used by teachers around the world, reaching millions of students.

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Material found in paint may hold the key to a technological revolution – Advanced Science News

The waste chips of paint you strip off the walls might not be so useless afterall.

Image credit: Sandia National Laboratories

For the next generation of computer processors, one persistent challenge for researchers is finding novel ways to make non-volatile memory on an ever-smaller scale. As smaller processors inevitably lead toward a finite limit on space and therefore processing power quantum computing or new materials that move away from traditional silicon chips are thought to overcome this barrier.

Now, researchers at Sandia National Laboratory, California, and the University of Michigan, publishing in Advanced Materials, have made a step forward in realizing a solution to this problem using a new material in processing chips for machine-learning applications, that gives these computers more processing power than conventional computer chips. The specific obstacle the authors wanted to overcome was the limitations with filamentary resistive random access memory (RRAM), in which defects occur within the nanosized filaments. The team instead wanted to create filament-free bulk RRAM cells.

The materials the authors use, titanium oxide or TiO2, may sound like a rather mundane inorganic substance to readers unfamiliar with it, but it is in fact a lot more common than most people realize. If you ever watched Bob Rosss wonderful The Joy of Painting, you may be more familiar with TiO2 as titanium white the name it is given when used as a pigment in paints. In fact, TiO2 is ubiquitous in paints not just on the landscape artists pallet, but in house paints, varnishes, and other coatings. It is also found in sunscreen and toothpaste.

The point is, TiO2 is cheap and easy to make, which is one of the reasons this new-found application in computer technology is so exciting.

A. Alec Talin of the Sandia National Laboratory, lead author of the paper, explained why this cheap, nontoxic substance is ideal for his teams novel processing chip: Its an oxide, theres already oxygen there. But if you take a few out, you create what are called oxygen vacancies. It turns out that when you create oxygen vacancies, you make this material electrically conductive.

These vacancies can also store electrical data, a key ingredient computing power. These oxygen vacancies are created by heating a computer chip with a titanium oxide coating 150 C, and through basic electrochemistry, some of the oxygen in the TiO2 coating can be removed, creating oxygen vacancies.

When it cools off, it stores any information you program it with, Talin said.

Furthermore, their TiO2-based processor not only offers a new way of processing digital information, it also has the potential to fundamentally alter the way computers operate. Currently, computers work by storing data in one place and processing that same data in another place. In other words, energy is wasted in moving data from one place to another before it can be processed.

What weve done is make the processing and the storage at the same place, said Yiyang Li of the University of Michigan and first author of the paper. Whats new is that weve been able to do it in a predictable and repeatable manner.

This is particularly important for machine-learning and deep neural network applications, where as much computing power is needed for data processing, and not data moving.

Li explained: If you have autonomous vehicles, making decisions about driving consumes a large amount of energy to process all the inputs. If we can create an alternative material for computer chips, they will be able to process information more efficiently, saving energy and processing a lot more data.

Talin also sees applications in everyday devices that are already ubiquitous. Think about your cell phone, he said. If you want to give it a voice command, you need to be connected to a network that transfers the command to a central hub of computers that listen to your voice and then send a signal back telling your phone what to do. Through this process, voice recognition and other functions happen right in your phone.

In an age where digital privacy is important, it may be attractive to consumers to know sensitive datasuch as the sound of their own voice stays in their phone, rather than being sent to the Cloud first, where accountability and control is less clear-cut.

Like many advances in science, the discovery of this technological application of TiO2 is, as Bob Ross would call it, yet another happy accident, that has real-world, positive applications.

Reference: Yiyang Li et al., FilamentFree Bulk Resistive Memory Enables Deterministic Analogue Switching, Advanced Materials (2020) DOI: 10.1002/adma.202003984

Quotes adapted from the Sandia National Laboratory press release.

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Bridging the Skills Gap for AI and Machine Learning – Integration Developers

Even as COVID-19 has slowed business investments worldwide, AI/ML spending is increasing. In a post for IDN, dotDatas CEO Ryohei Fujimaki, Ph.D, looks at the latest trends in AI/ML automation and how they will speed adoption across industries.

