The Ethics Of AI And Death – Big Easy Magazine

AI can now accurately predict death, but is that a prediction we want to hear?

In almost every industry, artificial intelligence (AI) is on the fast track to outpacing human endeavor. Machine learning technologies are already better than the average person at gaming, creating content and even building AI, and it appears they are only going from strength to strength.

As a result of their developing intelligence, the most common question AI critics have been asking is whether its ethical to be putting ourselves out of a job. YouTube video essayist CGP Grey put it best when he said that, by investing in AI development, we are steaming ahead towards a market in which humans need not apply without adequately preparing the population for that scenario.

However, there is another ethical question to ask about superhuman AI: do we truly want all our questions answered? Is there some knowledge that, given the option, wed actually prefer not to have? Perhaps the most profound piece of knowledge any one of us could have would be knowing when we die. The idea that we could predict death with 100% accuracy has been the subject of art and literature from Ancient Greece to modern science fiction and beyond, and its no wonder. The preservation of life is an evolutionary instinct and knowing whether and when that life will end is necessarily part of preserving it.

With regard to preserving and prolonging life, AI already has a very good track record. Frances AI in the hands of medical experts is a truly powerful tool to detect and deter disease. Deep learning technology based on retinal scans was shown to be a good indicator of cardiovascular health and a predictor of potential heart attacks, and also supremely accurate at indicating diabetes with the addition of expert assessment.

The greatest advantage of these early warning systems was the ability to anticipate treatment plans, particularly for conditions with potentially precipitous declines. One such disease is Alzheimers, the appearance of which can be hard to notice before the effects are irreversible. Thats why a 2017 study attempted to use machine learning to identify incipient Alzheimers dementia in patients. The system predicted the progression of dementia within the next 24 months and was accurate 84% of the time.

Considering all of this, its not all that surprising that AI is getting very good at predicting death. The most-quoted example of this was the University of Nottinghams study last year, which developed a deep- and machine-learning algorithm to predict premature death in patients aged 40 to 69.

Based on health data from 2006 to 2010 from over half a million people within the age range, the deep learning program was significantly more accurate in predicting death than the standard prediction models developed by a human expert. What this means in numbers is that the two AI algorithms were able to accurately identify 76% and 64% of subjects who died, respectively, while the human-generated prediction model predicted only 44%.

One of the lessons from the University of Nottingham study is that AI can be used to enhance human predictive models. The two systems used in the study arrived at their predictions by looking at different variables than the human model. While the human model leaned heavily on the ethnicity, gender, age, and physical activity of the subjects, one algorithm focussed on factors like body fat percentage and fruit and vegetable intake, while the most accurate algorithm looked mostly at job-related hazards and the consumption of alcohol and medication.

This means, that far from replacing scientists and healthcare professionals, AI can be used to shed new light on old problems, creating a partnership of humans and machines that could lead to new innovations.

However, the question still stands, how much do we want to know about our own mortality? Of course, the ability to identify life-risking habits and behaviors is an invaluable way to prevent unnecessary death and ease the burden on the healthcare industry worldwide. As systems become more sophisticated they will likely be able to identify specific actions and individual decisions that lead to a prolonged or foreshortened life. Insofar as prolonging life is the purpose of healthcare, AI certainly has a future as a tool to enhance the vital work of doctors and health scientists.

But at what point do we begin to shape our lives around the algorithm? Progressing to its logical conclusion, AI systems will likely soon have the ability to accurately predict the life expectancy of anyone. If you know you have 40 more years to live, how will that change the way you live those 40 years? What if it was 2 years?

Furthermore, is it possible that we are building a world in which we allow the predictions of machines to interfere with our ethical choices? A pregnant mother could know with near certainty that their baby will be born disabled from the moment of conception. How will that affect the ethical debate on abortion?

I do not have the answers to any of these questions I dont think anyone does but they begging to be asked. As we develop our technological abilities further, we need to assess how they affect our social and ethical lives.

Sources

Molly Crockett writes for UK writings and Academized. She is also an editor for Essay Roo. As a marketing writer, she shares her lifestyle and personal development advice with readers.

