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Could Blockchain Survive if Unchained from Digital Currency?

Bitcoin, Ethereum, Ripple, and even Dogecoin would not exist without blockchain technology. But can blockchain technology exist without cryptocurrencies? Cryptocurrency has been having a bad year; most of the currencies hit a high against the USD in November of last year and have slid to a fraction of that high point since. A research director at CoinDesk named Nolan Bauerle says 90% of cryptocurrencies today will not survive a crash in the markets. He does, however, believe that the few survivors will thrive. But there are naysayers like Berkshire Hathaway’s Charlie Munger, who said he “admires the Chinese” for banning cryptocurrencies. Munger has also been quoted as saying that digital currency “is going to zero” and has described it as a “venereal disease.”

Recent problems with bitcoin (BTC.X) and smaller cryptos, including price-driven margin calls, central bank interference, the SEC and other regulators exploring ways to tighten controls, a failed bitcoin-based bond offering in Ecuador, and current investor fear put the future in question. Hypothetically, what if bitcoin and all non-central bank-sponsored digital currency disappeared? Would blockchain technology still have blossoming applications in other areas?

 

About Blockchain

The technology now serves a very wide range of applications. At its core, blockchain is a distributed digital ledger that forever stores data of any kind. A blockchain can record unique information about cryptocurrency transactions, non-fungible token (NFT) ownership, DeFi smart contracts, and far more.

While any conventional database can store this sort of information, blockchain is unique in that it’s completely decentralized. Rather than being maintained in one location by an administrator, many identical copies of a blockchain database are held across a network (nodes).

The majority of nodes must verify and then confirm back the legitimacy of new data before a new block can be added to the ledger. For a cryptocurrency, this protects against fraud and confirms that a coin has not been spent more than once by the holder. Transactions are kept secure using cryptography at the node level.

Blockchain Use Beyond Cryptocurrency

The theory that created blockchain is rooted in the theoretical
paper that launched bitcoin. Since then, the security and verifiability of ownership provided have caused its applications to spread from everything from agriculture to fine wines. The most widespread non-crypto adoption is in banking, payments or asset transfer, contracts, supply chain oversight, voting, and NFT art. These are the larger current uses explained.

Banking, blockchain is being used to process
transactions in fiat currency, like US dollars and euros. This is often faster than sending money through a bank or other financial institution as the transactions can be speedily processed even outside of normal business hours.

Asset Transfers, blockchain can also be used to record and transfer the ownership of different assets. This is popular with digital assets like NFTs, a representation of ownership of digital art, videos, in-game items or anything else deemed unique.

The technology is also used to process the ownership, like the deed to real estate, vehicles, and other “titled” assets. In a transaction, both parties would first use the blockchain to verify that one owns the property and the other has the money to buy; then, they could move forward and complete and record the sale on the blockchain.

Using this process, there is the ability to transfer titles without manually submitting paperwork to update any government records; it would be simultaneously updated in the blockchain.

Contracts (Smart Contracts), another innovation, is self-executing contracts commonly called “smart
contracts.” These digital contracts are executed automatically once conditions are met. For instance, a payment might be released instantly once the buyer and seller have met all specified parameters for a deal.

Supply Chain Monitoring, supply chains involve massive amounts of logistics and information, especially when it involves several stops around the globe, as a computer chip does. With traditional data storage methods, it can be hard to trace the source of problems and slowdowns. Storing this information on the blockchain would make it easier to review. There are products in use today that monitor food stages from harvest to just before consumption.

Voting, as blockchain is a superior verification system, it is being considered to be implemented to prevent fraud in voting. In theory, blockchain voting would allow people to submit votes that couldn’t be tampered with. 

Blockchain Companies With Low Cryptocurrency Baggage

One company early-stage company that exemplifies what it is to have a primary focus on non-currency products but instead embrace future efforts like Web 3.0, Staking, gaming, NFTs, DeFi, and metaverse applications is Tokens.com ($SMURF). Read the most recent analyst
report on SMURF from the Noble Capital Markets analyst that covers this industry.

