Data, not code, will dictate systems of the future, says Tecton.ai – SiliconANGLE News

Posted on May 27, 2020 by admin

As many companies struggle in the midst of the COVID-19 pandemic, Tecton.ai has managed to garner a $20-million investment fromAndreessen Horowitz and Sequoia Capitalin April 2020.

Tecton.ai was founded by members who created Uber Inc.s Michelangelo, an end-to-end workflow that enablesinternal teamsto seamlessly build, deploy and operate machine-learning solutionsatscale. Through the lessons learned at Uber, the founders of Tecton branched out to create a world-class data platform for machine learning accessible to every company.

So why did this appeal so much to investorslike Andreessen Horowitz? Because while data is the future, wrangling data is still one of the most complex tasks that organizations and data scientists can do. And tools that incorporate machine learning must continue to be developed in order to help enterprises understand the overwhelmingly vast world of data.

I actually think this is probably the biggest shift certainly Ive seen in my career, saidMartin Casado(pictured, left), general partner at Andreessen Horowitz. It used to be if you looked at a system you wrote bad code, you made bugs, you had vulnerabilities in your code that would dictate the system. But more and more, thats actually not the case. You create these models, you feed the data models, the data gives you output, and your workflows around those models are really dictating things.

CasadoandMike Del Balso(pictured, right), co-founder and chief executive officer of Tecton, spoke with Stu Miniman,host of theCUBE, SiliconANGLE Medias livestreaming studio,during a digital CUBE Conversation. They discussed Tectons future, machine learning, and the importance of the data industry.(* Disclosure below.)

The importance of data cant be overstated, according to Casado. I honestly think the data industry is going to be 10 times the computer industry, he said. With compute, youre building houses from the ground up, and theres a ton of value there. With data youre extracting insight and value from the universe, right? Its like the natural system.

In 2020, 90% of business professionals and enterprise analytics say data and analytics are key to their organizations digital transformation initiatives, according to a recent study by Acute Market Reports. Both Casado and Del Balso believe that Tecton has a chance to be a very pivotal company in democratizing access to data. The opportunity is enormous because data is still hard to capture, clean up, and interpret in effective ways. In fact, almost three-quarters (73.5%) of recent survey respondents said they spend 25% or more of their time managing, cleaning, and/or labeling data, according to an Appen Ltd.whitepaper.Andthe demand for data scientists increased32% in 2019 compared to the previous year, according to aDice Tech Jobsreport released in February.

What we dont really know is, how do you take data and reign it in so you can use it in the same way that you use software system? Casado stated. Talking about things like data network effects and extracting data is a little bit preliminary, because we still actually dont even understand how much work it takes to mine insights from data. So I think that were now in this era building the tooling that is required to extract the insights of that data. And I think thats a very necessary step, and this is where a Tecton comes in to provide that tooling.

Tecton is a data platform for machine learning that manages all the feature data and transformations to allow an organization to share predictive signals across use cases and understand what they are, according to Del Balso. During their time with Uber, Del Balsoand the other founders of Tectonrecognized that a feature management layer was the component that really allows a company to scale out machine learning across a number of different use cases, and allows individual data scientists to own more than just one model in production.

In a machine-learning application, theres fundamentally two components, right? Theres a model that you have to build thats going to make the decisions given a certain set of inputs, and then theres the features, which end up being those inputs that the model uses to make the decision, Del Balso explained. And common machine-learning infrastructure stats really are split into two layers. Theres a model management layer and a feature management layer, and thats an emerging pattern in some of the more sophisticated machine-learning stacks that are out there.

At the core of Tectons strategyare a few simple components. The first is feature pipelines, which are data pipelines that plug into a business raw data and turn them into features with predictive signals. The second part of that is a feature store, which catalogs these pipelines and draws the output feature data. The third component is feature service and making data accessible to a data scientist when theyre building their models so they can make these decisions, which is sometimes needed in milliseconds for real-time decisioning.

Were at private beta with a number of customers, Del Balso said. We are spending time engaging in deep, hands-on engagements with different teams who are really trying to set up their machine learning on the cloud, figuring out how to get their machine learning in production. And it tends to be teams that are trying to really use machine learning for operational use cases really trying to drive real business decisions and power their product customer experiences.

Watch the complete video interview below, and be sure to check out more of SiliconANGLEs and theCUBEsCUBE Conversations.

Show your support for our mission with our one-click subscription to our YouTube channel (below). The more subscribers we have, the more YouTube will suggest relevant enterprise and emerging technology content to you. Thanks!

Support our mission: >>>>>> SUBSCRIBE NOW >>>>>> to our YouTube channel.

Wed also like to tell you about our mission and how you can help us fulfill it. SiliconANGLE Media Inc.s business model is based on the intrinsic value of the content, not advertising. Unlike many online publications, we dont have a paywall or run banner advertising, because we want to keep our journalism open, without influence or the need to chase traffic.The journalism, reporting and commentary onSiliconANGLE along with live, unscripted video from our Silicon Valley studio and globe-trotting video teams attheCUBE take a lot of hard work, time and money. Keeping the quality high requires the support of sponsors who are aligned with our vision of ad-free journalism content.

If you like the reporting, video interviews and other ad-free content here,please take a moment to check out a sample of the video content supported by our sponsors,tweet your support, and keep coming back toSiliconANGLE.

