HOUSTON, April 25, 2024 (GLOBE NEWSWIRE) -- <strong>Sysco</strong> Corporation (NYSE:SYY) today announced that the Board of Directors has approved a $0.01 increase in the quarterly cash dividend to $0.51 per share from the current $0.50 per share. The new dividend is payable for the first time on July 26, 2024, ...

Sysco Declares Increase to Quarterly Dividend

<strong>Sysco</strong>&#x27;s SYY short percent of float has fallen 4.51% since its last report. The company recently reported that it has 6.33 million shares sold short, which is 1.27% of all regular shares that are available for trading. Based on its trading volume, it would take traders 2.65 days to cover their ...

Looking Into Sysco's Recent Short Interest - Sysco (NYSE:SYY) - Benzinga

Welcome to Sysco's First Quarter Fiscal Year 2024 Conference Call. As a reminder, today's call is being recorded. We will begin with opening remarks and introductions. I would like to turn it over to Kevin Kim, Vice President of Investor Relations. Please go ahead. Kevin J. Kim

Q1 2024 Sysco Corp Earnings Call

Food distribution giant Sysco has made multiple executive moves since September, including creating a new global COO role.

Food distribution giant Sysco makes multiple executive changes, plans to grow sales team

HOUSTON (AP) — HOUSTON (AP) — Sysco Corp. (SYY) on Tuesday reported fiscal first-quarter earnings of $503.4 million. The Houston-based company said it had net income of 99 cents per share. Earnings, adjusted for one-time gains and costs, were $1.07 per share.

Sysco: Fiscal Q1 Earnings Snapshot

Sysco Corporation SYY started fiscal 2024 on a strong note, with the first-quarter top and bottom lines increasing year over year and earnings beating the Zacks Consensus Estimate. Results were aided by higher volumes,

Sysco (SYY) Q1 Earnings Top Estimates, Volume Gains a Driver

Sysco (SYY) came out with quarterly earnings of $1.07 per share, beating the Zacks Consensus Estimate of $1.02 per share. This compares to earnings of $0.97 per share a year ago. These figures are adjusted for non-recurring items.

Sysco (SYY) Q1 Earnings Surpass Estimates

This includes our planned acquisition of Edward Don & Company, one of the largest kitchen ... except as required by applicable law. Sysco is the global leader in selling, marketing and distributing food products to restaurants, healthcare and educational ...

Sysco Corporation: Sysco Reports First Quarter Sales and Operating Income Growth; Reiterates Fiscal Year 2024 Guidance

Sysco Corporation (NYSE: SYY) (“Sysco” or the “company”) today announced financial results for its 13-week first fiscal quarter ended September 30, 2023. Key financial results for the first quarter of fiscal year 2024 include the following (comparisons are to the same period in fiscal year 2023): “Sysco delivered another quarter of compelling earnings results,

Sysco Reports First Quarter Sales and Operating Income Growth; Reiterates Fiscal Year 2024 Guidance