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The Ethics Of AI And Death - Big Easy Magazine

Global Machine Learning Market expected to grow USD XX.X million by 2025: Microsoft, IBM, SAP, SAS, Google, Amazon Web Services – Bulletin Line

Global Machine Learning Market research report presentation demonstrates and presents an easily understandable market depiction, lending crucial insights on market size, market share as well as latest market developments and notable trends that collectively harness growth in the global Machine Learning market.This detailed and meticulously composed market research report on the Machine Learning market discussed the various market growth tactics and techniques that are leveraged by industry players to make maximum profits in the Machine Learning market even amidst pandemic situation such as COVID-19.

The various components and growth propellants such as dominant trends, existing challenges and restrictions as well as opportunities have also been discussed at length. The report is designed to guide the business decisions of various companies and research experts who look forward to maket profitable decisions in the Machine Learning market.

Global Machine Learning Market 2020-26: Competitive Landscape Analytical ReviewMicrosoftIBMSAPSASGoogleAmazon Web ServicesBaiduBigMLFair Isaac Corporation (FICO)HPEIntelKNIMERapidMinerAngossH2O.aiOracleDomino Data LabDataikuLuminosoTrademarkVisionFractal AnalyticsTIBCOTeradataDell

This report also includes substantial inputs regarding the current competition spectrum and discusses pertinent details such as new product-based developments that various market players are targeting. Further, relevant inputs on M&A developments, business partnership, collaborations and commercial agreements have also been touched upon in this report on Machine Learning market.

Access Complete Report @ https://www.orbismarketreports.com/global-machine-learning-market-size-status-and-forecast-2019-2025-2?utm_source=Puja

By the product type, the market is primarily split into Professional ServicesManaged Services

By the end-users/application, this report covers the following segments BFSIHealthcare and Life SciencesRetailTelecommunicationGovernment and DefenseManufacturingEnergy and Utilities

What to expect from the report A complete analysis of the Machine Learning market Concrete and tangible alterations in market dynamics A thorough study of dynamic segmentation of the Machine Learning market A complete review of historical, current as well as potential foreseeable growth projections concerning volume and value A holistic review of the vital market alterations and developments Notable growth friendly activities of leading players

Regional Analysis of the Machine Learning Market: The report further proceeds with unravelling the geographical scope of the Machine Learning market. Additionally, a country-wise discussion with specific growth pockets have also been touched upon in the succeeding sections of this detailed report on the Machine Learning market.

North America (U.S., Canada, Mexico) Europe (U.K., France, Germany, Spain, Italy, Central & Eastern Europe, CIS) Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific) Latin America (Brazil, Rest of L.A.) Middle East and Africa (Turkey, GCC, Rest of Middle East)

Scope of the ReportThe discussed Machine Learning market has been valued at xx million US dollars in 2019 and is further projected to grow at xx million US dollars through the forecast span till 2026, growing at a CAGR of xx% through the forecast period.

For the convenience of complete analytical review of the Machine Learning market, 2019 has been identified as the base year and 2020-24 comprises the forecast period to make accurate estimation about the future growth prospects in the Machine Learning market.

Some Major TOC Points: Chapter 1. Report Overview Chapter 2. Global Growth Trends Chapter 3. Market Share by Key Players Chapter 4. Breakdown Data by Type and Application Chapter 5. Market by End Users/Application Chapter 6. COVID-19 Outbreak: Machine Learning Industry Impact Chapter 7. Opportunity Analysis in Covid-19 Crisis Chapter 9. Market Driving ForceAnd Many More

Further in the subsequent sections of the report, readers can get an overview and complete picture of all major company players, covering also upstream and downstream market developments such as raw material supply and equipment profiles as well as downstream demand prospects. This Machine Learning market report offers report readers with vital details on opportunities, primary stakeholders as well as high potential segments that trigger growth in the Machine Learning market.

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Target Audience:* Machine Learning Manufactures* Traders, Importers, and Exporters* Raw Material Suppliers and Distributors* Research and Consulting Firms* Government and Research Organizations* Associations and Industry Bodies

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Global Machine Learning Market expected to grow USD XX.X million by 2025: Microsoft, IBM, SAP, SAS, Google, Amazon Web Services - Bulletin Line

Meghan Markle, Prince Harry, and Prince Andrew’s Social Media Accounts Were Removed From the Royals’ Website – Yahoo Lifestyle

We Finally Know the Name of Meghan Markle and Prince Harrys Dog

Naturally, it has a special meaning.