Another is TAAL Distributed Information Technologies ($TAALF). TAAL, blockchain services, provides professional-grade, highly scalable blockchain infrastructure and transactional platforms that support businesses building solutions and applications and developing, operating, and managing distributed computing systems for enterprise users. Read the most recent analyst
report on TAAL from the Noble Capital Markets analyst that covers this industry.

 

Take-Away

The technology that gave birth to cryptocurrency has taken on a life of its own, it provides efficiency in asset transfer, added security against fraud, ownership verification, round-the-clock and round-the-globe transactions, proof of stake, and proof-of-work, like no other system or technology. It’s likely to expand as it finds its way into helping our lives improve and will certainly be a staple in business dealings in the near future. And it can do this with or without private cryptocurrencies or stablecoins.

Paul Hoffman

Managing Editor, Channelchek

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Voyager Digital Provides Update on Asset and Risk Management

Research, News, and Market Data on Voyager Digital

NEW YORK, June 14, 2022 /CNW/ – Voyager Digital Ltd. (“Voyager” or the “Company”) (TSX: VOYG) (OTCQX: VYGVF) (FRA: UCD2), one of the fastest-growing consumer cryptocurrency platforms in the United States, and one of the first public companies in the crypto industry, today provides an asset and risk management update in light of changing market conditions. As a public company, Voyager operates with a consistently high level of transparency, providing regular quarterly financial statements detailing the company’s financial position and financial statement disclosure surrounding risk management practices and counterparty exposure.

Voyager differentiates itself through a straightforward, low-risk approach to lending and asset management by working with a select group of reputable counterparties, which are all vetted through extensive due diligence by its Risk Committee. The company does not participate in DeFi lending activities, algorithmic stablecoin staking and lending, or derivative assets, such as stETH. One of Voyager’s important objectives is to make crypto as simple and safe as possible for consumer use. With that mission in mind, safeguarding customer assets is a top priority.

Although Voyager announced a prior partnership with Celsius in 2019, due to the company’s ongoing due diligence and risk management process, Voyager currently has no customer assets at Celsius.

“Voyager holds a strong position in the crypto industry. Not only were we among the first to go public and provide full balance sheet transparency, our leadership also has deep financial expertise across the sector and has led companies through multiple market cycles,” said Steve Ehrlich, Chief Executive Officer and co-founder of Voyager. “The company is well capitalized and in a good position to weather this market cycle and protect customer assets. It is Voyager’s goal to continue to build secure products and services, as well as build trust and leadership in the cryptocurrency industry.”

About Voyager Digital Ltd.

Voyager Digital Ltd.’s (TSX: VOYG) (OTCQX: VYGVF) (FRA: UCD2) US subsidiary, Voyager Digital, LLC, is a fast-growing cryptocurrency platform in the United States founded in 2018 to bring choice, transparency, and cost-efficiency to the marketplace. Voyager offers a secure way to trade over 100 different crypto assets using its easy-to-use mobile application. Through its subsidiary Coinify ApS, Voyager provides crypto payment solutions for both consumers and merchants around the globe. To learn more about the company, please visit https://www.investvoyager.com.

The TSX has not approved or disapproved of the information
contained herein.

SOURCE Voyager Digital (Canada) Ltd.

For further information: Press Contacts, Voyager Digital, Ltd., Voyager Public Relations Team, pr@investvoyager.com

 

Voyager State Orders Update Voyager Continues to Operate the Voyager Earn Program in all States Except Kentucky

Research, News, and Market Data on Voyager Digital

June 09, 2022 04:05 PM EST

Voyager Digital Ltd. (TSX: VOYG) (OTCQX: VYGVF) (FRA:UCD2) (“Voyager” or the “Company”), through its operating subsidiaries, is at the forefront of innovation in the rapidly evolving crypto industry, and is committed to providing the best experience for its customers.