More here:
Data, not code, will dictate systems of the future, says Tecton.ai - SiliconANGLE News

Machine Learning as a Service (MLaaS) Market Down To A Trickle Month Other Covid-19 Traders Cling On The Hope. – Cole of Duty

Posted on May 27, 2020 by admin

CMI announced that its published an exclusive report namelyGlobal Machine Learning as a Service (MLaaS) Marketby Manufacturers, Regions, Type and Application, Forecast to 2027 in its research database with report summary, table of content, research methodologies and data sources. The research study offers a substantial knowledge platform for entrants and investors as well as veteran companies, manufacturers functioning in the WorldwideMachine Learning as a Service (MLaaS)Market. This is an informative study covering the market with in-depth analysis and portraying the current state of affairs in the industry.

You Keep Your Social Distance And We Provide You A SocialDISCOUNTUseQUARANTINEDAYSCode In Precise Requirement And GetFLAT $1,000OFFOn AllCMI Reports

Read Summary Of Machine Learning as a Service (MLaaS) Market Report @ Machine Learning as a Service (MLaaS) Market

The report presents an overview of Machine Learning as a Service (MLaaS) Market consist of objectives study and definition of Machine Learning as a Service (MLaaS). The next section focuses on market size, region-wise Machine Learning as a Service (MLaaS) production value ($) and growth rate estimation from 2020-2027. Manufacturers are taking innovative strategies to increase the market share of their products. The success of new product launches is expected to speedup players for business growth.

Key Manufacturers Analysis:H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc.

The top manufacturers, exporters, and retailers (if applicable) around the world are analyzed for this research report with respect to their company profile, product portfolio, capacity, price, cost, and revenue.

We do provide Sample of this report, Please go through the following information in order to request Sample Copy

ThisReportSampleIncludes

Get Sample Copy Of This Report @ https://www.coherentmarketinsights.com/insight/request-sample/3718

Machine Learning as a Service (MLaaS) Market 2020 Forecast to 2027 Market Segment by Regions, regional analysis covers

Machine Learning as a Service (MLaaS) MarketTaxonomy:

Global Machine Learning as a Service (MLaaS) Market, By Deployment:

Global Machine Learning as a Service (MLaaS) Market, By End-use Application:

Following market aspects are enfolded in Global Machine Learning as a Service (MLaaS) Market Report:

A wide summarization of the Global Machine Learning as a Service (MLaaS) Market. The present and forecasted regional market size data based on applications, types, and regions. Market trends, drivers and challenges for the Global Machine Learning as a Service (MLaaS) Market. Analysis of company profiles of Top major players functioning in the market.

Machine Learning as a Service (MLaaS) Market report passes on a fundamental overview of the Market including its definition, applications, and advancement. Furthermore, the Industry report investigates the ecumenical Major Machine Learning as a Service (MLaaS) Market players in detail.Machine Learning as a Service (MLaaS) Market report gives key bits ofCautiousness and subsisting status of the Players and is a basic Source obviously and heading for Companies and people energized by the Industry.

Note: Request Discount option enables you to get the discounts on the actual price of the report. Kindly fill the form, and one of our consultants would get in touch with you to discuss your allocated budget, and would provide discounts.

UseQUARANTINEDAYSCode In Precise Requirement And GetFLAT $1,000OFFOnThisReports

Ask Discount Before Purchasing @ https://www.coherentmarketinsights.com/insight/request-discount/3718

Key questions answered in Report:-

Machine Learning as a Service (MLaaS) Business Analysis Including Size, Share, Key Drivers, Growth Opportunities and Trends 2020- 2027 Consumption Analysis of Machine Learning as a Service (MLaaS), Guidelines Overview and Upcoming Trends Forecast till 2027 Machine Learning as a Service (MLaaS) Market Top Companies Sales, Price, Revenue and Market Share Outlook Machine Learning as a Service (MLaaS) Revenue, Key Players, Supply-Demand, Investment Feasibility and Forecast 2027 Analytical Overview, Growth Factors, Demand and Trends Machine Learning as a Service (MLaaS) by Technology, Opportunity Analysis and Industry Forecasts, 2020- 2027 Analysis Covering Market Size, Growth Factors, Demand, Trends and Forecast Machine Learning as a Service (MLaaS) Overview, Raw Materials Analysis, Market Drivers and Opportunities In-depth Research on Market Size, Trends, Emerging Growth Factors and Forecasts.

Conclusively, this report will provide you a clear view of each fact of the market without a need to refer to any other research report or a data source. Our report will provide you with all the facts about the past, present, and future of the concerned Market.

Mr. ShahCoherent Market Insights1001 4th Ave, #3200 Seattle, WA 98154Tel: +1-206-701-6702Email: [emailprotected]

AlsoCheckout our latest Blog at: http://bit.ly/Sumit

Teaching machine learning to check senses may avoid sophisticated attacks – University of Wisconsin-Madison

Posted on May 27, 2020 by admin

Complex machines that steer autonomous vehicles, set the temperature in our homes and buy and sell stocks with little human control are built to learn from their environments and act on what they see or hear. They can be tricked into grave errors by relatively simple attacks or innocent misunderstandings, but they may be able to help themselves by mixing their senses.

In 2018, a group of security researchers managed to befuddle object-detecting software with tactics that appear so innocuous its hard to think of them as attacks. By adding a few carefully designed stickers to stop signs, the researchers fooled the sort of object-recognizing computer that helps guide driverless cars. The computers saw an umbrella, bottle or banana but no stop sign.