After stepping back from their roles as working royals earlier this year, Prince Harry and Meghan Markle, as well as Prince Andrew, have had their social media accounts removed from the official royal family website.

People pointed out that Meghan MarkleandPrince Harry's@SussexRoyal Instagrampage andPrince Andrew'sTwitterandInstagram pages were removed from royal.uk earlier this month.

Meghan and Harry's account, of course, was shut down after they announced they would no longer be senior members of the royal family, and would be splitting their time between North America and the U.K.

"While you may not see us here, the work continues," they wrote in their last post. "Thank you to this community for the support, the inspiration and the shared commitment to the good in the world. We look forward to reconnecting with you soon. Youve been great!"

Prince Andrew, on the other hand, announced he would be stepping back from public duties amid the scandal over his close ties to convicted pedophile Jeffrey Epstein.

Story continues

It has become clear to me over the last few days that the circumstances relating to my former association with Jeffrey Epstein has become a major disruption to my familys work and the valuable work going on in the many organizations and charities that I am proud to support," he said in a statement last November. "Therefore, I have asked Her Majesty if I may step back from public duties for the foreseeable future, and she has given her permission."

He was later dropped from his patronages, though he has since returned to the spotlight for private functions.

RELATED: Prince Harry Wants to Completely "Redesign" Social Media

As People pointed out, Meghan, Harry,andPrince Andrew all still have bio pages on the royal family's website highlighting their key causes.

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Meghan Markle, Prince Harry, and Prince Andrew's Social Media Accounts Were Removed From the Royals' Website - Yahoo Lifestyle

Can The EU Create Its Own Cloud Platform? – Forbes

The EU is forming an alternative to US and Chinese cloud platforms called Gaia X. This effort will fail on so many fronts. It reminds me of Australias National Broadband Network (NBN) which still struggles for viability after spending an estimated $51 billion.

An idea for a new cloud platform

This CRN article reports: According to Germany's Federal Ministry for Economic Affairs and Energy, the Gaia-X cloud computing platform is expected to be ready to launch in early 2021. That would be a remarkable time frame although admittedly you can assemble a couple of racks of bare metal servers and run virtualized services on them in short order. But can you create the equivalent of AWS? Never.

Just look at the relative size of the major cloud providers. The combined market cap of the four largest cloud companies, Amazon, Microsoft, Google, and Alibaba is $4.8 trillion (1.569+1.578+1.001+.685). For comparison the GDP of the largest member of the EU, Germany, is $3.9 trillion. (I know, false equivalence, but I dont know how to calculate a market cap for a country.)

Admittedly, Airbus, a similar venture partnership between government and industry, has succeeded in creating and supporting an aerospace industry in Europe. It has not been a commercial success of course. One can make the argument that having a viable aerospace industry is critical to national security and therefore creating and operating a money losing business is still worth it. Can the same argument be made on the grounds of data privacy? I would argue no, especially when the real purpose is actually the opposite.

The era of digital mercantilismor, as the East West Institute calls it, Tech Nationalismwas ushered in after Edward Snowden revealed the extent of the NSAs digital tentacles as it reached into as many data sources as it could to collect everything. The blowback was predictable and is destined to harm the US dominance of the technology sector. Also revealed by Snowden was the vast partnerships between the NSA, the rest of the Five Eyes, and Sweden, Germany, and others. They too were beneficiaries of the NSAs systematic Hoovering of the worlds data.

The EU General Data Protection Act (GDPR) was crafted and enacted in the wake of Snowdens revelations. But note the carve out in GDPR for law enforcement data records and government agencies. Lets face it. Every intelligence agency wants to emulate the US and not be beholden to the NSA for favors in exchange for being able to tap into its data stores in Utah.

The three tech giants that own most of the cloud platform business in the US are rabidly competitive. Yes, we dont know the full extent of their relationship with the Intelligence Community. There is even a mechanism which, in the hands of an overly aggressive regime, could be abused: that of national security letters whereby the subject of a demand for data cannot even reveal the existence of the letter. But their business would be drastically harmed if they were discovered to be providing backdoors to the FBI or NSA and they resist such efforts with lobbying and teams of lawyers.

