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Fujitsu and Hokkaido University Develop “Explainable AI” Technology Providing Users with Concrete Steps to Achieve Desired Outcomes



KAWASAKI, Japan, Feb 04, 2021 – (JCN Newswire) – Fujitsu Laboratories Ltd. and Hokkaido University today announced the development of a new technology based on the principle of “explainable AI” that automatically presents users with steps needed to achieve a desired outcome based on AI results about data, for example, from medical checkups.

“Explainable AI” represents an area of increasing interest in the field of artificial intelligence and machine learning. While AI technologies can automatically make decisions from data, “explainable AI” also provides individual reasons for these decisions – this helps avoid the so-called “black box” phenomenon, in which AI reaches conclusions through unclear and potentially problematic means.

While certain techniques can also provide hypothetical improvements one could take when an undesirable outcome occurs for individual items, these do not provide any concrete steps to improve.

For example, if an AI that makes judgments about the subject’s health status determines that a person is unhealthy, the new technology can be applied to first explain the reason for the outcome from health examination data like height, weight, and blood pressure. Then, the new technology can additionally offer the user targeted suggestions about the best way to become healthy, identifying the interaction among a large number of complicated medical checkups items from past data and showing specific steps to improvement that take into account feasibility and difficulty of implementation.

Ultimately, this new technology offers the potential to improve the transparency and reliability of decisions made by AI, allowing more people in the future to interact with technologies that utilize AI with a sense of trust and peace of mind. Further details will be presented at the AAAI-21, Thirty-Fifth AAAI Conference on Artificial Intelligence opening from Tuesday, February 2.

Developmental Background

Currently, deep learning technologies widely used in AI systems requiring advanced tasks such as face recognition and automatic driving automatically make various decisions based on a large amount of data using a kind of black box predictive model. In the future, however, ensuring the transparency and reliability of AI systems will become an important issue for AI to make important decisions and proposals for society. This need has led to increased interest and research into “explainable AI” technologies.

For example, in medical checkups, AI can successfully determine the level of risk of illness based on data like weight and muscle mass (Figure 1 (A)). In addition to the results of the judgment on the level of risk, attention has been increasingly focused on “explainable AI” that presents the attributes (Figure 1 (B)) that served as the basis for the judgment.

Because AI determines that health risks are high based on the attributes of the input data, it’s possible to change the values of these attributes to get the desired results of low health risks.


In order to achieve the desired results in AI automated decisions, it is necessary not only to present the attributes that need to be changed, but also to present the attributes that can be changed with as little effort as is practical.

In the case of medical checkups, if one wants to change the outcome of the AI’s decision from high risk status to low risk status, achieving it with less effort may seem to increase muscle mass (Figure 2 Change 1) – but it is unrealistic to increase one’s muscle mass alone without changing one’s weight, so actually increasing weight and muscle mass simultaneously is a more realistic solution (Figure 2 Change 2). In addition, there are many interactions between attributes such as weight and muscle mass, such as causal relationships in which weight increases with muscle growth, and the total effort required to make changes depends on the order in which the attributes are changed. Therefore, it is necessary to present the appropriate order in which the attributes are changed. In Figure 2, it is not obvious whether weight or muscle mass should be changed first in order to reach Change 2 from the current state, so it remains challenging to find an appropriate method of change taking into the account the possibility and order of changes from among a large number potential candidates.

About the Newly Developed Technology

Through joint research on machine learning and data mining, Fujitsu Laboratories and Arimura Laboratory at the Graduate School of Information Science and Technology, Hokkaido University have developed new AI technologies that can explain the reasons for AI decisions to users, leading to the discovery of useful, actionable knowledge.

AI technologies such as LIME (1) and SHAP (2), which have been developed as AI technologies to support decision-making of human users, are technologies that make the decision convincing by explaining why AI made such a decision. The jointly developed new technology is based on the concept of counterfactual explanation (3) and presents the action in attribute change and the order of execution as a procedure. While avoiding unrealistic changes through the analysis of past cases, the AI estimates the effects of attribute value changes on other attribute values, such as causality, and calculates the amount that the user actually has to change based on this, enabling the presentation of actions that will achieve optimal results in the proper order and with the least effort.