Two multi-colored stickers attached to a stop sign were enough to disguise it to the eyes of an image-recognition algorithm as a bottle, banana and umbrella. UW-Madison

They did this attack physically added some clever graffiti to a stop sign, so it looks like some person just wrote on it or something and then the object detectors would start seeing it is a speed limit sign, says Somesh Jha, a University of WisconsinMadison computer sciences professor and computer security expert. You can imagine that if this kind of thing happened in the wild, to an auto-driving vehicle, that could be really catastrophic.

The Defense Advanced Research Projects Agency has awarded a team of researchers led by Jha a $2.7 million grant to design algorithms that can protect themselves against potentially dangerous deception. Joining Jha as co-investigators are UWMadison Electrical and Computer Engineering Professor Kassem Fawaz, University of Toronto Computer Sciences Professor Nicolas Papernot, and Atul Prakash, a University of Michigan professor of Electrical Engineering and Computer Science and an author of the 2018 study.

Kassem Fawaz

One of Prakashs stop signs, now an exhibit at the Science Museum of London, is adorned with just two narrow bands of disorganized-looking blobs of color. Subtle changes can make a big difference to object- or audio-recognition algorithms that fly drones or make smart speakers work, because they are looking for subtle cues in the first place, Jha says.

The systems are often self-taught through a process called machine learning. Instead of being programmed into rigid recognition of a stop sign as a red octagon with specific, blocky white lettering, machine learning algorithms build their own rules by picking distinctive similarities from images that the system may know only to contain or not contain stop signs.

The more examples it learns from, the more angles and conditions it is exposed to, the more flexible it can be in making identifications, Jha says. The better it should be at operating in the real world.

But a clever person with a good idea of how the algorithm digests its inputs might be able to exploit those rules to confuse the system.

DARPA likes to stay a couple steps ahead, says Jha. These sorts of attacks are largely theoretical now, based on security research, and wed like them to stay that way.

A military adversary, however or some other organization that sees advantage in it could devise these attacks to waylay sensor-dependent drones or even trick largely automated commodity-trading computers run into bad buying and selling patterns.

Somesh Jha

What you can do to defend against this is something more fundamental during the training of the machine learning algorithms to make them more robust against lots of different types of attacks, says Jha.

One approach is to make the algorithms multi-modal. Instead of a self-driving car relying solely on object-recognition to identify a stop sign, it can use other sensors to cross-check results. Self-driving cars or automated drones have cameras, but often also GPS devices for location and laser-scanning LIDAR to map changing terrain.

So, while the camera may be saying, Hey this is a 45-mile-per-hour speed limit sign, the LIDAR says, But wait, its an octagon. Thats not the shape of a speed limit sign, Jha says. The GPS might say, But were at the intersection of two major roads here, that would be a better place for a stop sign than a speed limit sign.

The trick is not to over-train, constraining the algorithm too much.

The important consideration is how you balance accuracy against robustness against attacks, says Jha. I can have a very robust algorithm that says every object is a cat. It would be hard to attack. But it would also be hard to find a use for that.

Share via Facebook

Share via Twitter

Share via Linked In

Share via Email

AI threat intelligence is the future, and the future is now – TechTarget

Posted on May 27, 2020 by admin

The next progression in organizations using threat intelligence is adding AI threat intelligence capabilities, in the form of machine learning technologies, to improve attack detection. Machine learning is a form of AI that enables computers to analyze data and learn its significance. The rationale for using machine learning with threat intelligence is to enable computers to more rapidly detect attacks than humans can and stop those attacks before more damage occurs. In addition, because the volume of threat intelligence is often so large, traditional detection technologies inevitably generate too many false positives. Machine learning can analyze the threat intelligence and condense it into a smaller set of things to look for, thereby reducing the number of false positives.

This sounds fantastic, but there's a catch -- actually, a few catches. Expecting AI to magically improve security is unrealistic, and deploying machine learning without preparation and ongoing support may make things worse.

Here are three steps enterprises should take to use AI threat intelligence tools with machine learning capabilities to improve attack detection.

AI threat intelligence products that use machine learning work by taking inputs, analyzing them and producing outputs. For attack detection, machine learning's inputs include threat intelligence, and its outputs are either alerts indicating attacks or automated actions stopping attacks. If the threat intelligence has errors, it will give "bad" information to the attack detection tools, so the tools' machine learning algorithms may produce "bad" outputs.

Many organizations subscribe to multiple sources of threat intelligence. These include feeds, which contain machine-readable signs of attacks, like the IP addresses of computers issuing attacks and the file names used by malware. Other sources of threat intelligence are services, which generally provide human-readable prose describing the newest threats. Machine learning can use feeds but not services.

Organizations should use the highest quality threat intelligence feeds for machine learning. Characteristics to consider include the following:

It's hard to directly evaluate the quality of threat intelligence, but you can indirectly evaluate it based on the number of false positives that occur from using it. High-quality threat intelligence should lead to minimal false positives when it's used directly by detection tools -- without machine learning.

False positives are a real concern if you're using threat intelligence with machine learning to do things like automatically block attacks. Mistakes will disrupt benign activity and could negatively affect operations.

