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Bitcoin SV (BSV) Mines World Record 128MB Blocks

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Bitcoin SV (BSV) recently witnessed not one, but two, 128MB blocks mined on its network – the world’s largest ever on a public blockchain. The first huge block was mined on March 30, 2019 by nChain’s BMG Pool; just a day later on March 21, the second 128MB block was mined by entrepreneur Calvin Ayre’s CoinGeek Mining operation. These record-setting blocks prove that massive on-chain scaling works on Bitcoin, and Bitcoin SV is succeeding as the only project following Bitcoin’s original design and protocol.

Bitcoin SV emerged from the world’s first Bitcoin “hash war” last November, initially as a competitor to the Bitcoin ABC implementation of Bitcoin Cash (BCH) and now as its own chain and BSV token. Named for the “Satoshi Vision” of Bitcoin’s creator Satoshi Nakamoto, Bitcoin SV restores the original Bitcoin protocol, will keep it stable, and allow it to massively scale to a global network used by billions of people.

Bitcoin SV currently has a default maximum block size of 128MB, meaning the recent huge blocks contained sufficient data from BSV users to fill the current cap. The two 128MB blocks come as Bitcoin SV witnessed multiple days of big action, including a 113MB block mined on March 28 by CoinGeek Mining and numerous blocks above 50, 60 and even 80MB – all far larger than blocks on any other competing blockchain.

The big blocks come from organic growth as users take advantage of BSV’s larger data capacity for the OP_RETURN field, a place in Bitcoin transactions to embed metadata. Whereas the Bitcoin Core and Bitcoin Cash ABC networks still restrict OP_RETURN data to much smaller sizes, BSV is lifting such limits to unleash the Bitcoin blockchain’s power to act as a global commodity ledger and data network. BSV’s recent big blocks contain large data files (high-resolution pictures) uploaded using the BitPaste multi-swipe application, which makes it easy for users to upload large files with quick swipes of MoneyButton. Other users have uploaded music and even video files to BSV.

As its big blocks are more routine, Bitcoin SV debunks incorrect notions of Bitcoin Core (BTC) (now more accurately called SegWit coin) which opposed on-chain scaling, capped its block size at a tiny 1MB, and instead pursued Segregated Witness and a Layer 2 payment solution in Lightning Network. BSV also disproves Bitcoin Cash ABC developer claims that it is not yet practically feasible to sustain blocks above 32MB (the default limit on BCH ABC).

The 128MB blocks are notable for another reason: each generated transaction fees for the successful miner of 1.279 BSV, adding another 10+% of miner revenue on top of the normal 12.5 BSV block reward. This demonstrates how massive on-chain scaling allows more transactions (of differing data types and differing fee levels) in a block, which in turn results in more revenue for miners. Bitcoin block rewards halve every 4 years, happening again next year as the block reward reduces from 12.5 to 6.25 coins. For mining to remain profitable to sustain the network, Bitcoin’s economic model requires miners to progressively earn more transaction fees to make up for the continually-reducing block reward value. That only happens with bigger blocks – as now demonstrated by BSV – to ensure Bitcoin’s long-term success. In contrast, other networks undermine Bitcoin’s economic incentive model by refusing to massively scale on-chain – with the BTC network’s biggest block to date only 2.3MB on March 11, 2019 and the BCH ABC chain only having a 4.6MB block on December 18, 2018. (The original Bitcoin Cash (BCH) chain had bigger 32MB blocks but that chain no longer exists after the November 2018 hard fork event; in any event, the 32MB blocks mined on the prior BCH chain were done using the Bitcoin SV implementation.)

Jimmy Nguyen, Founding President of Bitcoin Association which advances the global Bitcoin SV ecosystem, observes:

“For too much of its 10-year life, Bitcoin has been artificially restricted. BSV users are now proving the original Bitcoin can massively scale and that Satoshi Vision is correct. We are thrilled to see the explosion of user creativity organically fill big blocks with new forms of data and generate more transaction fees for miners. With the BSV network handling big blocks quite well, we look forward to lifting the block cap even higher this year.”