Sysco

sysco

What is Happening? Syscoin is Rollux, the new Optimistic & ZK-Rollups tool that will enable projects operating on the Sys network directly or over a bridge with the scalability capabilities they need to deliver Web3 services at high throughput. launching The Rollux is a white glove service whose optimistic roll-ups use modular tech to give Layer 2 capabilities. Layer 2 scaling can be accomplished using optimistic rollups as it improves performance by offloading part of the processing work of the main or layer 1 chain, which leads to faster processing times. To understand the impact of Rollux, it is better to visualize Web2-like speed and efficiency but with the decentralization and economic viability that Syscoin can provide, owing to the unique combination of Bitcoin and Ethereum architecture. As pioneered by Jag Sidhu, Syscoin's Network-Enhanced Virtual Machine (NEVM) is the first to implement (PoDA). Proof-of-Data Availability : Vested Interest Disclosure The author is an independent contributor publishing via our . Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story.  HackerNoon has reviewed the story for quality, but the claims hereon belong to the author. #DYOR brand-as-author program Jagdeep Sidhu, the Lead Developer at Syscoin, said: There has recently been renewed interest in the security and scalability aspects of Optimistic roll-ups that have forced us to take another look at this technology even though we strongly believe in ZK-Rollups. One of these reasons is code-base maturity: Optimistic roll-ups are already more mature than ZK because a Zk-EVM is yet to be released and tested in the wild. We also believe that with direct EVM equivalence such as Nitro and Cannon technologies, we can unlock performance and scale that will advance the space and likely give a window of a few years before ZK-Rollups will be as efficient. What is Syscoin? Open-source blockchain project Syscoin, launched in 2014, uses the NEVM blockchain to merge the best Cryptocurrencies into a single modular platform. With Syscoin's rollups and other Layer 2 technologies, ledger technology is moving into the next development phase, bringing together Bitcoin's proven security and Ethereum's Turing-complete programmability. Syscoin's master node service layer offers extra ledger security through chain locks for user projects. Why Should We Care About Syscoin’s Rollux? Syscoin NEVM and Rollux provide low-cost and high-performance throughput for smart contracts and interoperability that can be scaled up, while offering strong decentralized settlements and reconciliation capabilities - . this ensures a layer one blockchain which has scalable smart contracts Syscoin Rollux and NEVM are protected by Bitcoin's own proof-of-work security mechanism through merge-mining. Syscoin Rollux and NEVM can be used in smart cities, IoT Devices, and decentralized applications to create applications that run on a low-cost and modular layer one design. As the hazards of the experimental security approach "come home to roost," blockchain users and market players appreciate the need for verified security. Rollux allows the building of zero-knowledge proofs on the NEVM side to provide Turing-complete smart contracts with scalability and trustless interoperability. When using zkRollups and zero-knowledge proofs, contracts on Syscoin would only have to wait a few hours, and these withdrawal delays may be avoided altogether. Rather than re-running transactions, smart contracts may give succinct proofs of one-time executions, which can be verified in parallel, to support an unbounded number of transactions due to Sys Rollux and NEVM. How Do Rollux Impact Layer 2 Decentralized Applications? The Rollux innovation by Syscoin is critical for scaling layer 2 applications, as rollux allows for scaling of smart contracts as Layer 1 consensus is achieved by the use of rollups, which undertake transaction execution outside of layer 1. The modular nature of the layer one blockchain allows for trustless cross-chain interoperability which enables easier integration with a wide range of blockchains at far lower costs and technological overhead making it easy for web3 developers to create applications that can be connected to other blockchains such as Tezos, Polkadot and Solana etc. to Jag Sidhu, as a result of optimistic rollups implemented through Rollux, the blockchain may grow by a factor of 50 or more, reducing the possibility of censorship. All transactions can theoretically be processed and executed by blockchain nodes if they were rolled up because nodes can only do a specific number of calculations per second before they can no longer keep up with the network, this would reduce the congestion. According If these transactions are represented as rollups, the checks are significantly easier. As a result, if the Ethereum ecosystem's software (parity/geth) decides to boost the network's processing capacity at any point, the transactions might theoretically be completed in parallel. Validity proofs using Rollups are used to establish that smart contracts were performed successfully without the need for external consensus. To put it another way, data storage and availability requirements for protocols are more flexible as compared to current blockchain systems. Due to this Rollux makes it easy for layer 2 decentralized applications to have a high throughput rate, with a high rate of scalability, security and flexibility. To build decentralized applications for the future, it is critical to have a layer one blockchain which is scalable with high security and low transaction costs. Final Thoughts on Syscoin Rollux Release I believe that new technological innovation in layer one blockchain architecture and infrastructure pushes forward the competition between blockchains to provide an ecosystem for building applications that are flexible, scalable, and secure in nature. Syscoin’s rollux release is a technological innovation that tries to approach the problems faced by blockchains, such as scalability, security, and decentralization by combining the advantages of optimistic rollups, ZK-rollups, and off-chain settlement with a cross mining mechanism that is based on both Bitcoin and Ethereum. Don’t forget to like and share the story! Image credits: Syscoin, , and . Shubham Dhage Pierre Borthiry