Organizations in the EU should be as leery of working with the US cloud providers as they would be with Chinese cloud providers. But there is an argument to be made against having a domestic cloud platform. Your own government, which has much more interest in your data than a foreign government does, could have unfettered access to your data. From a privacy perspective the people with the power to abuse your private data are your own government, not China.

The answer is not to trust any cloud provider. This is what the term zero-trust meant originally. You encrypt all of your data before it goes to the cloud and you protect the encryption keys with multiple layers of defense. Do the job right and you will know when a government agency wants your data. They will demand the keys or, if it is a foreign agency, they will attempt to steal your keys.

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Can The EU Create Its Own Cloud Platform? - Forbes

Bitcoin Price Seals Best Weekly Close in 2.5 Years: 5 Things to Know – Cointelegraph

Bitcoin (BTC) greets another week with a push to $12,000 and its highest weekly close since after it hit $20,000 will it return?

Cointelegraph takes a look at five things that stand to impact BTC price performance in the coming five days.

Bitcoin hitting $12,000 again early Monday was more than just a boon for traders in doing so, BTC/USD sealed its highest close on weekly time frames since January 2018.

This means that no single week of price action ended at such high levels since, including during the height of last years bull market.

Having pleased analysts for several months in the short term, Bitcoin thus followed through on longer timeframes a crucial move to cement the upward trajectory.

Now, investors seeking confirmation that the bull market will continue may well have received it versus daily and hourly developments, a multi-year high weekly close is significant.

BTC/USD was thus up 2.4% on the day, with weekly gains sitting at 7% and monthly returns at over 30%.

Price-wise, $12,000 represents the highest that Bitcoin has reached since June 2019, three months after a Q2 bull market took the cryptocurrency from $4,000 to $13,800 a level which this cycle has yet to reach.

BTC/USD 7-day price chart. Source: Coin360

Bitcoins price surge comes the week after United States president Donald Trump added to existing geopolitical tensions by banning Chinese social media platform TikTok.

The resulting escalation of ties with Beijing adds to existing weakness in the U.S. dollar and ongoing concerns over Coronavirus a perfect storm for a flight to safe haven assets.

At the same time, Trump signed a series of executive orders on Coronavirus stimulus, something which now has a curious impact on markets which are already subject to heavy intervention from the Federal Reserve.

This time around, however, the measures will have a smaller direct effect on the average American. A payroll tax delay, for example, does not go far enough in the eyes of critics.

This fake tax cut would also be a big shock to workers who thought they were getting a tax cut when it was only a delay, Bloomberg quoted Democratic Senator Ron Wyden as saying in a statement.

These workers would be hit with much bigger payments down the road.

It is this delaying the inevitable financial cost to personal wealth, which lies at the heart of the pro-Bitcoin argument high-time-preference economic behavior ultimately costs much more in the long term than the immediate benefit to the target audience.

Where Bitcoin might head in the short term is now less clear cut when considering its historical performance versus other macro assets.

The period since March, which saw a cross-asset crash, was marked first by a correlation to stock markets, and then to safe havens and specifically gold.

Gold hit its all-time highs in U.S. dollar terms weeks before Bitcoin began significantly gaining, and its run has continued until now.

A slight correction took XAU/USD to $2,030 from highs of near $2,075 should the trend continue, Bitcoin may likewise cool off from its upward momentum.

Nonetheless, as Cointelegraph reported, incoming action from the Fed looks set to buoy the precious metal further in a wildly bullish policy shift to expanding inflation way beyond its current rate of 0.6%.

Stocks were likewise looking less stable analysts were warning over fallout for developing markets thanks to Turkeys currency crisis, and China sanctioning U.S. officials over Hong Kong added to pressure.

Bitcoin up as tensions rise in Asia. Capital flight out of Asia taking the Bitcoin express, RT host Max Keiser summarized, adding:

You cant take it with you, unless its Bitcoin - then you can take IT ALL with you (Something near impossible with Gold).

Another volatile weekend has opened up a classic feature for short-term Bitcoin price forecasting a gap in CME Bitcoin futures markets.

The weekends volatility means that futures finished Friday at $11,680 and began again at $11,750. The resulting void provides a key price target, with Bitcoin historically filling such gaps within days or even hours.

Last week saw just such a setup emerge, with volatility aiding the trend after weeks of flat price action removed gaps from the market altogether.