This is an update to announcements Voyager made on March 30, 2022 and April 5, 2022 regarding certain orders the Company received from the state securities divisions of several states. These orders concern only one benefit of customer accounts permitting customers to earn rewards on their balances of certain crypto assets (“Voyager Earn Program”). Since these announcements, Voyager has received additional orders from California and South Carolina with similar concerns about the Voyager Earn Program. All but one state, Kentucky, continue to permit customers to participate in the Voyager Earn Program. Voyager continues to engage in dialogue with several states in order to pursue an acceptable regulatory solution.

“It is encouraging that all states, other than Kentucky, have allowed Voyager to continue to operate the Voyager Earn Program. Based on the continued operation of the Voyager Earn Program and similar programs across the industry, I am hopeful that an acceptable path forward can be agreed upon to ensure that our customers can continue to be rewarded for their loyalty to Voyager in these inflationary times and to keep the US crypto asset industry at the forefront of crypto adoption and innovation. Voyager’s ethos has been, and will continue to be, about giving our customers the most accessible and rewarding experience possible,” said Stephen Ehrlich, CEO and co-founder of Voyager.

About
Voyager Digital Ltd.
Publicly traded, Voyager Digital Ltd.’s (TSX: VOYG) (OTCQX: VYGVF) (FRA: UCD2) US subsidiary, Voyager Digital, LLC, is a fast-growing cryptocurrency platform in the United States founded in 2018 to bring choice, transparency, and cost efficiency to the marketplace. Voyager offers a secure way to trade over 100 different crypto assets using its easy-to-use mobile application. Through its subsidiary Coinify ApS, Voyager provides crypto payment solutions for both consumers and merchants around the globe. To learn more about the company, please visit https://www.investvoyager.com. 

Forward
Looking Statements
Certain information in this press release, including, but not limited to, statements regarding the Company’s interpretation of the orders received, the intent, terms and effectiveness of the orders, the expectation of clarification of such orders from the applicable states, the outcome of the discussions with the regulators, the timing for the imposition of restrictions and the terms of such restrictions, the impact of the orders on the other products and services offered by the Company, the success of the Company’s business strategy, future changes in laws and regulations or the interpretation thereof, the Company’s success and legal strategy in response to stat orders, future legislative change, the status and operation of the Voyager Earn Program, future growth and performance of the business, momentum in the businesses, future adoption of digital assets, and the Company’s anticipated results may constitute forward looking information (collectively, forward-looking statements), which can be identified by the use of terms such as “may,” “will,” “should,” “expect,” “anticipate,” “project,” “estimate,” “intend,” “continue” or “believe” (or the negatives) or other similar variations. Forward-looking statements involve known and unknown risks, uncertainties and other factors that may cause Voyager’s actual results, performance, or achievements to be materially different from any of its future results, performance or achievements expressed or implied by forward- looking statements. Moreover, Voyager operates in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for Company management to predict all risks, the interpretation or application of existing laws by regulators, nor can Voyager assess the impact of all factors on Voyager business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements Voyager may make. In light of these risks, uncertainties, and assumptions, the future events and trends discussed in this press release may not occur and actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. Forward looking statements are subject to regulatory risks, regulatory actions and claims, the risk of changes of laws or the interpretation or application thereof, the risk that the global economy, industry, or the Company’s businesses and investments do not perform as anticipated, that revenue or expenses estimates may not be met or may be materially less or more than those anticipated, that trading momentum does not continue or the demand for trading solutions declines, customer acquisition does not increase as planned, product and international expansion do not occur as planned, risks of compliance with laws and regulations that currently apply or become applicable to the business or the interpretation or application of laws and regulations by regulatory authorities, and those other risks contained in the Company’s public filings, including in its Management Discussion and Analysis and its Annual Information Form (AIF). Factors that could cause actual results of the Company and its businesses to differ materially from those described in such forward-looking statements include, but are not limited to, the ability of the Company to continue offering Voyager Earn Program and to offer products and services consistent with past offerings and continue to offer new and innovative products and services, a decline in the digital asset market or general economic conditions; changes in laws or approaches to regulation or the interpretation or application thereof, regulatory investigations, enforcement actions or other regulatory action or sanction or proceedings, the failure or delay in the adoption of digital assets and the blockchain ecosystem by institutions; changes in the volatility of crypto currency, changes in demand for Bitcoin and Ethereum, changes in the status or classification of cryptocurrency assets, cybersecurity breaches, a delay or failure in developing infrastructure for the trading businesses or achieving mandates and gaining traction; failure to grow assets under management, an adverse development with respect to an issuer or party to the transaction or failure to obtain a required regulatory approval. In connection with the forward-looking statements contained in this press release, the Company has made assumptions regarding the terms and conditions of the orders, its ability to continue the dialogue with the regulators, its ability to seek clarification, its ability to continue with the Voyager Earn Program, the timing for the imposition of restrictions and the terms of such restrictions, the impact of the orders on the other products and services offered by the Company, its success in responding to any orders or other regulatory enquiries, actions or claims and the applicability, interpretation and application of existing laws and regulations. Forward-looking statements, past and present performance and trends are not guarantees of future performance; accordingly, you should not put undue reliance on forward-looking statements, current or past performance, or current or past trends. Information identifying assumptions, risks, and uncertainties relating to the Company are contained in its filings with the Canadian securities regulators available at www.sedar.com. The forward-looking statements in this press release are applicable only as of the date of this release or as of the date specified in the relevant forward-looking statement and the Company undertakes no obligation to update any forward-looking statement to reflect events or circumstances after that date or to reflect the occurrence of unanticipated events. The Company assumes no obligation to provide operational updates, except as required by law. If the Company does update one or more forward-looking statements, no inference should be drawn that it will make additional updates with respect to those or other forward-looking statements, unless required by law. Readers are cautioned that past performance is not indicative of future performance and current trends in the business and demand for digital assets or in the application or interpretation of laws and regulations may not continue and readers should not put undue reliance on past performance and current trends. All figures are in U.S. dollars unless otherwise noted.