Syscoin Launches Rollux to Scale Layer Two Decentralized Applications 

Disrupting Organizations with Decentralized Governance through DAOs Jag Sidhu, President of the Syscoin Foundation, announced a plan to develop a new standard for Decentralized Autonomous Organizations while speaking in Dubai at the Binance Blockchain Week 2022 conference (DAOs). The Syscoin Foundation has begun work on a project that they believe will be a big evolutionary step for DAO technology, bringing fresh vitality to the market. In addition, the company wants to start implementing its groundbreaking new model in 2022. To date, DAOs have been plagued by significant problems and have failed to match the spirit of bitcoin. Self-sovereign capital is the core value proposition of cryptocurrencies. ‘Nor my keys, not my cash,’ says the narrator. DAOs now possess users’ funds and manage them in a treasury managed by a few persons. It’s akin to not being able to control your wallet’s keys. Furthermore, present governance systems are incompatible with stakeholder values. Typically, governance does not control the protocol directly; rather, it serves as an advisory vote to signers on the multi-sig that controls the treasury. The common gap between a DAO governance token and the protocol’s real value proposition exacerbates the problem. With an innovative methodology for organizing bitcoin as capital investments, DAOSYS attempts to overcome these concerns. DAOs, according to the Syscoin Foundation, should function more like pure AMMs, with an autonomous and permissionless protocol that anybody may use to consume the DAO’s services, essentially functioning as autonomous economic agents. This indicates that DAOs must go beyond the present phase of capital extraction maximization. The economics must be customized to support the DAO’s mission statement and executed without the need for external controls. With the current state of smart-contract and DeFi architecture, it was almost impossible to construct a functioning DAO prior to this endeavor. It is feasible to deploy DAOs simply as a liquidity pool by iterating on the AMM model to generalize the process. Without the use of a governance token, a treasury management platform may be built using antifragile tokenomics and interactions with DeFi protocols. Existing markets may be used to organize money to carry out mission statements by future DAOs. DAOSYS includes this technology, known as the Autonomous Service Engine. Understanding DAOSYS and Autonomous Service Engine DAOSYS will be a reference design that will use the Autonomous Service Engine to turn Syscoin into an innovation hotspot by allowing users to control their assets. A risk-mitigating financing mechanism is created due to the antifragile market architecture. This moves the major risk in supporting new projects and activities from the Syscoin Foundation’s treasury to basic opportunity cost, resulting in some great efficiencies for the Syscoin Foundation and all who participate. Because it is intended to promote the progress of Syscoin’s ecosystem, a full-stack Layer 1 blockchain with a modular architecture that enables a scalable Layer 2, DAOSYS will be well-positioned to encourage digital value from the ground up. The non-profit Syscoin Foundation’s purpose with this program and its DAOSYS implementation is to offer the breakthroughs needed for DAO technology to disrupt for-profit business and NGO funding by becoming a go-to innovation engine. Syscoin is a decentralized and open-source project launched in 2014 and uses the NEVM blockchain to merge the best of Bitcoin and Ethereum into a single modular platform. Through ZK-Rollups and other Layer 2 technologies, Syscoin is ushering in the next phase in the development of blockchain technology, bringing Bitcoin’s proven security and Ethereum’s Turing-complete programmability to genuine scalability. Catch all the breaking news, and Don’t forget to like the story! Image credits: and . Brian McGowan David Rodrigo The content of this story DO NOT represent the views of HackerNoon and are meant as information only from the lens of the independent contributor. Please DYOR before investing.