For example, if one has to add 1 kg of muscle mass and 7 kg to their body weight in order to reduce the risk in the input attribute and its order (Figure 1 (C)) that they change to obtain the desired result in a medical checkup, it’s possible to estimate the relationship by analyzing the interaction between the muscle mass and the body weight in advance. That means that if one adds 1 kg of muscle mass, the body weight will increase by 6 kg. In this case, out of the additional 7 kg required for weight change, the amount of change required after the muscle mass change is just 1 kg. In other words, the amount of change one actually has to make is to add 1 kg of muscle mass and 1 kg of weight, so one can get the desired result with less effort than the order changing their weight first.


Using the jointly developed counterfactual explanation AI technology, Fujitsu and Hokkaido University verified three types of data sets (4) that are used in the following use cases: diabetes, loan credit screening, and wine evaluation. By combining three key algorithms for machine learning – Logistic Regression (5), Random Forest (6), and Multi-Layer Perceptron (7) – with the newly developed techniques, we have verified that it becomes possible to identify the appropriate actions and sequence to change the prediction to a desired result with less effort than the effort of actions derived by existing technologies in all datasets and machine learning algorithm combinations. This proved especially effective for the loan credit screening use case, making it possible to change the prediction to the preferred result with less than half the effort.

Using this technology, when an undesirable result is expected in the automatic judgment by AI, the actions required to change the result to a more desirable one can be presented. This will allow for the application of AI to be expanded not only to judgment but also to support improvements in human behavior.

Future Plans

Going forward, Fujitsu Laboratories will continue to combine this technology with individual cause-and-effect discovery technologies (8) to enable more appropriate actions to be presented. Fujitsu will also use this technology to expand its action extraction technology (9) based on its proprietary “FUJITSU AI Technology Wide Learning”, with the aim of commercializing it in fiscal 2021.

Hokkaido University aims to establish AI technology to extract knowledge and information useful for human decision-making from various field data, not limited to the presentation of actions.

(1) LIME: An explainable AI technology. Explains in a simple, interpretable model.
(2) SHAP: An explainable AI technology. Explains by showing the contribution of the explanatory variable in the model.
(3) counterfactual explanation:
A method of indicating and explaining a state that is different from the truth, such as “If I had done this, the result would have been”.
(4) data sets:
The UC Irvine Machine Learning Repository is a world-famous repository that provides a number of data sets for comparative evaluation of machine learning, and FICO, a credit scoring company, published data for machine learning in three types of data sets: diabetes, loan credit screening, and wine evaluation.
(5) Logistic Regression:
A type of machine learning algorithm. A probability model that combines a logistic function with a hyperplane.
(6) Random Forest:
A type of machine learning algorithm. A prediction model that makes stable decisions by using a large number of decision tree classifiers.
(7) Multi-Layer Perceptron:
A type of machine learning algorithm. A model for training multiple neural networks.
(8) Individual cause-and-effect discovery technologies:
Fujitsu Develops Technology to Discover Characteristic Causal Relationships of Individual Data in Medicine, Marketing, and More (2020/12/17)
(9) “FUJITSU AI Technology Wide Learning” action extraction technology:
Fujitsu Bolsters its AI “Wide Learning” Technology with New Technique to Deliver Optimized Action Plans in Various Fields (2019/9/13)

About Fujitsu

Fujitsu is the leading Japanese information and communication technology (ICT) company offering a full range of technology products, solutions and services. Approximately 130,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.9 trillion yen (US$35 billion) for the fiscal year ended March 31, 2020. For more information, please see

About Fujitsu Laboratories

Founded in 1968 as a wholly owned subsidiary of Fujitsu Limited, Fujitsu Laboratories Ltd. is one of the premier research centers in the world. With a global network of laboratories in Japan, China, the United States and Europe, the organization conducts a wide range of basic and applied research in the areas of Next-generation Services, Computer Servers, Networks, Electronic Devices and Advanced Materials. For more information, please see:



SEC Outlines Regulatory Agenda, Exempt Securities Top the List Including Reg D, Accredited Investor Definition



The Securities and Exchange Commission (SEC) has outlined its regulatory agenda for the coming months and at the top of the list are exempt securities that include Reg D and perhaps other exemptions such as Reg CF and Reg A+. Of note, is that the accredited investor definition may receive a change as well.