Ultimately, threat intelligence is just one part of assessing risk. Another part is understanding context -- like the role, importance and operational characteristics of each computer. Providing contextual information to machine learning can help it get more value from threat intelligence. Suppose threat intelligence indicates a particular external IP address is malicious. Detecting outgoing network traffic from an internal database server to that address might merit a different action than outgoing network traffic to the same address from a server that sends files to subscribers every day.

The toughest part of using machine learning is providing the actual learning. Machine learning needs to be told what's good and what's bad, as well as when it makes mistakes so it can learn from them. This requires frequent attention from skilled humans. A common way of teaching machine learning-enabled technologies is to put them into a monitor-only mode where they identify what's malicious but don't block anything. Humans review the machine learning tool's alerts and validate them, letting it know which were erroneous. Without feedback from humans, machine learning can't improve on its mistakes.

Conventional wisdom is to avoid relying on AI threat intelligence that uses machine learning to detect attacks because of concern over false positives. That makes sense in some environments, but not in others. Older detection techniques are more likely to miss the latest attacks, which may not follow the patterns those techniques typically look for. Machine learning can help security teams find the latest attacks, but with potentially higher false positive rates. If missing attacks is a greater concern than the resources needed to investigate additional false positives, then more reliance on automation utilizing machine learning may make sense to protect those assets.

Many organizations will find it best to use threat intelligence without machine learning for some purposes, and to get machine learning-generated insights for other purposes. For example, threat hunters might use machine learning to get suggestions of things to investigate that would have been impossible for them to find in large threat intelligence data sets. Also, don't forget about threat intelligence services -- their reports can provide invaluable insights for threat hunters on the newest threats. These insights often include things that can't easily be automated into something machine learning can process.

More here:
AI threat intelligence is the future, and the future is now - TechTarget

Will Shopifys New Cryptocurrency Partnership Widen Its Moat? – Motley Fool

Posted on May 27, 2020 by admin

Shopify's (NYSE:SHOP) platform allows its merchants to accept payments in bitcoin, Litecoin, Ethereum, andover 300 other types of cryptocurrencies. It recently expanded that reach by partnering withcryptocurrency payments processor CoinPayments, which helps merchants process 1,800 types of cryptocurrencies.

Shopify claims the partnership will "make cryptocurrency transactions easier and more accessible while reducing transaction fees." CoinPayments CEO Jason Butcher declared the partnership would deliver a "seamless process for anyone looking to do business using cryptocurrencies."

CoinPayments has processed over $5 billion in cryptocurrency payments since its founding in 2013 and provides clients with various APIs, shopping cart plugins, and digital wallets. Shopify's cryptocurrency expansion isn't surprising, but will this new partnership widen its moat?

Image source: Getty Images.

Cryptocurrencies like bitcoin have gained a lot of attention among speculators in recent years. However, the broad price swings -- which have ranged from about $500 to $19,000 for bitcoin over the past four years -- made them tough to accept as mainstream payments.

Last year, a survey by the Foundation for Interwallet Operability (FIO) found that only 30% of cryptocurrency owners actually used the coins forpayments. The vast majority held the coins as investments. A more recent survey by the Economist Intelligence Unit and digital payments platform Crypto.com found just 34% ofcryptocurrency usersprimarily used digital currencies for online payments.

Crypto Radar recently claimed 6.2% ofAmericans owned bitcoin, and 7.3% planned to buy some in the future. Yet the overwhelming majority (64.8%) didn't own any bitcoin and had no plans to buy any coins in the future. Another 21.8% hadn't even heard of bitcoin.

Those percentages indicate cryptocurrency payments don't appeal to mainstream shoppersyet. Nonetheless, manymajor companies -- including Microsoft, AT&T, and Expedia -- already accept bitcoin payments, though it's unclear how many customers actually choose those options.

Shopify alsorecently joined the Facebook (NASDAQ:FB)-led Libra Association, which wants to serve underbanked markets with its Libra cryptocurrency. That decision was surprising, since Libra had already lost many of its top members after regulators opposed its development.

Image source: Getty Images.

However, Libra is being developed as a "stablecoin" which is pinned to fiat currencies instead of mining algorithms. That stability could make Libra a more viable payment option than bitcoin and other volatile cryptocurrencies, and tethering them to Facebook's Calibra digital wallet, Messenger, and WhatsApp could quickly expand its reach.

CoinPayments also processes payments in other top stablecoins like TrueUSD, USD Coin, and Gemini Dollar (GUSD). These currencies could be more appealing to merchants and shoppers, who can sleep easier knowing the value of their payments won't plummet or skyrocket overnight.

Shopify's partnerships with the Libra Association and CoinPayments could pivot its merchants from bitcoin toward less volatile cryptocurrencies. That process might be glacial and won't move the needle anytime soon, but it could enhance its broader platform -- which already serves over a million businesses in more than 175 countries.

Shopify's cryptocurrency partnerships should also widen its moatagainst Adobe's (NASDAQ:ADBE) Magento, which recently partnered with cryptocurrency payments platform Utrust to provide its crypto transactions to over 250,000 merchants. Magento is arguably Shopify's toughest competitor since it's tightly integrated into Adobe's other cloud-based analytics, marketing, and advertising tools.

The cryptocurrency market remains a niche one, butit could still grow from $1.03 billion to $1.4 billion between 2019 and 2024, according to Markets and Markets. Shopify probably doesn't expect cryptocurrency payments to overtake traditional payment methods anytime soon, but it also doesn't want to be left behind a crucial tech curve. If top cryptocurrencies like bitcoin stabilize and stablecoins gain ground, Shopify's recent partnerships could widen its moat against Adobe and other rivals while planting the seeds for future growth.