The TSX has not approved or disapproved of the information contained herein.

Press Contacts

Voyager
Digital, Ltd.
Kevin Rodriguez Investor Relations
(212) 547-8807

krodriguez@investvoyager.com

Voyager Public Relations Team
pr@investvoyager.com

TAAL to Webcast Live at the OTCQX Best 50 Virtual Investors Conference June 16

Research, News, and Market Data on TAAL

TAAL invites individual and institutional
investor as well as advisors and analysts to attend the interactive
presentation at VirtualInvestorConferences.com

TORONTO, June 9, 2022 /CNW/ – TAAL Distributed Information Technologies Inc. (CSE:TAAL) (FWB:9SQ1) (OTC:TAALF) (“TAAL” or the “Company”), a vertically integrated blockchain infrastructure and service provider for enterprise, announces that CEO Richard Baker will present live at the OTCQX Best 50 Virtual Investors Conference on June 16, 2022 at 11am Eastern Time (details below).  Mr. Baker will also host 1×1 investor meetings through the event.

“TAAL is building the infrastructure needed to power the next generation of the internet,” said CEO, Richard Baker. “We believe in a future beyond block subsidy rewards where revenues are driven by transaction processing and we are on a path to become a major network provider for Web 3.0 and the digital economy; I look forward to sharing this and more with investors at the OTCQX Best 50 conference.”   

Recent Company Highlights

• Gross revenue from hashing operations was $8.7 million, a $7.8 million increase from $0.9 million compared to the first quarter of the prior year (“Q1 2021”). 
• Adjusted EBITDA loss of $0.9 million versus a $3.5 million loss in Q1 2021.
• TAAL processed over 232 million transactions within 9,595 blocks on the BSV network for the quarter, earning almost $0.3 million in additional rewards from transaction processing, representing 3% of total revenue.
• Future growth secured with deposits for plant and equipment of $34.7 million to expand hashing fleet and a clean energy data center in New Brunswick, Canada.
• As of March 31, 2022, TAAL had about 23,000 BSV, 600 BCH and 0.5 BTC in coin treasury.