Syscoin is Launching DAOSYS to Revolutionize DAO Governance 

Disclosure: This article is sponsored by Syscoin to sustain my blockchain innovation series. I'm not part of Syscoin or hold/receive any Syscoin tokens. This article is part of my blockchain innovation series where I try to spot interesting technology that might impact the further development of blockchain. Today’s innovation talks about a directed acyclic graph (DAG) technology and how gave a twist to this concept with their Z-DAG implementation. Syscoin What is DAG technology? What is Z-DAG? How is Z-DAG different from a regular DAG? What is zero-confirmation in relation to DAG Technology? Techniques Syscoin Uses for Optimizing Transaction Throughput DAG: A Buzz or Breakthrough? If we simplify how blockchain works, we can compare it with a staircase. Each block you add is a new level on top of your staircase. So, your staircase grows vertically in a single direction. Staircase levels are stacked one at the time. This guarantees that the same transactions are recorded across all nodes in the network. In case a node decides to propose a malicious block or malicious transactions, your staircase would violate the “protocol” rules defined for building staircases. On the other side, a DAG can be compared with a tree which grows in several separate branches. Transactions are processed in a network of interlocking branches that grow outwards in multiple directions. The validation in a DAG is also quite different from a standard blockchain. Each newly added transaction to a branch is responsible for validating two previous transactions (depends on the protocol definition). If the transaction does not follow this guideline, it is impossible to be valid itself. It might sound like a weak requirement to only validate the two previous transactions. However, by validating the two previous transactions you are actually validating a whole branch of transactions connected to this last transaction. Source image: A simple DAG by Vasa Due to this division in branches, a DAG is able to confirm transactions much faster reaching very high speeds. I’m not gonna mention exact numbers as a lot of projects claim to have reached very high transaction throughput (TPS). But one thing is for sure, a DAG allows mostly for a higher TPS than regular blockchain technology. In short, a DAG is a very promising technology that allows for a higher TPS to be reached. It has an interesting structure similar to a tree where every transaction has to verify two prior transactions. In case you want to learn more about DAG technology, fellow writer Vasa wrote an amazing post going deeper into the DAG variations and its properties . What is Z-DAG Technology? Now we know what a DAG is, let’s explore what kind of beast Syscoin has built, naming it Z-DAG. According to Whiteblock CEO Zak Cole, “The Z-DAG protocol is extremely innovative and presents a practical solution for many of the performance issues that are currently bottlenecking the continued scalability of blockchain systems.” Let’s find out what is true about this statement! Diving into Z-DAG Technicals Zero-Confirmation Directed Acyclic Graph (Z-DAG) is a probabilistic transaction scheme that allows for one to separate micro/macro transactions with different security domain tradeoffs in exchange for convenience. Whereas Bitcoin applies PoW scheme on top of every micro or macro transaction, Z-DAG allows an interactive protocol for merchants to decide. Every merchant can accept or decline a Z-DAG transaction based on their preference. Every Z-DAG transaction that has entered the mempool and has some type of probabilities that it will get mined in the future since balances are tracked in real-time and not upon PoW. Upon PoW, however, the state is removed and reproduced based on the block. Because balances are updated in real-time based on transactions in mempool, it is a probabilistic model so the ultimate truth will be what the miners put into the block and what the block of transactions that has Proof of Work on it has in terms of which transactions get mined. Once miners mine a block, the state is replayed based on the state of the previous block. Thus, the probability model around Z-DAG settlement is the likelihood that transactions in the mempool and their balances accurately reflect the truth once miners create and forward blocks to the network. The balances have a high probability of being the same as when they first entered the mempool and settled via ZDAG. This means PoW is ultimately the partition tolerance in the system and the idea is that the view of the network and view of the miner is essentially the same after X seconds where X can be a reasonable amount of time before a transaction is propagated across the network. For now, they have chosen for 10 seconds for the reference client but it can come down as networks are exponentially increasing in efficiency and this can organically be tending towards 0. Source: Syscoin website — report Whiteblock How is Z-DAG different from a regular DAG? Regular DAG protocols do not rely on Proof-of-Work. These protocols include uncles or historical information to keep the graph from dissolving. There is typically no longest-chain-rule with DAGs as it is based on the probability that transactions are ordered based on the historical information provided. However, that comes with some problems. There is little to no partition tolerance which is why there is sometimes central or authoritative models to ensure the DAG doesn’t steer off course (referring to IOTA). With Z-DAG, the partition tolerance is around every block. For every block, the balances are set based on validating each transaction in a block. Therefore, the DAG cannot dissolve as it is only based on what happens within a block. This serves the purpose for a micro-transaction layer 0 solution on top of Proof-of-Work, ultimately settling transactions just like Bitcoin. What is zero-confirmation in relation to DAG Technology? “Z-DAG (Zero-Confirmation Directed Acyclic Graph) is an instant settlement protocol that is used as a complementary system to proof-of-work (PoW) in the confirmation of Syscoin service transactions. In essence, a Z-DAG is simply a directed acyclic graph (DAG) where validating nodes verify the sequential ordering of transactions that are received in their memory pools.” — Syscoin Whitepaper p.1 So, how does this tie back to a DAG? A DAG is a natural construction of transactions with dependencies on balances for dependability. In Bitcoin this dependence is affected after a block, in Syscoin it is affected upon mempool inclusion on every node. It is important to note that Satoshi wrote about a snack machine example where about 3 seconds is needed to detect a double spend. In the Syscoin implementation, they increased this time slot to 10 seconds but the real-time balances are adjusted and one can spend in a chain of transactions based on their balances, creating a natural DAG that is resolved every block. In Syscoin v3, they enforced the order of the DAG by doing topology sort and circuit detections. However, in Syscoin v3, this is not really needed because balances are strictly enforced and clients will not allow invalid transactions to be created in a block that would overflow a balance. Techniques Syscoin Uses for Optimizing Transaction Throughput Let’s take a look at some technical implementations Syscoin has implemented to improve the transaction speed of the overall network. 