In a statement published on Friday, SEC Chairman Gary Gensler stated:

“To meet our mission of protecting investors, maintaining fair, orderly, and efficient markets, and facilitating capital formation, the SEC has a lot of regulatory work ahead of us. I look forward to collaborating with my fellow commissioners and the dedicated staff to propose and finalize rules that will strengthen our markets, increase transparency, and safeguard investors.”

The list includes both short and long-term regulatory actions that administrative agencies plan to take.

Exempt offerings will garner additional scrutiny. According to the abstract:

“The Division [of Corporate Finance] is considering recommending that the Commission seek public comment on ways to further update the Commission’s rules related to exempt offerings to more effectively promote investor protection, including updating the financial thresholds in the accredited investor definition, ensuring appropriate access to and enhancing the information available regarding Regulation D offerings, and amendments related to the integration framework for registered and exempt offerings.”

Reg D is the top securities exemption when it comes to early-stage ventures raising growth capital. The top two iterations are Reg D 506b and Reg D 506c – with the latter allowing for general solicitation or online capital formation (crowdfunding). Any changes made could impact access to capital for promising young firms as the exemption in its current iteration has been highly effective.

The definition of an accredited investor has long been criticized by many Fintech industry insiders as too restrictive, denying opportunity to all investors. Yet there are some policymakers that believe the current wealth metrics need to be made more stringent, thus limiting access to investors even more. It is not immediately clear, what exactly, the commission has in store for any change.

Another regulatory area of note is the topic of “Gamification” something some digital investment platforms, such as Robinhood, have received criticism and encouraging trading – perhaps to the detriment of investors.

The abstract states:

“The Division [of Trading and Markets] is considering recommending that the Commission seek public comment on potential rules related to gamification, behavioral prompts, predictive analytics, and differential marketing.”

Special Purpose Acquisition Companies (SPACs), or blank check firms, have made the list as well as this sector of finance has boomed in the past year. As SPACs have increased, both regulators and elected officials have focused more of their attention on the method of taking a private firm public.

The SEC says:

“The Division [of Corporate Finance] is considering recommending that the Commission propose rule amendments related to special purpose acquisition companies.”

While any outcome is pure speculation at this time, the progress made during the last administration in areas such as access to capital and improvements to the exempt securities ecosystem could be at risk. Time will tell.

SEC Commissioner Hester Peirce, an individual well known for her support of innovation and smaller firms, Tweeted that the list may not be her “ideal list” but she is ready to work with her peers on the Commission.

There is plenty more on the SEC regulatory agenda.

The list is below or may be accessed here.