TAAL Investor
Presentation Webcast

DATE: Thursday June 16, 2022

TIME: 11:00am EST
LINK: https://bit.ly/3MB962u

Available for 1×1 meetings: Friday June 17, 2022.

This will be a live, interactive online event where investors are invited to ask the Company questions in real-time. If attendees are not able to join the event live on the day of the conference, an archived webcast will also be made available after the event.

It is recommended that investors pre-register and run the online system check to expedite participation and receive event updates.

Learn more about the event at www.virtualinvestorconferences.com.

About TAAL Distributed
Information Technologies Inc.

TAAL Distributed Information Technologies Inc. delivers value-added blockchain services, providing professional-grade, highly scalable blockchain infrastructure and transactional platforms to support businesses building solutions and applications upon the BitcoinSV platform, and developing, operating, and managing distributed computing systems for enterprise users.

Visit TAAL online at www.taal.com/investors 

About Virtual Investor
Conferences^®

Virtual Investor Conferences (VIC) is the leading proprietary investor conference series that provides an interactive forum for publicly traded companies to seamlessly present directly to investors.

Providing a real-time investor engagement solution, VIC is specifically designed to offer companies more efficient investor access.  Replicating the components of an on-site investor conference, VIC offers companies enhanced capabilities to connect with investors, schedule targeted one-on-one meetings and enhance their presentations with dynamic video content. Accelerating the next level of investor engagement, Virtual Investor Conferences delivers leading investor communications to a global network of retail and institutional investors.

SOURCE Taal Distributed Information Technologies Inc.

For further information: Media and Investor Contact: TAAL, Richard Baker, Chief Executive Officer, Office: (437) 826-8889, Richard.Baker@taal.com; Sophic Capital, Sean Peasgood, President & Chief Executive Officer, Office: (437) 826-8889, Sean@SophicCapital.com

Image Credit: Lauren Hinkel (MIT)

Machine Hallucinating to Better Translate Languages

Lauren Hinkel | MIT-IBM Watson AI Lab

As babies, we babble and imitate our way of learning languages. We don’t start off reading raw text, which requires fundamental knowledge and understanding about the world, as well as the advanced ability to interpret and infer descriptions and relationships. Rather, humans begin our language journey slowly, by pointing and interacting with our environment, basing our words and perceiving their meaning through the context of the physical and social world. Eventually, we can craft full sentences to communicate complex ideas.

Similarly, when humans begin learning and translating into another language, the incorporation of other sensory information, like multimedia, paired with the new and unfamiliar words, like flashcards with images, improves language acquisition and retention. Then, with enough practice, humans can accurately translate new, unseen sentences in context without the accompanying media; however, imagining a picture based on the original text helps.

This is the basis of a new machine learning model, called VALHALLA, by researchers from MIT, IBM, and the University of California at San Diego, in which a trained neural network sees a source sentence in one language, hallucinates an image of what it looks like, and then uses both to translate into a target language. The team found that their method demonstrates improved accuracy of machine translation over text-only translation. Further, it provided an additional boost for cases with long sentences, under-resourced languages, and instances where part of the source sentence is inaccessible to the machine translator.

As a core task within the AI field of natural language processing (NLP), machine translation is an “eminently practical technology that’s being used by millions of people every day,” says study co-author Yoon Kim, assistant professor in MIT’s Department of Electrical Engineering and Computer Science with affiliations in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the MIT-IBM Watson AI Lab. With recent, significant advances in deep learning, “there’s been an interesting development in how one might use non-text information — for example, images, audio, or other grounding information — to tackle practical tasks involving language” says Kim, because “when humans are performing language processing tasks, we’re doing so within a grounded, situated world.” The pairing of hallucinated images and text during inference, the team postulated, imitates that process, providing context for improved performance over current state-of-the-art techniques, which utilize text-only data.