1. Parallel Signature Verification First of all, whenever a node receives a newly broadcasted transaction, it will relay the transaction to other nodes before validating it. This means that also potentially invalid transactions are broadcasted to the rest of the network. However, this approach allows for more transactions to be validated quicker. A couple of invalid transactions have minimal impact on the overall throughput of the network. This multithreaded approach greatly reduces the time it takes for signatures to be verified. Users choose the time they want to wait and as they wait longer and check the status of their transactions, it is more likely they will detect and not complete the transaction with the buyer in a point of sale application. How to Prevent for Double Spends? Syscoin recommends that 10 seconds is a good amount of time to wait for a transaction to arrive at your node before checking if it's valid. Of course, it's up to the merchant as it’s an interactive protocol. Also, balances are tracked throughout the system to detect two spends that overflow the balance. If this occurs, the sender will be flagged and the receiver will be able to see something went wrong. 2. Flagging Invalid Signatures Syscoin has a protocol in place that will flag a signature as invalid whenever the signature validation check fails in the multithreaded verification process. This flag causes the network to switch back to a single threaded mode in order for other nodes to not waste valuable time and resources on validating an invalid transaction. 3. Sub-linearly Scaling Transaction Throughput Syscoin’s whitepaper explains that a master node can scale to 700–1000 transactions per second (TPS) on average. This number is calculated with latency effects taken into account. However, when 100 of these master nodes are active, the whitepaper talks about a possible TPS of 70k. I questioned them about this statement to find out how this works. Jag Sidhu, the Lead Core Developer and co-founder, explained to me how this scaling works. “It would be a sub-linear increase in efficiency as more nodes enter and an exponential decrease in the effect of latent nodes on the overall functioning of ZDAG on the network. As more paths open up, latent nodes will trail messages where with fewer nodes, higher risk of depending on a latent node for information. Competitors of Syscoin Any DAG project is considered to be a competitor for Syscoin. Let's take a look at the competition. Nano Nano is also able to reach very high transaction speed as they leverage DAG technology. Nano has developed a new piece of technology called block-lattice that allows them to leverage DAG technology but still work like a traditional blockchain. Nano works with nodes that all act as an individual wallet or chain. Only the node owner can make changes to these individual chains which means they can be updated asynchronously. Fast transaction speed by block-lattice Zero transaction fees Byteball Byteball is one of the older projects in the blockchain space. Unlike Nano, transactions are not free on the Byteball chain. However, Byteball offers the feature of having fully private and untraceable transactions. Transaction verification in 30 seconds 51% attack impossible due to validator system to avoid double spends Private transactions IOTA IOTA is also one of the first DAG projects, or more know as Tangle. A new transaction can be added to the network if you first verify the two previous transactions (actually building the tangle). This means that they offer instant transactions which are zero fee. The main idea for IOTA is to build a DLT infrastructure for machine to machine payments, enabling economy 4.0 where smart machines communicate with each other and create a whole economy by itself. IOTA allows for micro transactions and can handle a high throughput. Zero fee transactions Developed for IOT (machine to machine) Enables micro transactions Hedera Hashgraph Hedera Hashgraph might be an odd one in the list as it is a patented technology. You can buy licenses to use the software. Hedera also uses DAG technology and gained attention with their gossip about gossip protocol. As this is too complex to explain for this article, you can find a . podcast here Drawbacks of Syscoin In general, many DAG projects have proven that they can handle very high transaction amounts. Often, much higher than a traditional blockchain. However, DAG technology is still in its infancy and there are still many questions about its performance and how decentralised they actually are. Specifically to Syscoin, whenever a node receives a newly broadcasted transaction, it will relay the transaction to other nodes before validating it. This means that also potentially invalid transactions are broadcasted to the rest of the network. It is not sure how this can impact the network if high volumes of invalid transactions are broadcasted to the network. Also, Syscoin waits 10 seconds for a transaction to arrive before checking its validity. It would be nice if they could provide some more quantitive arguments to back up this "10 seconds rule". In short, I feel that the Syscoin network should be stress-tested a bit more to really figure out how well their protocol works. Let's hope for the best! Conclusion DAG technology has shown some great potential in many projects like Nano, Byteball, and now Syscoin. It mostly allows for a higher transaction throughput than a regular blockchain project. In short about Syscoin, it holds some innovative technical approaches to increase their transaction throughput. The most interesting one is the parallel signature validation. Let’s see how this innovative approach entangles itself in the future.