Scaling even bigger is the next step for BSV. In March, the Bitcoin SV Node team announced results from its BSV Scaling Test Network showing 128MB blocks were successfully sustained for 36 continuous hours. Later this year, the BSV Node team expects to lift the default block cap to 512MB, en route to 1 gigabyte (1000 megabytes) or higher block caps. The ultimate goal is to have no default block limit, and allow miners to fully decide for themselves what block sizes to accept and create new competitive marketplaces for mining.

Nguyen adds:

Whereas other Bitcoin and cryptocurrency project supporters focus on price and market cap, Bitcoin SV is building a blockchain that is ready for business with massive scaling, with real utility to support real long term price value. We are also building an ecosystem that is regulation-friendly, which is essential for Bitcoin usage to become widespread. For any big business looking to build blockchain applications, we invite you to build on the global enterprise blockchain and to use the world’s new money – Bitcoin SV.”

UPCOMING: COINGEEK TORONTO CONFERENCE – May 29-30Toronto, Canada

Come learn more about what Bitcoin can do with “No Limits” and the latest on-chain scaling developments with Bitcoin SV at the CoinGeek Toronto conference May 29-30. Bitcoin Association is a proud supporter of CoinGeek events. It’s easy to register. And pay with the world’s new money and you’ll receive a discount by using BSV via Coingate.

 

SOURCE Bitcoin SV

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IJCAI 2019 in the Spotlight: WeBank AI Group Shared Remarkable Academic Innovation

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The 28th International Joint Conferences on Artificial Intelligence (IJCAI) was held from August 10th – 16th, in Macao, SAR, China. WeBank, the first private and digital bank in China, contributed to the event with multiple academic research findings, and demonstrated great engagement in IJCAI by organizing a heavy-weight workshop FML’19 (the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality).

100+ World-leading Scholars Discussed Academic Frontier at the 1st International Workshop on Federated Machine Learning

The idea of adopting FML in AI for data confidentiality and user privacy was coined by WeBank in China. In a bid to promote this emerging AI technology, WeBank, IBM and other organizations jointly held the 1st International Workshop on Federated Machine Learning in conjunction with IJCAI 2019. 100+ leading scholars with insight in FML from home and abroad were invited to share cutting-edge academic findings and most advanced applications. President of IJCAI, Chief AI Officer of WeBank Professor Qiang Yang delivered opening remarks. Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google delivered keynote addresses. The moderator of panel discussion, AI Principal Scientist of WeBank Dr. Lixin Fan joined panelists including Professor Benny Pinkas from Bar-Ilan University, Dr. Shahrokh Daijavad of IBM Academy of Technology, Chief Architect of Squirrel AI Dr. Richard Tong, Research Scientist of Google Dr. Jakub Konečný, Dr. Baofeng Zhang from CTO Office of CBG Software in Huawei, Executive VP of Clustar Dr. Junxue Zhang, VP of AI Institute in Sinovation Ventures Dr. Ji Feng and other experts in exchanging thoughts on the way ahead for FML.

Take Stock on 40 Years’ Achievement of AI in China  Panel Discussion Featuring Chinese Characteristics

Elements of previous conferences including Traditional AI Session, Industry Day focused on industrial application and Best Paper Awards Session were inherited in this year’s IJCAI. IJCAI-19 also opened panels and workshops under the new agenda with a focus on most-discussed topics e.g., data privacy and AI universality. Chief AI Officer of WeBank Professor Qiang Yang engaged in multiple agendas as the President of IJCAI-19 and chair of two panel discussions namely AI in China, AI and User Privacy.

Panelists of “AI in China” include Academician of Chinese Academy of Sciences Bo Zhang, Academician of Chinese Academy of Engineering Wen Gao, Dean of School of AI of Nanjing University Professor Zhihua Zhou, Professor Pascale Fung of Department of Electronic and Computer Engineering of HKUST, Professor Tong Zhang of HKUST, CEO of 4Paradigm Wenyuan Dai. These leading figures in China’s AI sector shared stories within the industry. This theme, with its unique historic significance, added weight to IJCAI-19.