This research will be presented at the IEEE / CVF Computer Vision and Pattern Recognition Conference this month. Kim’s co-authors are UC San Diego graduate student Yi Li and Professor Nuno Vasconcelos, along with research staff members Rameswar Panda, Chun-fu “Richard” Chen, Rogerio Feris, and IBM Director David Cox of IBM Research and the MIT-IBM Watson AI Lab.

 

Learning to Hallucinate
from Images

When we learn new languages and to translate, we’re often provided with examples and practice before venturing out on our own. The same is true for machine-translation systems; however, if images are used during training, these AI methods also require visual aids for testing, limiting their applicability, says Panda.

“In real-world scenarios, you might not have an image with respect to the source sentence. So, our motivation was basically: Instead of using an external image during inference as input, can we use visual hallucination — the ability to imagine visual scenes — to improve machine translation systems?” says Panda.

To do this, the team used an encoder-decoder architecture with two transformers, a type of neural network model that’s suited for sequence-dependent data, like language, that can pay attention key words and semantics of a sentence. One transformer generates a visual hallucination, and the other performs multimodal translation using outputs from the first transformer.

During training, there are two streams of translation: a source sentence and a ground-truth image that is paired with it, and the same source sentence that is visually hallucinated to make a text-image pair. First the ground-truth image and sentence are tokenized into representations that can be handled by transformers; for the case of the sentence, each word is a token. The source sentence is tokenized again, but this time passed through the visual hallucination transformer, outputting a hallucination, a discrete image representation of the sentence. The researchers incorporated an autoregression that compares the ground-truth and hallucinated representations for congruency — e.g., homonyms: a reference to an animal “bat” isn’t hallucinated as a baseball bat. The hallucination transformer then uses the difference between them to optimize its predictions and visual output, making sure the context is consistent.

The two sets of tokens are then simultaneously passed through the multimodal translation transformer, each containing the sentence representation and either the hallucinated or ground-truth image. The tokenized text translation outputs are compared with the goal of being similar to each other and to the target sentence in another language. Any differences are then relayed back to the translation transformer for further optimization.

For testing, the ground-truth image stream drops off, since images likely wouldn’t be available in everyday scenarios.

“To the best of our knowledge, we haven’t seen any work which actually uses a hallucination transformer jointly with a multimodal translation system to improve machine translation performance,” says Panda.

 

Visualizing the
Target Text

To test their method, the team put VALHALLA up against other state-of-the-art multimodal and text-only translation methods. They used public benchmark datasets containing ground-truth images with source sentences, and a dataset for translating text-only news articles. The researchers measured its performance over 13 tasks, ranging from translation on well-resourced languages (like English, German, and French), under-resourced languages (like English to Romanian) and non-English (like Spanish to French). The group also tested varying transformer model sizes, how accuracy changes with the sentence length, and translation under limited textual context, where portions of the text were hidden from the machine translators.

The team observed significant improvements over text-only translation methods, improving data efficiency, and that smaller models performed better than the larger base model. As sentences became longer, VALHALLA’s performance over other methods grew, which the researchers attributed to the addition of more ambiguous words. In cases where part of the sentence was masked, VALHALLA could recover and translate the original text, which the team found surprising.

Further unexpected findings arose: “Where there weren’t as many training [image and] text pairs, [like for under-resourced languages], improvements were more significant, which indicates that grounding in images helps in low-data regimes,” says Kim. “Another thing that was quite surprising to me was this improved performance, even on types of text that aren’t necessarily easily connectable to images. For example, maybe it’s not so surprising if this helps in translating visually salient sentences, like the ‘there is a red car in front of the house.’ [However], even in text-only [news article] domains, the approach was able to improve upon text-only systems.”