  • SEC Prerule Stage Exempt Offerings 3235-AM85
  • SEC Prerule Stage Third Party Service Providers 3235-AM95
  • SEC Prerule Stage Prohibition Against Fraud, Manipulation, and Deception in Connection With Security-Based Swaps 3235-AK77
  • SEC Prerule Stage Gamification 3235-AN00
  • SEC Proposed Rule Stage Listing Standards for Recovery of Erroneously Awarded Compensation 3235-AK99
  • SEC Proposed Rule Stage Corporate Board Diversity 3235-AL91
  • SEC Proposed Rule Stage Disclosure of Payments by Resource Extraction Issuers 3235-AM06
  • SEC Proposed Rule Stage Mandated Electronic Filings 3235-AM15
  • SEC Proposed Rule Stage Rule 10b5-1 3235-AM86
  • SEC Proposed Rule Stage Climate Change Disclosure 3235-AM87
  • SEC Proposed Rule Stage Human Capital Management Disclosure 3235-AM88
  • SEC Proposed Rule Stage Cybersecurity Risk Governance 3235-AM89
  • SEC Proposed Rule Stage Special Purpose Acquisition Companies 3235-AM90
  • SEC Proposed Rule Stage Rule 14a-8 Amendments 3235-AM91
  • SEC Proposed Rule Stage Proxy Voting Advice 3235-AM92
  • SEC Proposed Rule Stage Disclosure Regarding Beneficial Ownership and Swaps 3235-AM93
  • SEC Proposed Rule Stage Share Repurchase Disclosure Modernization 3235-AM94
  • SEC Proposed Rule Stage Reporting of Proxy Votes on Executive Compensation and Other Matters 3235-AK67
  • SEC Proposed Rule Stage Amendments to the Custody Rules for Investment Advisers 3235-AM32
  • SEC Proposed Rule Stage Amendments to Rule 17a-7 Under the Investment Company Act 3235-AM69
  • SEC Proposed Rule Stage Amendments to Form PF 3235-AM75
  • SEC Proposed Rule Stage Money Market Fund Reforms 3235-AM80
  • SEC Proposed Rule Stage Rules Related to Investment Companies and Investment Advisers to Address Matters Relating to Environmental, Social and Governance Factors 3235-AM96
  • SEC Proposed Rule Stage Electronic Submission of Applications for Orders Under the Advisers Act, Confidential Treatment Requests for Filings on Form 13F, and ADV-NR 3235-AM97
  • SEC Proposed Rule Stage Open-End Fund Liquidity and Dilution Management 3235-AM98
  • SEC Proposed Rule Stage Registration and Regulation of Security-Based Swap Execution Facilities 3235-AK93
  • SEC Proposed Rule Stage Prohibition Against Conflicts of Interest Relating to Certain Securitizations 3235-AL04
  • SEC Proposed Rule Stage Incentive-Based Compensation Arrangements 3235-AL06
  • SEC Proposed Rule Stage Broker-Dealer Liquidity Stress Testing, Early Warning, and Account Transfer Requirements 3235-AL50
  • SEC Proposed Rule Stage Transfer Agents 3235-AL55
  • SEC Proposed Rule Stage Electronic Filing of Broker-Dealer Reports 3235-AL85
  • SEC Proposed Rule Stage Electronic Filing of Form 1 and Form 1 Amendments; Form 19b-4(e) 3235-AM09
  • SEC Proposed Rule Stage Short Sale Disclosure Reforms 3235-AM34
  • SEC Proposed Rule Stage Market Structure Modernization 3235-AM57
  • SEC Proposed Rule Stage Portfolio Margining of Uncleared Swaps and Non-Cleared Security Based Swaps 3235-AM64
  • SEC Proposed Rule Stage Records to be Preserved by Certain Exchange Members, Brokers and Dealers 3235-AM76
  • SEC Proposed Rule Stage Trading Prohibitions Under the Holding Foreign Companies Accountable Act and Enhanced Listing Standards 3235-AM81
  • SEC Proposed Rule Stage Loan or Borrowing of Securities 3235-AN01
  • SEC Proposed Rule Stage Amendments to the Securities Transaction Settlement Cycle 3235-AN02
  • SEC Proposed Rule Stage Amendments to the Commission’s Whistleblower Program Rules 3235-AN03
  • SEC Final Rule Stage Pay Versus Performance 3235-AL00
  • SEC Final Rule Stage Universal Proxy 3235-AL84
  • SEC Final Rule Stage Filing Fee Disclosure and Payment Methods Modernization 3235-AL96
  • SEC Final Rule Stage Rule 144 Holding Period and Form 144 Filings 3235-AM78
  • SEC Final Rule Stage Tailored Shareholder Reports, Treatment of Annual Prospectus Updates for Existing Investors, and Improved Fee and Risk Disclosure for Mutual Funds and ETFs; Fee Information in Investment Company Ads 3235-AM52
  • SEC Final Rule Stage Exemption from the Definition of “Clearing Agency” for Certain Activities of Security-Based Swap Dealers and Security-Based Swap Execution Facilities 3235-AK74
  • SEC Final Rule Stage Establishing the Form and Manner With Which Security-Based Swap Data Repositories Must Make Security-Based Swap Data Available to the Commission 3235-AL72
  • SEC Final Rule Stage Regulation ATS for ATSs That Trade U.S. Government Securities 3235-AM45
  • SEC Final Rule Stage Amendments to NMS Plan for the Consolidated Audit Trail-Data Security 3235-AM62

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FootballCoin Launches Euro 2020 Fantasy Game

Press Release: FootballCoin launched a new version of its fantasy football game for EURO 2020, with a host of new features, NFT cards, and prizes.  11th June 2021, Dubai, UAE — Pioneering Football Fantasy Blockchain platform FootballCoin launched the new version of its game for EURO 2020. The announcement comes with increased prizes for all … Continued

The post FootballCoin Launches Euro 2020 Fantasy Game appeared first on BeInCrypto.