COVID-19 has impacted businesses across the globe, from closures to supply chain interruptions to resource scarcity. As businesses adjust to the new normal, many are looking to do more with less and find ways to optimize their current business investments.

In this resource-constrained environment, many types of business investments have slowed dramatically. That said, investments in AI and machine learning are accelerated, according to a recentAdweek survey.

Adweek found two-thirds of business executives say COVID-19 has not slowed AI projects. In fact, some 40% of respondents told Adweek that the pandemic has accelerated their AI/ML efforts. Reasons for the sustained and growing interest in AI/ML include decreasing costs, improving performance, and increasing efficiencies-all efforts to make up for time and output lost during the COVID-19 slowdown.

Despite the rosy outlook for AI/ML investments, it bears mentioning that businesses also admit they still struggle to scale these technologies beyond PoCs (proof of concepts). This is due to an ongoing talent shortage in the data science field a shortage that COVID has made even more acute.

Data science is an interdisciplinary approach that requires cross-domain expertise, including mathematics, statistics, data engineering, software engineering, and subject matter expertise.

The shortage of data scientists as well as data architects, machine learning engineers skilled in building, testing, and deploying ML models has created a big challenge for businesses implementing AI and ML initiatives, limiting the scale of data science projects and slowing time to production. The scarcity of data scientists has also created a quandary for organizations: how can they change the way they do data science, empowering the teams they already have?

The democratization of data science is very important and a current industry trend, but true democratization has never been easy for organizations. Analytics and data science leaders lament their team's ability to only manage a few projects per year. BI leaders, on the other hand, have been trying to embed predictive analytics in their dashboards but face the daunting task of learning how to build AI/ML models. What can organizations do, what tactics will help them to scale AI initiatives and bridge the gap between what is required and what's available?

Democratization of data science in a true sense is to empower teams with advanced analytical tools and automation technologies.

These tools can significantly simplify tasks that formerly could only be completed by data scientists. They are empowering business analysts, BI developers and data engineers to execute AI and machine learning projects. Further, they accelerate data science processes with very little training.

Notable among these offerings are:

This class of automation tools removes much of the time and expense to design and deploy AI-powered analytics pipelines and do so little cost and without high-priced technical staff.

Today, s typical data team is interdisciplinary and consists of data engineers, data analysts and data scientists. The data analyst and engineer are responsible for cleaning, formatting and preparing data for the data scientist who then uses analytics-ready data to build features and then build ML models using a trial and error approach.

Data science processes are complicated, highly manual, and iterative in nature. Depending on the maturity of the data pipelines, a data science project can take from 30 to 90 days to complete with nearly 80% of the effort spent on AI-focused data preparation and Feature Engineering.

Further, the AI-focused data preparation process requires an impressive amount of hacking skills from developers, data scientists and data engineers to clean, manipulate and transform the data to enable data scientists to execute feature engineering.

That said, the landscaping is changing. Tools are now surfacing to deliver AI automation to pre-process data, connect to data and automatically build features and ML models. These results eliminate the need for having a large team and doing it efficiently at the greatest possible speed.

In addition, feature engineering automation has vast potential to change the traditional data science process. Feature engineering involves the application of business knowledge, math, and statistics to transform data into a format that can be directly consumed by machine learning models.

It also can significantly lower skill barriers beyond ML automation alone, eliminating hundreds or even thousands of manually-crafted SQL queries, and ramps up the speed of the data science project even without a full light of domain knowledge).

Organizations with large data science teams will also find automation platforms very valuable. They free up highly-skilled resources from many of the manual and time-consuming efforts involved in data science and machine learning workflow and allow them to focus on more complex and challenging strategic tasks.

The trend is definitely to leverage automation technologies to speed-up the ML development process. By using AI automation technologies, BI and junior data scientist can automatically build models. This frees up time for experienced data scientists who take on more challenging business problems. While everyone seemed to focus on building automated ML models, the industry is definitely moving towards automating the entire AI/ML workflow.

This empowers data scientists to achieve higher productivity and drive greater business impact than ever before.