Another gap lower down at $9,700 still remains from July.

CME Bitcoin futures chart showing recent latest gaps. Source: TradingView

For quant analyst PlanB, creator of Bitcoins stock-to-flow price forecasting model, the bullish action of the past weeks is exactly to be expected.

Earlier in August, PlanB noted that BTC/USD was filling out the stock-to-flow chart according to historical precedent since Mays block subsidy halving, dots have confirmed that current behavior falls within the rules.

Bitcoin stock-to-flow chart as of August 10. Source: Digitalik

On the topic of major players flipping bullish, meanwhile, he added last week that when bitcoin was $4k in 2019, lot of big accounts were bearish, predicting $1k.

Behind the scenes, however, signs were that if $6,000 appeared, the mood would change to favor the bulls.

That actually happened, we shot through $6k. Now many were bearish at $9k .. $13.5k will be interesting, PlanB wrote.

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Bitcoin Price Seals Best Weekly Close in 2.5 Years: 5 Things to Know - Cointelegraph

Machine Learning Market Emerging Trends, Business Opportunities, Segmentation, Production Values, Supply-Demand, Brand Shares and Forecast 2020-2027 -…

Machine Learning Market Report Forecast to 2027

Reports and Data has added a new research report titled Global Machine Learning Market to its extensive database. The report thoroughly explains the market dynamics from vital industry data to accurate estimation in the forecast years. It comprises of all the crucial segments of the changing dynamics of the market. The information can be beneficial for readers to gain a robust footing in the global market.

The report mainly focuses on the types, applications, overview, and major players in the Machine Learning market. The report provides historical data from 2017-2018 and industrial development trends and growth patterns for the forecast years 2020-2027. The report is updated with the latest economic scenario due to the global COVID-19 crisis. The pandemic has brought dynamic changes in the major segments of the market. The report covers the present and future impact of the COVID-19 crisis and the economic scenario post-COVID-19.

Get a sample of the report @ https://www.reportsanddata.com/sample-enquiry-form/2149

The report on the global Machine Learning market consists of up-to-date financial data formulated by extensive research to provide accurate analysis. The report also consists of the evaluation of key market trends, in-depth analysis of segmentations, and sub-market categorization on a regional and global scale. The report also provides strategic recommendations to key market players and new entrants based on current emerging trends.

Key players of the market mentioned in the report are:

IBM Corporation, Microsoft Corporation, SAP SE, Dell Inc., SAS Institute Inc., Google, Inc., Amazon Web Services Inc., Baidu, Inc., BigML, Inc., Intel Corporation, RapidMiner, Inc., Hewlett Packard Enterprise (HPE), Angoss Software Corporation, Alpine Data, Dataiku, Luminoso Technologies, Inc., TrademarkVision, Fractal Analytics Inc., TIBCO Software Inc., Teradata, and Oracle Corporation, among others.

The report provides an in-depth analysis of production cost, market segmentation, end-use applications, and industry chain analysis. The report provides CAGR, value, volume, revenue, and other key factors related to the global Machine Learning market. All the findings and data have been gathered through extensive primary and secondary research and are validated by industry experts and research analysts.

The report further studies the segmentation of the market based on product types offered in the market and their end-use/applications.

Component Outlook (Revenue, USD Billion; 2016-2026)

SoftwareAccess controlSecurity intelligenceBig data governance

Cloud and Web-based Application Programming Interface (APIs)OthersServicesManaged servicesProfessional servicesSupport and MaintenanceSystem IntegrationTraining

Organization Size Outlook (Revenue, USD Billion; 2016-2026)

Small and Medium-Sized EnterprisesLarge Enterprises

Application Outlook (Revenue, USD Billion; 2016-2026)

Fraud Detection & Risk AnalyticsAugmented & Virtual realityNatural Language processingComputer visionSecurity & surveillanceMarketing & AdvertisementAutomated Network ManagementPredictive MaintenanceOthers

Industry Vertical Outlook (Revenue, USD Billion; 2016-2026)

AutomotiveAerospace & DefenseRetail & E-commerceGovernmentHealthcare And Life SciencesMedia And EntertainmentIT And TelecommunicationsBanking, Financial Services, And InsuranceOthers

Request customization of the report @ https://www.reportsanddata.com/request-customization-form/2149

Major geographical regions studied in this report include:

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Key points covered in the report:

To get the Report Description and TOC, visit @ https://www.reportsanddata.com/report-detail/machine-learning-market

Thank you for reading our report. Please get in touch with us if you wish to request a customization of the report. Our team will ensure you get a report well-suited for your needs.