See more here:
Will Shopifys New Cryptocurrency Partnership Widen Its Moat? - Motley Fool

PCAOB eyes audits involving cryptocurrency – Accounting Today

Posted on May 27, 2020 by admin

The Public Company Accounting Oversight Board released a document Tuesday with information for auditors and audit committees about audits involving cryptoassets, such as Bitcoin and other digital currencies.

The Spotlight document, Audits Involving Cryptoassets Information for Auditors and Audit Committees, is part of the PCAOBs Strategic Plan to monitor the development and implementation of emerging technologies to analyze their implications for the quality of audit services.

The PCAOBs staff has noticed that cryptocurrencies such as Bitcoin have recently started to be recorded and disclosed in the financial statements of companies, broker-dealers and other issuers. When doing inspections of auditors of some smaller issuers, the PCAOBs staff has seen situations where transactions involving cryptoassets were material to the financial statements.

The document discusses some of the issues that auditors should consider when handling their responsibilities under PCAOB standards for auditing issuers who are transacting in or who hold cryptoassets.

Some of those issues may involve fraud: In identifying fraud risks, the discussion among the key engagement team members about the potential for material misstatement due to fraud may include, for example: the risk of management override of controls over the private keys, which may result in misuse or misappropriation of holdings of cryptoassets by those who control the keys; the susceptibility of the financial statements to material misstatement through transactions with related parties; the related parties identities may be difficult to ascertain because of the pseudonymous nature of transactions involving cryptoassets.

The document also includes some questions that audit committee members could have for auditors when transactions involving cryptocurrency or crypto holdings are material to the issuers financial statements.

Among the questions are:

The information in the document may be of special interest to auditors and audit committee members of issuers that are starting to transact in, or already hold, cryptocurrencies.

Go here to see the original:
PCAOB eyes audits involving cryptocurrency - Accounting Today

Meet Theta Fuel, the cryptocurrency that catches world’s attention – Nairametrics

Posted on May 27, 2020 by admin

OmiseGO, an ethereum token that energizes smart contract platforms and trades under a sticker known as OMG, surged after popular American based cryptocurrency exchange, Coinbase, revealed that it would list the token on its exchange.

OmiseGO, which is not even in the top 30 most valuable cryptos in the world, has gained over 150% since April 1, according to data obtained from Coinmarketcap.

It was trading at $0.5 on April 1st and is presently trading at %1.26, with a market capitalization of about $276 million.

READ ALSO: Elumelu says Covid-19 Presents Opportunity to Reset Africa

What you need to know: OMG coin was designed as a white-label eWallet. It was designed on the Ethereum blockchain by a Thailand based financial services company called Omise. Its full name is OmiseGo.

OmiseGo helps in easing the transfer of coins from one blockchain to another without using a crypto exchange.

Meanwhile, the broader bitcoin market is closely watching for Bitcoin to break the $10,000 price level, after Bitcoin went through a supply squeeze a few weeks ago. Yet, Bitcoins price has remained around the $9200+ mark in recent days.

However, Teju Adeyinka a product manager at Nigerias fast-growing crypto exchange, Buycoins, explained to Nairametrics why cryptos such as Bitcoin would continue to be a leading force in future. She said:

Bitcoin is the next important thing because it ushers in a new level of financial inclusion for everyone. It is a financial system that is truly democratized and in the interest of the people. It enables people to have total control over their money and decide what it does or where it goes.

READ MORE: Blue-chip stocks take Nigerian bourse to 5 days winning streak, Investors cash in N232 billion

It also opens up borderless trading and enables people who have been previously shut out economically to partake in financial opportunities beyond their geographical boundaries.

For instance, with our new product, Sendcash, people are able to easily receive payments to Nigeria from anywhere in the world.

Read the original:
Meet Theta Fuel, the cryptocurrency that catches world's attention - Nairametrics

Cryptocurrency Market to Reach USD 1,758.0 Million by 2027; Modifications in Virtual Currency Methods to Spur Business Opportunities, states Fortune…

Posted on May 27, 2020 by admin

Pune, May 26, 2020 (GLOBE NEWSWIRE) -- The global cryptocurrency market size is predicted to reach USD 1,758.0 million by 2027, exhibiting a CAGR of 11.2% during the forecast period. The growing inclination of individuals in developed countries towards virtual currency exchange methods will have a tremendous impact on the market during the forecast period. The integration of blockchain technology in cryptocurrency for fast, secure and effective transactions will bolster healthy growth of the market in the forthcoming years, mentioned in a report, titled Cryptocurrency Market Size, Share and COVID-19 Impact Analysis, By Component (Hardware, Software), By Type (Bitcoin, Ether, Litecoin, Ripple, Ether Classic, Others), By End-use (Trading, E-commerce and Retail, Peer-to-Peer Payment, and Remittance), and Regional Forecast, 2020 2027 , the market size stood at USD 754.0 million in 2019.

Get Sample PDF Brochure: https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/cryptocurrency-market-100149

An Overview of the Impact of COVID-19 on this Market:

The emergence of COVID-19 has brought the world to a standstill. We understand that this health crisis has brought an unprecedented impact on businesses across industries. However, this too shall pass. Rising support from governments and several companies can help in the fight against this highly contagious disease. There are some industries that are struggling and some are thriving. Overall, almost every sector is anticipated to be impacted by the pandemic.