IJCAI-19 also witnessed the founding of the GuangdongHong KongMacao Greater Bay Area on AI and Robotics Federation. Announced at “AI in China” Panel, the establishment of this new Federation requires the three academic societies to pool leading scholars and experts in AI and robotics within their localities. The merge was widely supported, acclaimed and recognized across the industrial sector and the government as it will further promote cohesion of talents, spawning of scientific innovation, R&D and application of key technologies in China.

“AI and User Privacy” Panel was joined by Director of IEEE Standards Association Victoria Wang, Professor Pedro Domingos of University of Washington, Director of Swiss Re Institute Jeffrey Bohn, Senior Research Scientist of WeBank AI Dr. Yang Liu and a host of experts and scholars to further discussions on how to promote technology development and legislation process simultaneously, which is helpful to addressing the user privacy issue in the current stage of AI development.

WeBank Shared New Insight on AI Safety Workshop

Besides user privacy as discussed in the panel discussions, data confidentiality also represents a common concern in the age of big data. At the AI Safety 2019 Workshop, Senior Research Scientist of WeBank AI Dr. Yang Liu delivered a speech themed Federated Machine Learning (FML), and shared in-depth insight on how to safeguard user privacy and AI safety as well as a number of technologies for privacy protection. She also elaborated on three categories of FML, namely Horizontal Federated Learning, Vertical Federated Learning, Federated Transfer Learning. According to Dr. Liu, data confidentiality and user privacy are the two major challenges in the age of big data, particularly challenging for financial, medical, legal and other data sensitive industries, whereas FML is a great solution to both challenges.

AI Enabling Contextualized Application in Finance  WeBank Shared Insight on Digital Innovative Transformation

While FML serves as the theoretical basis, the application of FML represents a common concern for all walks of life. Challenges before the highly digitalized financial sector manifest even greater complexity and risk. At Industry Day in IJCAI 2019, Deputy Managing Director of WeBank AI Tianjian Chen shared in-depth insight on digital banking business in the financial sector under the theme “AI in Digital Banking”, and elaborated on the important role that AI plays in digital banking. Given the challenges of AI application in the financial sector, he pointed the way ahead for the new generation of AI. “Safety, fairness, data protection are major challenges in the application of AI in the banking sector,” he said. “FML is potentially the new path to take for addressing these challenges.” So far, WeBank AI Group has developed a series of pioneering technologies including FML, which are proven to be contributive to joint modeling for credit risk control and anti-money laundering, etc.

Demonstration of FML Visualization  WeBank Introduced Best Practice

WeBank AI Group is dedicated to promoting widespread application of FML across the industry, sharing capabilities, enabling multi-win results. Videos submitted by WeBank AI Group, including Multi-Agent Visualization for Explaining Federated AI, Learning Federated Learning, were accepted by Demonstration Track and AI Video Competition of IJCAI-19, of which, the latter was awarded Most Educational Video. The videos provide straightforward illustration of cases to attendees on how FML and FedAI system works, all designed for more partners within the industry to enhance understanding of FML technologies and become promoters.

As an endeavor to explore “AI + Art” fusion, the man-computer car racing game demo developed by WeBank AI Group based on FML technology will be displayed under the invitation of China Central Academy of Fine Arts, and is expected to be showcased in the Shenzhen and Shanghai Art Exhibition scheduled in late October and early November respectively.

Among 35 papers submitted in Demonstration Track, the research paper on AI empowering flexible staffing by WeBank, HKUST, NTU and BBK Group, titled Fair and Explainable Dynamic Engagement of Crowd Workers, won the Innovation Award.

WeBank “AI+X” Innovation Debut  Exploration of Future AI Ecosystem

In addition to academic research findings, WeBank AI Group also exhibited industry-leading innovations in four main areas namely “AI + Service”, “AI + Marketing”, “AI + Big Data”, “AI + Asset Management”, which drew the attention of government officials from Macao SAR, professors and scholars of universities and research institutions in China and abroad.