David is an Experience Business writer who regularly contributes to the blog, He specializes in manufacturing news

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Machine Learning Market Emerging Trends, Business Opportunities, Segmentation, Production Values, Supply-Demand, Brand Shares and Forecast 2020-2027 -...

Stanford Center for Health Education Launches Online Program in Artificial Intelligence in Healthcare to Improve Patient Outcomes – PRNewswire

STANFORD, Calif., Aug. 10, 2020 /PRNewswire/ --TheStanford Center for Health Education launched an online program in AI and Healthcare this week. The program aims to advance the delivery of patient care and improve global health outcomes through artificial intelligence and machine learning.

The online program, taught by faculty from Stanford Medicine, is designed for healthcare providers, technology professionals, and computer scientists. The goal is to foster a common understanding of the potential for AI to safely and ethically improve patient care.

Stanford University is a leader in AI research and applications in healthcare, with expertise in health economics, clinical informatics, computer science, medical practice, and ethics.

"Effective use of AI in healthcare requires knowing more than just the algorithms and how they work," said Nigam Shah, associate professor of medicine and biomedical data science, the faculty director of the new program. "Stanford's AI in Healthcare program will equip participants to design solutions that help patients and transform our healthcare system. The program will provide a multifaceted perspective on what it takes to bring AI to the clinic safely, cost-effectively, and ethically."

AI has the potential to enable personalized care and predictive analytics, using patient data. Computer system analyses of large patient data sets can help providers personalize optimal care. And data-driven patient risk assessment canbetter enable physicians to take the right action, at the right time. Participants in the four-course program will learn about: the current state, trends and implications of artificial intelligence in healthcare; the ethics of AI in healthcare; how AI affects patient care safety, quality, and research; how AI relates to the science, practice and business of medicine; practical applications of AI in healthcare; and how to apply the building blocks of AI to innovate patient care and understand emerging technologies.

The Stanford Center for Health Education (SCHE), which created the AI in Healthcare program, develops online education programs to extend Stanford's reach to learners around the world. SCHE aims to shape the future of health and healthcare through the timely sharing of knowledge derived from medical research and advances. By facilitating interdisciplinary collaboration across medicine and technology, and introducing professionals to new disciplines, the AI in Healthcare program is intended to advance the field.

"In keeping with the mission of the Stanford Center for Health Education to expand knowledge and improve health on a global scale, we are excited to launch this online certificate program on Artificial Intelligence in Healthcare," said Dr. Charles G. Prober, founding executive director of SCHE. "This program features several of Stanford's leading thinkers in this emerging field a discipline that will have a profound effect on human health and disease in the 21st century."

The Stanford Center for Health Education is a university-wide program supported by Stanford Medicine. The AI in Healthcare program is available for enrollment through Stanford Online, and hosted on the Coursera online learning platform. The program consists of four online courses, and upon completion, participants can earn a Stanford Online specialization certificate through the Coursera platform. The four courses comprising the AI in Healthcare specialization are: Introduction to Healthcare, Introduction to Clinical Data, Fundamentals of Machine Learning for Healthcare, and Evaluations of AI Applications in Healthcare.

SOURCE Stanford Center for Health Education

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Stanford Center for Health Education Launches Online Program in Artificial Intelligence in Healthcare to Improve Patient Outcomes - PRNewswire

With All Eyes On Bitcoin, Another Crypto Is Up 500% In The Last YearAnd Its Still Soaring – Forbes

Bitcoin has been pushed back into the spotlight thanks to its recent rally and renewed interest from Wall Street and big-name day traders.

The bitcoin price, jumping over $12,000 per bitcoin late Sunday evening, has added 30% in the last monththough some smaller cryptocurrencies have made far bigger gains.

Chainlink's link token has now added 120% to its price in the last month, climbing to over $13 per token, and building on gains of around 500% during the last yearwith some investors saying link is still "wildly undervalued."