We are taking continuous efforts to help your business sustain and grow during COVID-19 pandemics. Based on our experience and expertise, we will offer you an impact analysis of coronavirus outbreak across industries to help you prepare for the future.

Click here to get the short-term and long-term impact of COVID-19 on this Market.

Please visit: https://www.fortunebusinessinsights.com/industry-reports/cryptocurrency-market-100149

Market Driver:

Rising Popularity of Digital Currency to Augment Growth

The rising trend of cryptocurrency has led to the acceptance of digital coins such as Bitcoins, Litecoins, Ethers, and more. The easy and flexible transactional method offered by cryptocurrency has facilitated the Central Bank Digital Currency (CBDC) activity provisions across the world. For instance, Bank of Thailand and Central Bank of Uruguay have applied for the toolkit to its CBDC evaluation process. The toolkit delivers a guide for the countries to make progress quickly and analyse CBDC as an exchange medium. Furthermore, the increasing investment in blockchain and cryptocurrency by major companies will enable speedy expansion of the market. For instance, in October 2018, Qtum Chain Foundation, an open-sourced blockchain application platform based in Singapore announced a partnership with Amazon Web Services (AWS) China to deploy blockchain systems on the AWS cloud. The partnership will allow help AWS users to use Amazon Machine Images (AMI) to develop and publish smart contracts easily and efficiently. Also, the introduction of unique digital currencies by eminent companies will influence the market positively in the foreseeable future. For instance, in June 2019, Facebook, Inc. announced the launch of a digital currency named Libra. Libra will enable customers to buy things or send money to others and cash out Libra online or at grocery shops.

Market Restraint:

Raging Coronavirus to Sway Market Potential

The outbreak of COVID-19 has negatively impacted the global economy. The regression in the stock market has directedly created concerns for the bitcoins. For instance, 12 March 2020, the price of Bitcoin fell below USD 4,000 after a sharp decline in the S&P Index in the U.S. The market crash has incited an increase in investment capital by blockchain companies to compensate for the losses. Giant blockchain analytics, Elliptic, Chainalysis, and CipherTrace declared that they have cut-price and reduced staffs or intend to do so in the immediate future to lessen the economic effects of the coronavirus pandemic. For instance, CipherTrace has decreased the jobs of the advertising and marketing departments. Whereas Elliptic has eliminated 30%of the workers in the U.S. and the U.K and Chainalysis has planned to reduce employees' wages by 10% to mitigate the risks.

Speak to Analyst: https://www.fortunebusinessinsights.com/enquiry/speak-to-analyst/cryptocurrency-market-100149

Regional Analysis:

Existential Players to Promote Growth in North America

The market in North America stood at USD 250.9 million in 2019 and is predicted to proliferate in the forthcoming years. The growth in the region is attributed to the rising popularity of bitcoins in the US. The presence of major eminent players will foster growth in the region during the forecast period. Asia Pacific is expected to witness significant growth during the forecast period owing to the technological developments and acceptance of virtual currency in Japan. The growing collaborations among key players will significantly boost the cryptocurrency market growth in Asia Pacific. For instance, in January 2020, Z Corporation, Inc. and TaoTao, Inc. announced a joint venture with the financial service agency to expand its presence by confirming regulatory compliance in the Japanese market.

Key Development:

January 2020: Binance, a cryptocurrency exchange company that provides a platform for trading various cryptocurrencies announced the acquisition of WazirX Bitcoin exchange based in Mumbai, India. With this acquisition, Binance will be able to expand its business portfolio in India.

List of the Key Companies Operating in the Cryptocurrency Market are:

Quick Buy Cryptocurrency Market Research Report: https://www.fortunebusinessinsights.com/checkout-page/100149

Detailed Table of Content

TOC Continued..!!!

Get your Customized Research Report: https://www.fortunebusinessinsights.com/enquiry/customization/cryptocurrency-market-100149

Have a Look at Related Research Insights:

Quantum Cryptography Market Size, Share and Global Trend By Component (Hardware & Services), By Services (Consulting, Support and Maintenance, Integration and Deployment), By Applications (Application Security, Network Security, Database Encryption), By Industry Verticals (Banking, Finance Services, Insurance, Consumer Good and Retail, Government & Defence, Healthcare and Life sciences, Telecom and IT) and Geography Forecast till 2025

Blockchain in Retail Market Size, Share & Industry Analysis, By Component (Platform, Services), By Provider (Application and solution provider, Middleware provider Infrastructure, Protocol Provider), By Organization Size (Large Enterprises, Small & Medium Enterprises) Others and Regional Forecast, 2019-2026

Blockchain in BFSI Market Size, Share And Global Trend By Type (Private Blockchain, Public Blockchain, Consortium Blockchain), By Application (Smart Contracts, Security, Trade Finance, Digital Currency, Record Keeping, GRC Management, Identity Management and Fraud Detection), And Geography Forecast Till 2026

Blockchain Technology Market Size, Share and Industry Analysis by Product Type (Vertical Solutions, Blockchain-as-a-Service), Deployment, Industry Vertical (BFSI, Energy & Utilities, Government, Healthcare and Life Sciences, Manufacturing, Telecom, Media & Ent., Retail & Consumer Goods, Travel and Transportation), and Regional Forecast 2018-2025

About Us:

Fortune Business Insightsoffers expert corporate analysis and accurate data, helping organizations of all sizes make timely decisions. We tailor innovative solutions for our clients, assisting them address challenges distinct to their businesses. Our goal is to empower our clients with holistic market intelligence, giving a granular overview of the market they are operating in.