Press Release: FootballCoin launched a new version of its fantasy football game for EURO 2020, with a host of new features, NFT cards, and prizes. 


11th June 2021, Dubai, UAE — Pioneering Football Fantasy Blockchain platformFootballCoin launched the new version of its game forEURO 2020. The announcement comes with increased prizes for all daily contests and a 100.000 XFC prize for top managers in the game.

EURO 2020 fantasy football


For anyone who is either getting ready to watch the Euro 2020 matches, enjoys fantasy football, or is passionate about cryptocurrency and the exciting world of NFTs, there could be no better entertainment than FootballCoin this summer.

Euro 2020 Fantasy is a free-to-play game with NFT player cards and includes every match from the tournament in the FootballCoin daily contests. Players can register and play for free for the chance to win prizes in the platform’s native XFC coin or convert those prizes into fiat currency.

NFT player cards and XFC coin

NFT player packs containing NFT player (and stadium) cards can be purchased in the game for as little as $12.

NFT Cards can be bought, sold, and even loaned (just like real players) on the vibrant FootballCoin marketplace. In addition, all fantasy cards are visible and registered on the blockchain, giving FootballCoin NFTs real utility to earn more XFC coins.

XFC is the game’s native cryptocurrency, but it is also tradable against fiat on crypto trading platforms. Most of the XFC trading volume takes place on centralized exchangeWhitebit. XFC can also be purchased safely on the FootballCoin platform with a credit card. 

How to play FootballCoin

Interested parties can enter the fantasy football contests by registering for free on theFootballCoin signup page. After signup, users simply select a contest to compete in and then create a draft of 11 players + five subs from a roster of real footballers.

XFC winnings are determined by how well the players perform in their real games. Real data determines this to score player performances. Each Euro 2020 game allows users to select a new draft composed of players participating in the competition. Choose the ultimate fantasy football draft and win.

FootballCoin: Changing the NFT game

2021 has seen a rise in sports-related NFT and blockchain projects. For example, NBA Top Shot and other football NFT sports projects have taken off, and FootballCoin is set to be the next NFT sports platform to explode in the space.

While NBA Top Shot focuses on collectibility in typical sports card fashion, FootballCoin allows users to not only build their sports card collection but become “managers” and use their cards to compete each day for rewards and prizes in real football fantasy contests.

Other fantasy football games using cryptocurrency to buy NFTs sometimes charge hundreds or thousands of dollars and also have other limiting aspects to the fantasy game experience.

By contrast, FootballCoin has been using NFTs as the central pillar of the concept for over four years, withplayer card NFTs starting at a price of around $3 and no additional fees for selling, trading, or leasing.

Interested parties can sign up for free at FootballCoin and start collecting NFT cards for the EURO 2020 Fantasy game. 

For more information about FootballCoin, please visit —

FootballCoin Socials

Website |Twitter |Facebook |Telegram |Whitepaper

Media Contact Details

Contact Name: Silvio

Contact Email:

FootballCoin is the source of this content. This Press Release is for informational purposes only. The information does not constitute investment advice or an offer to invest.


All the information contained on our website is published in good faith and for general information purposes only. Any action the reader takes upon the information found on our website is strictly at their own risk.

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I was born in Russia. I have a degree in Chinese Economy and now studying Marketing at Higher School of Economics. I have been following blockchain technology for several years and decided to connect my career with crypto industry. My passions also are Netflix and science fiction books.

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Elon Musk lays out when Tesla will begin accepting Bitcoin payments

Musk responded to a Cointelegraph tweet about Sygnia CEO Magda Wierzycka calling for the SEC to investigate him over alleged Bitcoin price manipulation.



Tesla CEO Elon Musk says his electric-vehicle company will start accepting Bitcoin (BTC) payments once there’s confirmation that miners are utilizing clean energy, offering a glimmer of hope that the FUD surrounding digital assets could soon subside. 