Traders have sent the price of Chainlink's link token sharply higher over recent months, dwarfing ... [+] bitcoin's latest rally.

"Chainlink is on track to function as [the decentralized web3's] de facto security layer for any and all transactions of meaningful value," Michael Anderson, co-founder of Framework Ventures, the largest private holder of link tokens outside of the core team and bitcoin and crypto exchanges, said via email.

"We believe the value of link will track the value of the smart contract platform it is securing, meaning the long term market cap of link will eventually be larger than ethereums current market cap today."

Chainlink, an ethereum-based token that powers a decentralized network designed to connect smart contracts to external data sources, currently has market capitalization of just under $5 billion compared to ethereum's $45 billion.

Chainlink, up 65% in the last week alone, has has been boosted in recent months by a surge of interest in decentralized finance (DeFi)the idea that blockchain entrepreneurs can use bitcoin and crypto technology to recreate traditional financial instruments such as loans and insurance.

"As it stands, blockchains are unable to speak in a trustless way with real world data, meaning they require some sort of blockchain abstraction layer that lies between the blockchain and the outside world," said Anderson, adding Chainlink's importance has "become more apparent as billions of dollars have been locked up in DeFi products reliant on smart contracts."

Since early June, the total value locked in DeFi protocols has risen from around $1 billion to almost $5 billion, according to data from DiFi Pulse.

Meanwhile, the cryptocurrency token of a Chainlink competitor, band, the native token of Band Protocol, has also soared in recent weeks. Band, ranked 43rd on CoinMarketCap's list of most valuable cryptocurrencies compared to link's 6th, has added almost 5,000% since its rally began in early April.

Over the weekend, trading of Chainlinks link token surged, knocking bitcoin off the top spot on the largest U.S. bitcoin and cryptocurrency exchange, Coinbase, to become the most traded cryptocurrency on the popular platform over a 24-hour period.

Links 24-hour trading volume on Coinbase Pro climbed to $163 million, some 70% higher than bitcoins trading volume of $96 million, according to data from bitcoin and crypto analysis firm Messari.

However, around the world, link's 24-hour trading volume of just over $3 billion is still just a fraction of bitcoin's $17 billion.

The price of Chainlink's link token has more than doubled in value over the last month, far ... [+] outpacing bitcoin's 30% rally.

Despite link's massive rally and suggestions link's price could be a swelling bubble about to pop, Anderson is confident the link price will continue to climb, pointing to Chainlink's ambitions to work with smart contracts "for any transaction that requires real world data, events and payment" and plans to for so-called staking, meaning "users will be able to stake their link as collateral with Chainlink nodes, allowing them to earn a passive income stream when said nodes complete jobs by providing useful data to smart contracts."

"A correction is possible in the short term, but even if the link price were to double tomorrow, wed still think it's wildly undervalued in light of the long term vision," Anderson added.

"If they achieve even a fraction of what theyve set out to do, the implications for enterprise, banking, derivatives, insurance and more will be enormous."

Link's surge over the last week has been put down to a massive short squeeze in the futures market, according to reports, leading some to warn its rally may not hold.

"Chainlink can be a very bubbly asset and it looks very bubbly now," cautioned chartered alternative investment analyst and manager at Cane Island Alternative Advisors, Timothy Peterson, via Twitter.

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With All Eyes On Bitcoin, Another Crypto Is Up 500% In The Last YearAnd Its Still Soaring - Forbes

Bitcoin is on rampage as it breaks through $12000 price level – Nairametrics

Its crypto. Its physical gold. And recently, it was approved by the New York State Department of Financial Services for custody and listing. Its a product from the crypto-verse that combines gold and crypto into a single unit.

Data from Coinmarketcap showed PAX Gold traded at about $1,521 as of March 21, 2020. As of the time of writing this report, the crypto asset was trading at about $2,039.40, showing gains in percentage terms of about 134%. Meanwhile, Gold price so far has gained just 35% in 2020.

READ MORE: ChainLinks digital coin skyrockets 388% in 130 days, still soaring

Why PAX Gold: The sudden surge in this gold-backed stablecoin, since the era of the COVID-19 pandemic, appears to be driven by increased awareness of its unique features, which include access to gold without bullion fees or other storage costs.