Our reports contain a unique mix of tangible insights and qualitative analysis to help companies achieve sustainable growth. Our team of experienced analysts and consultants use industry-leading research tools and techniques to compile comprehensive market studies, interspersed with relevant data.

At Fortune Business Insights, we aim at highlighting the most lucrative growth opportunities for our clients. We therefore offer recommendations, making it easier for them to navigate through technological and market-related changes. Our consulting services are designed to help organizations identify hidden opportunities and understand prevailing competitive challenges.

Contact Us:Fortune Business Insights Pvt. Ltd.308, Supreme Headquarters,Survey No. 36, Baner,Pune-Bangalore Highway,Pune- 411045, Maharashtra,India.Phone:US: +1-424-253-0390UK: +44-2071-939123APAC: +91-744-740-1245Email:sales@fortunebusinessinsights.comFortune Business InsightsLinkedIn|Twitter|Blogs

Read Press Release https://www.fortunebusinessinsights.com/press-release/cryptocurrency-market-9952

More here:
Cryptocurrency Market to Reach USD 1,758.0 Million by 2027; Modifications in Virtual Currency Methods to Spur Business Opportunities, states Fortune...

Everything to Know about the Emergence of Prepaid Cryptocurrency Debit Cards: – PaymentsJournal

Posted on May 27, 2020 by admin

Dont miss another episode of Truth In Data! Click on the red bell in the lower-left corner of your screen to receive notifications as soon as the episode publishes.

Data for todays episode is provided by Mercator Advisory Groups report Cryptocurrency: A New Growth Segment for Prepaid Debit Cards?

Everything to Know about the Emergence of Prepaid Cryptocurrency Debit Cards:

Cryptocurrency prepaid debit cards are the method of choice for spending cryptocurrency off the blockchain.

A major cryptocurrency prepaid debit card serving the U.S. market closed in 2018. Only a year later, in addition to BitPay, there are two new entrants. Should you be a part of the new Wild West of cryptocurrency prepaid debit cards?

Summary

Title

Everything to Know about the Emergence of Prepaid Cryptocurrency Debit Cards:

Description

Continued here:
Everything to Know about the Emergence of Prepaid Cryptocurrency Debit Cards: - PaymentsJournal

Bitcoin: QE Unlimited And The Next Wave Higher – Seeking Alpha

Posted on May 27, 2020 by admin

Image Source - Bitcoin or Gold, which would you prefer?

With trillions upon trillions of coronavirus stimulus pilling up, the Feds balance sheet, along with the U.S.s monetary base, is exploding like never in history.

Source: The Fed - The monetary base could reach $10-$12 Trillion as the Fed goes through with its unprecedented lending program.

Source: The Fed - Numbers are in trillions and illustrate that the Fed's balance sheet has nearly doubled just since the beginning of this year.

To complicate matters further, U.S. Federal spending budget is about $3.4 trillion in the red, and national debt to GDP ratio is approaching 120%. Furthermore, it is not just the U.S., as fiat currency debasement has essentially become the norm all over the globe. Due to the continuous debasement of global fiat currencies, Bitcoin (BTC-USD) and other inflation-resistant digital assets should continue to experience increased demand and further price appreciation.

As the Fed perpetually increases the supply of dollars around the world, assets such as Bitcoin and other promising digital currencies should go a lot higher.

Image Source

This is effectively the same phenomenon that gold and GSMs have benefited from. Ultimately, the trillions of dollars created by the Fed will filter through to the real economy, which will very likely lead to inflation, loss of purchasing power, and possibly even a loss of confidence at some point. QE unlimited is not going unnoticed, and market participants are beginning to understand that there is no returning to the old normal. There is only the new normal now, and it is filled with incredibly easy credit, rock bottom interest rates, and essentially limitless amounts of capital provided by the fed.

Even Goldman Sachs (NYSE:GS.PK) is hosting a conference on inflation, crisis, and Bitcoin, which is a positive development for the crypto industry in itself. This is telling that major organizations and the smartest guys in the room are starting to recognize potential in the digital asset industry due to massive fiat devaluation.

Additionally, the current fiat financial system is filled with faults, redundant charges, and inadequacies. Therefore, banks, large institutions, as well as retail consumers/investors could start to utilize digital assets on a mass scale within the next several years.

I want to clarify what a digital asset means to me. Whether it is Bitcoin, Ethereum, Litecoin, etc., a digital asset is a unit of value. Moreover, this unit of exchange represents your share on a given blockchain network. You see, every cryptocurrency/digital asset has its own protocol and its own blockchain. Additionally, each blockchain project/network has a specific role to play in the ever-evolving digital payment and services industry. Every project essentially consists of a form of a medium of exchange, its own blockchain system, and a very extensive infrastructure to facilitate various business activities. Therefore, a digital asset, coupled with its blockchain, in its essence, is very much like a company, but instead of shares in a startup, market participants own coins in a "project".