Musk responded to a Cointelegraph tweet about recent accusations from Sygnia CEO Magda Wierzycka, who called on the United States Securities and Exchange Commission to investigate the billionaire for allegedly manipulating Bitcoin’s price.

According to Wierzycka, Musk knowingly pumped the price of Bitcoin only to sell a “big part of his exposure at the peak.”

“This is inaccurate,” Musk said in a Sunday response. “Tesla only sold ~10% of holdings to confirm BTC could be liquidated easily without moving [the] market.”

As Cointelegraph reported, Musk acknowledged in April that Tesla had sold a portion of its Bitcoin holdings to prove its liquidity as an alternative to cash. Just one month earlier, the billionaire confirmed that Tesla added $1.5 billion worth of BTC to its balance sheet and would begin accepting the virtual asset as payment for its vehicles. 

However, Tesla’s embrace of Bitcoin-as-a-payment was short-lived after Musk flagged concerns over the cryptocurrency’s energy usage. On May 12, Musk tweeted that his company would no longer accept Bitcoin payments due to the network’s “increasingly rapid use of fossil fuels…”

Musk’s tweet coincided with a slew of negative headlines about Bitcoin’s energy usage, China’s intent to ban Bitcoin mining and an overextended crypto rally that was showing signs of weakness. The news cycle helped trigger one of Bitcoin’s most painful episodes, culminating in a 54% drop between mid-April and mid-May.

Related: ‘I have not sold any of my Bitcoin’: Elon Musk.

On Sunday, Musk laid the groundwork for when Tesla will once again accept Bitcoin payments:  

“When there’s confirmation of reasonable (~50%) clean energy usage by miners with positive future trend, Tesla will resume allowing Bitcoin transactions.”

As Cointelegraph reported, Musk was recently invited to a meeting of Bitcoin miners by MicroStrategy CEO Michael Saylor. The Bitcoin Mining Council, a voluntary, self-regulating industry body, emerged from the meeting with a mandate to use more renewable energy and promot more transparency in the mining process.

Despite all the criticism about Bitcoin mining, it’s estimated that a strong majority of miners already use alternative energy resources.

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Next-Gen Decentralized NFT Platform, NEFTiPEDIA Announces Launch of its ICO In 3 Days

Next-Gen Decentralized NFT Platform, NEFTiPEDIA Announces Launch of its ICO In 3 Days

NEFTiPEDIA, a next-generation decentralized NFT platform that operates in a way that contributes to the elevation of digital artists, creators, and investors has announced the launch of its ICO which is set to happen in 3 days. NEFTiPEDIA has designed a commission-free platform to enable its artists to maximize income, following its aim to help […]



Next-Gen Decentralized NFT Platform, NEFTiPEDIA Announces Launch of its ICO In 3 Days

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NEFTiPEDIA, a next-generation decentralized NFT platform that operates in a way that contributes to the elevation of digital artists, creators, and investors has announced the launch of its ICO which is set to happen in 3 days.

NEFTiPEDIA has designed a commission-free platform to enable its artists to maximize income, following its aim to help them increase revenue via NFTs.

Following NEFTiPEDIA’s plans to storm the marketplace while launching its ICO, it aims to serve the marketplace with different categories of products including cosmetics, vehicles and property.

“….we believe NEFTiPEDiA will become a community-run marketplace and the industry will make our project as a kind and remarkable one in the world,” the announcement reads.

The development will see the platform provide a decentralized marketplace for Artists, where they can sell and validate their NFT links to fans and interested buyers.

Advertisement &  & 

NEFTiPEDIA Offers Exciting Prizes to Users

The team behind the project have allotted a total of 250,000,000 $NFT tokens for its users to enjoy in the upcoming ICO.

To further celebrate the intended development, the platform has proposed a referral scheme where winners can enjoy amazing and exciting prices.

Users who wish to participate in the program are required to sign up for the platform’s ICO panel and get a referral code.

The code can as well be shared with friends, giving users the opportunity to win exciting prizes.

A minimum of 5 referrals is required for participants to be considered for winning.

“Only those referrals ended in purchase will be added to the count. After the completion of ICO in 30 days, winners will be announced. Notably, winners will bear all the applicable tax.” The team further elaborated on the conditions for winning.

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