Quick fact: PAX Gold (PAXG) is a crypto asset backed by Gold. A PaxoGold digital coin is backed by one fine troy ounce (t oz) of a 400 oz London Good Delivery gold bar, stored in Brinks gold vaults. Any entity or individual who owns PAX Gold owns the underlying physical gold held in custody by Paxos Trust Company.

READ MORE: QKC: fastest rising crypto asset in 30 days, gains 100%

Paxos has recently responded to all its digital coins being listed on the New York State Department of Financial Services (NYDFS), stating that it validated the companys time, energy, and expense which it put into compliance.

Commenting on the green list, Dan Burstein, Chief Compliance Officer at Paxos said: As the Chief Compliance Officer at Paxos, Im proud that the culture of Paxos is truly centered around compliance. We build products that the world has never seen before, and we build them for the innovators in the space, not the bad actors.

Our engineers and product managers prioritize compliance as we create new products, our business development team considers compliance as we structure new partnerships, our operations team helps onboard and service customers according to our high compliance standards, our information security team ensures we hold our customers digital assets and personal information in the most secure way possible the list goes on.

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Bitcoin is on rampage as it breaks through $12000 price level - Nairametrics

Bitcoin and Ripples XRP Weekly Technical Analysis August 10th, 2020 – Yahoo Finance

Bitcoin

Bitcoin rose by 5.57% in the week ending 9th August. Following on from an 11.11% rally from the previous week, Bitcoin ended the week at $11,675.3.

It was a bullish week for Bitcoin and the broader market. Bitcoin slipped to a Monday intraweek low $10,943.0 before making a move.

Steering clear of the first major support level at $9,967, Bitcoin rallied to a Friday intraweek high $11,900.

Falling short of the weeks first major resistance level at $12,119, Bitcoin fell back to $11,500 levels before finding support.

5 days in the green that included a 4.93% rally on Wednesday delivered the upside for the week.

Bitcoin would need to avoid a fall through $11,506 pivot to support another run the first major resistance level at $12,069 into play.

Support from the broader market would be needed for Bitcoin to break out from the current week high $12,060.

Barring another extended crypto rally, the first major resistance level would likely cap any upside.

In the event of a breakout, Bitcoin could break out from the second major resistance level at $12,463 to target $13,000 levels.

A fall through the $11,506 pivot would bring the first major support level at $11,112 into play.

Barring an extended sell-off, Bitcoin should avoid sub-$11,000 levels and the second major support level at $10,549.

At the time of writing, Bitcoin was up by 2.80% to $12,002.0. A bullish start to the week saw Bitcoin rise from an early morning low $11,675.3 to a high $12,060 on Monday.

Bitcoin tested the first major resistance level at $12,069 at the start of the week.

Ripples XRP slipped by 0.04% in the week ending 9th August. Following the previous weeks 33.50% breakout, Ripples XRP ended the week at $0.28781.

A bullish start to the week saw Ripples XRP rally to a Monday intraweek high $0.31950 before hitting reverse.

Falling short of the first major resistance level at $0.3395, Ripples XRP slid to a Friday intraweek low $0.27742.

Steering well clear of the first major support level at $0.22249, Ripples XRP revisited $0.29 levels before slipping back to sub-$0.29 levels and into the red.

3-days in the red reversed Mondays 7.68% rally to leave Ripples XRP in the red for the week.

Ripples XRP would need to avoid a fall through the $0.29491 pivot to support a run at the first major resistance level at $0.31240.

Support from the broader market would be needed, however, for Ripples XRP to break back through to $0.31 levels.

Barring an extended crypto rally, the first major resistance level would likely cap any upside.

In the event of another breakout, 23.6% FIB of $0.3134 and the second major resistance level at $0.33699 could come into play.

A fall through the $0.29491 pivot would bring the first major support level at $0.27032 into play.

Barring an extended broader-market sell-off, however, Ripples XRP should steer well clear of the second major support level at $0.25283.

At the time of writing, Ripples XRP was up by 2.62% to $0.29536. A bullish start to the week saw Ripples XRP rise from an early Monday low $0.28821 to a high $0.29550.

Ripples XRP left the major support and resistance levels untested at the start of the week.

This article was originally posted on FX Empire

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Bitcoin and Ripples XRP Weekly Technical Analysis August 10th, 2020 - Yahoo Finance