While VALHALLA performs well, the researchers note that it does have limitations, requiring pairs of sentences to be annotated with an image, which could make it more expensive to obtain. It also performs better in its ground domain and not the text-only news articles. Moreover, Kim and Panda note, a technique like VALHALLA is still a black box, with the assumption that hallucinated images are providing helpful information, and the team plans to investigate what and how the model is learning in order to validate their methods.

In the future, the team plans to explore other means of improving translation. “Here, we only focus on images, but there are other types of a multimodal information — for example, speech, video or touch, or other sensory modalities,” says Panda. “We believe such multimodal grounding can lead to even more efficient machine translation models, potentially benefiting translation across many low-resource languages spoken in the world.”

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Tuesday, June 07, 2022

TAAL Distributed Information Technologies (TAALF)
Results Below Expectations in Challenging Crypto Market

TAAL Distributed Information Technologies Inc. delivers value-added blockchain services, providing professional-grade, highly scalable blockchain infrastructure and transactional platforms to support businesses building solutions and applications upon the BitcoinSV platform, and developing, operating, and managing distributed computing systems for enterprise users.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

1Q22 Results. TAAL reported first quarter 2022 revenue of $8.7 million, up from $0.9 million in the year ago quarter but down from 4Q21 of $14.7 million. The sharp drop is due to the difficult operating conditions in the crypto market, including both declining values and reduced trade volumes. We had projected revenue of $12 million. TAAL reported a net loss of $12.7 million, or $0.33 per share, mostly driven by a sharp increase in non-cash share-based payments. We had estimated a net loss of $700,000, or $0.02 per share.

Operating Environment. Declining prices and lowered volumes as a result of overall economic conditions have pushed expected operating growth to the right. BSV is currently selling for about $58, down from $121 at the beginning of the year. Total crypto volume declined to $2.25 trillion in the quarter, down from $3.73 trillion in the fourth quarter….

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

Image Credit: Science.org

Computer Modeling Experts Explain the Benefits of Digital Twins

A digital twin is a virtual representation of a real system – a building, the power grid, a city, even a human being – that mimics the characteristics of the system. A digital twin is more than just a computer model, however. It receives data from sensors in the real system to constantly parallel the system’s state.

A digital twin helps people analyze and predict a system’s behavior under different conditions. The systems being twinned are typically very complex and require significant effort to model and track.

Digital twins are useful in a wide variety of domains, including supply chains, health care, buildings, bridges, self-driving cars and retail customer personas to improve efficiency and reliability. For example, a warehouse operator can optimize a warehouse’s performance by exploring the response of its digital twin to various material handling policies and equipment without incurring the cost of making actual changes.

Even a wildfire can be represented by a digital twin. Government agencies can predict the spread of the fire and its impact under different conditions such as wind velocity, humidity and proximity to habitats, and use this information to guide evacuations.

Why Digital Twins Matter

Digital twins are often used to model, understand and analyze complex systems where performance, reliability and security of the system are critical. In such systems it is paramount to test any changes, whether planned or unplanned.

In order to accurately test changes to the state of the actual system and the effects of any possible stimulus, the digital twin must accurately represent the physical system in its current state. This requires the digital twin to receive continuous updates from the physical system via fast and reliable communications channels.

Creating and maintaining digital twins often involves vast amounts of data to represent various features of the real system. Collecting and processing this data requires advanced communication and computing technologies. Communication support typically involves high-speed internet connections and wireless networks such as Wi-Fi and 5G. Computational support is typically in the form of servers, either in the cloud or closer to the physical system.

This article was republished with permission from The Conversation, a news site dedicated to sharing ideas from academic experts. It was written by and represents the research-based opinions of Amlan Ganguly, Associate Professor of Computer Engineering, Rochester Institute of Technology and Nalini Venkatasubramanian, Professor of Computer Science, University of California, Irvine.

We and other faculty members at Rochester Institute of Technology and the University of California, Irvine are starting the Center for Smart Spaces Research, a research center sponsored by the National Science Foundation. One of the primary ongoing projects within this center is building the basic technologies for creating digital twins in a variety of applications.

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