In the area of “AI + Big Data”, WeBank established FedAI ecosystem for cooperation, the world’s first industrial-grade framework for Federated Learning (FATE), AI scenario-based rapid modeling platform (QML). In “AI + Service”, WeBank explored new approaches and scenarios for human-computer interaction, developed ubiquitous robots focused on financial services, integrated core technologies such as NLP, TTS, OCR with scenarios, and expanded to a series of business contextualized applications. The robot developed independently by WeBank became a spotlight in the exhibition. In “AI + Marketing”, WeBank AI Group played a leading role in trust marketing development, aimed to promote long-link and long-term effective marketing conversion of high-value products. In “AI + Asset Management”, WeBank used new alternative big data and machine learning technology helped forge a new generation of AI-driven intelligent asset management system.

China’s scientific research capability is among the top in the world thanks to advances in big data, AI and other frontier technologies. As an internet bank dedicated to innovation in fintech, WeBank AI Group demonstrates its commitment in global collaboration for scientific research and sparks technological advances by coupling theory and application. Looking ahead, WeBank will further leverage its strength in AI technology and platform, integrate top-notch resource worldwide, forge high-level network for knowledge and research, and lead the way for global tech innovation.

 

SOURCE WeBank

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Galaxy Digital to Host a Shareholder Update Conference Call on Wednesday, August 28, 2019 at 9:00AM EDT

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Galaxy Digital Holdings Ltd. (TSXV: GLXY; Frankfurt: 7LX) (“Galaxy Digital” or the “Company”) is pleased to announce that it will report second quarter 2019 financial results before the opening of the TSX-Venture Exchange on Wednesday, August 28, 2019.

Michael Novogratz, CEO and Founder of Galaxy Digital, and members of management will host a conference call to provide a general update to shareholders on the Company’s activities and results on the same day at 9:00 am Eastern Daylight Time (EDT).

The dial-in number for callers in the United States or Canada is 800-289-0459. The dial-in number for callers in Germanyis 0800-589-4608. Callers who reside outside of the United StatesCanada or Germany should dial +1-323-794-2558. The passcode for all participants is 877692. For those unable to participate, an audio recording of the call will be available on the Company’s website until at least 5:00 pm EDT on September 17, 2019.

 

SOURCE Galaxy Digital Holdings Ltd

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Crypto Earn: Now Earn 8% p.a. on DAI & MKR Deposits

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Crypto.com, the pioneering payments and cryptocurrency platform, announced today that it has listed Maker (MKR) and added DAI & MKR to Crypto Earn, allowing users to enjoy up to 8% p.a. on their deposits.

Dai (DAI) DAI is a USD-pegged stablecoin running on the Ethereum developed by the MakerDAO team. Its $1 USDequivalent is maintained through a dynamic system of Collateralized Debt Positions (CDPs), autonomous feedback mechanisms, and appropriately incentivized external actors. DAI can be used in the same manner as any other cryptocurrency: It can be freely sent to others, used as payments for goods and services, or held as long term savings.

Maker (MKR) is an ERC-20 token on the Ethereum blockchain that backs and stabilizes the value of stablecoin DAI through automatic pricing mechanisms built into smart contracts. MKR tokens are created or destroyed in accordance with price fluctuations of the DAI coin in order to keep it as close to $1 USD as possible and is part of a fully inspectable system on the Ethereum blockchain. MKR tokens are also used to pay transaction fees on the Maker system, and provide holders with voting rights within Maker’s continuous approval voting system.

Crypto Earn now supports 13 coins for holders to maximize their returns, including BTC, ETH, LTC, XRP, BNB, TUSD, PAX, USDC, MCO, BAT, LINK with the addition of DAI and MKR. Interest is paid out weekly in the coin deposited with flexible, 1-month or 3-month terms available. Users earn more by staking at least 50 MCO.

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