Image Source

This market segment has a great deal of potential going forward and could potentially integrate and assimilate well with the mainstream financial industry. Even if assimilation is limited, digital assets could represent a growing share of the medium of exchange market and other niche areas in coming years. Digital assets offer market participants advantages such as investing, trading, conducting transitions, implementing various services, and much more. With that said, let us look at some top digital assets to consider.

Numerous ambitious projects with real-world applications already exist, and many of the best-established enterprises continue to dominate crucial areas of the digital asset market.

Some of my favorite networks include:

Bitcoin Bitcoin is typically the first option for many people, as it is extremely secure, and is the original, best known digital asset in the world. It is primarily used for storing value, but Bitcoin can also be used as a medium of exchange.

Litecoin (LTC-USD) They call it the silver to Bitcoin golds, yet Litecoin is simply just a much more efficient digital currency. When it comes to mass transactions, Litecoin is cheaper, faster, can handle scale much better than Bitcoin.

Zcash (ZEC-USD) Litecoin is not alone in the efficient medium of exchange market. In fact, Litecoin has several worthy adversaries in this space. A factor to consider is that this market is expanding, could grow dramatically as fiat currencies continue to debase, and could represent a significant share of the global store of value and worldwide medium of exchange markets within the next 3-5 years. Zcash is a great transactional coin, which is fast, efficient, and offers an added layer of anonymity to your transactions.

Dash (DASH-USD) - Another very efficient and promising transactional coin. Dash is very safe, efficient, cheap, and has an added layer of cryptography to provide more anonymity to users of its blockchain.

Monero (XMR-USD) - If you want untraceable, there is only one coin that can handle this task. Monero is a truly anonymous coin. Whereas Zcash and Dash transactions are extremely difficult to monitor, Moneros are essentially impossible to trace.

We just went over my favorite transactional coins that have enormous market share potential going forward, in my view. However, it is not all about transactional coins. Functional coins like Ethereum (ETH-USD), Tron (TRX-USDT), Tezos (XTZ-USD), EOS (EOS-USD), Cardano (ADA-USD), Stellar (XLM-USD), Neo (NEO-USD), Ethereum Classic (ETC-USD) and others represent very promising long-term opportunities in the cryptocurrency market.

BTC 4-Hour Chart

Image Source

We see that Bitcoin has staged a very powerful rally since the volatility induced panic bottom of mid-March. In fact, BTC gained as much as 165% from the $3,800 March low to the high around $10,000 in early-May. However, Bitcoin has been in a trading range of around $8,000 to roughly $10,000 for nearly a month now. The price is around $8,700 at the time of writing this article, but BTC appears to be consolidating here and could be setting up for its next leg higher above $10K. Bitcoin has attempted to penetrate this level on several occasions, but the favorable fundamental backdrop should enable Bitcoin to break above the $10,000 soon. For downside protection, I am watching the $8,500 level, and then $8,000, if for whatever reason these support levels begin to breakdown, Bitcoin could fall back as low as $6,500 support next (worst case scenario in my view).

The bottom line is that tokens, whether it is Bitcoin, Litecoin, Tron, Tezos, etc., are not just coins. These are unique enterprises built upon extremely capable blockchains, coupled with their own digital coins, and deep infrastructure projects. Right now, the industry appears to be notably underappreciated, and its future potential may be drastically underestimated by many.

Moreover, consider the trillions of dollars floating around looking for a place to park to get positive yield in this financial environment. Due to inflation resistance and future potential, I believe a prime place for future investment will likely be the digital asset segment. There is a lot of uncertainty concerning equities going forward, gold/GSMs are doing great, but in the intermediate term, there are not that many bright spots in the market. Furthermore, the Wuhan virus will likely continue to weigh on international confidence and consumption for many months. While it may take some time for inflation to filter through to the real economy, once it does, prices for various assets, including Bitcoin, should go substantially higher.

Digital Asset Price Check

If we look at market caps for some of the most lucrative digital assets, the figures may be undervalued relative to future functionality, capability, and market share potential.

After reshuffling our cryptocurrency basket holdings, these are all the coins we own interest in right now. I do not look at these as simple coins or tokens, but rather as shares in a company. After all, the more tokens you own, the more market share you have on a given blockchain network. As the worth of the network increases, so do the shares/coins you own in that network.

Source: Statista.com - Blockchain wallet growth

Thanks to the Fed and other central banks, the world is awash in money now, and there are not that many attractive options for investment out there. The intermediate direction of stocks is questionable, bond rates are incredibly low and likely headed even lower, the growth picture is very murky and anemic right now. Nevertheless, trillions of dollars are being printed, and they are going to have to land somewhere. It is very plausible that investments could continue to enter the gold/GSM and the Bitcoin/digital asset segment. There is enormous growth potential in the cryptocurrency market, and market caps of many projects/enterprises are relatively cheap right now. Thus, future capital inflows could send Bitcoin and other digital assets substantially higher over the next year, as well in the intermediate and long term.

Want the whole picture? If you would like full articles that include technical analysis, trade triggers, portfolio strategies, options insight, and much more, consider joining Albright Investment Group!

Disclosure: I am/we are long ASSETS MENTIONED. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: This article expresses solely my opinions, is produced for informational purposes only and is not a recommendation to buy or sell any securities. Please always conduct your own research before making any investment decisions.

Disclosure: Our digital asset basket is up by 30% QTD, and up by roughly 80% YTD.

See the original post here:
Bitcoin: QE Unlimited And The Next Wave Higher - Seeking Alpha