Another important tactic for bridging the skills gap in data science is ongoing skills training for the AI, data science and business intelligence teams.

Rather than hiring outside talent from an already shallow talent pool, companies are often better off investing time and resources in data-science training of their existing talent pool. These citizen data scientists can bridge the skill gap, address the labor shortage and enable companies to leverage the existing resources they already have.

There are many advantages to this approach.

Theidea is to build a team from inside the company versus hiring experts from outside. Any transformation is only going to succeed, provided it is embraced by the vast majority. Creating internal AI teams, empowering citizen data scientists and scaling pilot programs focused on AI is the right approach.

One of the most important of which is building data science skills across multiple teams to support data science's democratization across the organization. This strategy can be implemented by first identifying employees with existing programming, analytical and quantitative skills and then augmenting those skills with the required data science skills and tools training. Experienced data scientists can play the role of an evangelizer to share data science best practices and guide the citizen data scientists through the process.

AI and ML-driven innovation becomes indispensable as more enterprises transform themselves into data-driven organizations. Building a strong analytics team, while challenging in todays resource-scarce environment, is attainable by using appropriate automation tools. The benefits of this approach include:

These factors can not only help fill the skills gap but will help accelerate both data science and business innovation, delivering greater and broader business impact.

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Bridging the Skills Gap for AI and Machine Learning - Integration Developers

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Machine Learning and AI Can Now Create Plastics That Easily Degrade – Science Times

Plastic pollutionis one of the most pressing environmental issues, and the increase in the production of disposable plastics does not help at all. These plastics would often take many years before they degrade, which poisons the environment. This has prompted efforts from nations to create a global treaty to help reduce plastic pollution.

A combination of machine learning and artificial intelligence has accelerated the design of making materials, including plastics, with properties that quickly degrade without harming the environment and super-strong lightweight plastics for aircraft and satellites that would one day replace the metals being used.

The researchers from the Pritzker School of Molecular Engineering (PME) at the University of Chicago published their study in Science Advances on October 21, which shows a way toward designing polymers using a combination of modeling and machine learning.

This is done through computational structuring of almost 2,000 hypothetical polymers that are large enough to train neural links that understand a polymer's properties.

(Photo: Pixabay)Machine Learning and AI Can Now Create Plastics That Easily Degrade

People have been using products with polymer, like plastic bottles, for so long as this material is very common in many things in the daily lives of humans.

Polymers are materials that have amorphous and disordered structures that even techniques for studying metals and crystalline materials developed by scientists have a hard time defining it. They are made of large atoms arranged in a very long string that might compromise millions of monomers.

Moreover, the length and sequence can affect the polymer molecule's properties that may vary depending on which the atoms are arranged. Due to that, a trial-and-error method will not be ideal to use because it is only limited, and generating the needed data for a rational design strategy would be very demanding, Phys.orgreported.

Fortunately, machine learning could solve this problem as researchers set to answer whether machine learning and AI can predict the properties of polymers based on their sequence. If this might be the case, how large of a dataset would be needed to teach underlying algorithms.

Read Also: P&G Aims to Halve Its Use of Virgin Petroleum Plastics by 2030: Here's How It Plans to Do So

The researchers used almost 2,000 computationally structured polymers that have different sequences in creating the database. They also ran molecular simulations to predict its behavior.

Juan de Pablo, Liew Family Professor of Molecular Engineering and lead researcher, said that they are unsure how many are the different polymer sequences needed to learn its behavior as it could be millions. Fortunately, only a few hundred would do, which means that they can now follow the same technique ad create a database to train the machine learning network.

Then the researchers proceeded to use the data that was learned in making the actual design of the new molecules. They were able to demonstrate to specify a desired property from the polymer, and using machine learning generated a set of polymer sequences that lead to specific properties.

Through this, companies can now design products that save the environment and design polymers that do exactly what they want to do. For instance, they could create polymers that could someday replace the metals used in aerospace or those used in biomedical devices. It could allow engineers to more affordable and sustainable polymer materials.

Read More: Unique Enzyme Combination Could Reduce Global Plastic Waste

Check out more news and information on Plastic Pollutionon Science Times.

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