Entangling Z-DAG Technology with SysCoin

PrivateAI Closes Strategic Round, Commences PGPT Trading On Public Markets, And Launches AI Crowdsourcing Platform To Make Breakthrough Life Extension Discoveries PRIVATEAI (PRIVATEAI.COM), a decentralized AI protocol co-founded by the serial entrepreneur and Forbes 30 under 30 Global Angel Versetti and led by the former executives of Fantom, Filecoin, Dogecoin and Syscoin, announced successful raise of Strategic Round for its token PGPT, with lead investors including Charlie Hu of Bitlayer, DAO Maker, Gains Associates, Dextools Ventures, Connectico Capital, DOGE.ORG, Stone Block Association, 32 Ventures, Lunar Digital Assets, Pinnacle VC, Samara Asset Group, Snova Capital, Meezan Ventures. Immediately after closing the round, PrivateAI’s native token PGPT was launched on the centralized cryptocurrency exchange Bitget, where it debuted with a 500% daily gain in the first 24 hours of trading. PrivateAI has also unveiled its AI-native distributed data platform that intends to build the world’s first domain-specific Large Language Model (LLM) for the longevity industry. Powered by the unique architecture of knowledge graphs that process and structure scientific and research data into logic and framework suitable for the machine learning industry, PrivateAI creates monetization opportunities and liquid markets for owners and producers of longevity-related datasets by rewarding them with its liquid and tradeable cryptocurrency PGPT. For companies building their own Generative AI, Large Language Models, and AI-powered data analytics, PrivateAI offers access to unique data from the collective scientific hive-mind and incubation services where a mix of capital and AI tech is employed to accelerate promising early-stage scientific projects. The ultimate goal of PrivateAI is to enable breakthrough discoveries in life extension, also known as longevity. Knowledge Graphs give AI-powered systems the ability to understand the wider context of the data that is fed to the machines, enabling AI systems to develop critical thinking, context awareness, and semantic analysis. Importantly, knowledge graphs become living, perpetually updated, and expanded entities as a crowdsourcing community of scientists, researchers, and data providers expand the knowledge. The platform thus becomes the backend for such areas of longevity as AI-based drug discovery, personalized medicine, genomic research, and deep analysis of aging processes. The ultimate dream of Angel Versetti is to harness the collective scientific knowledge and research to enable people to live longer or even forever, which will be essential for humanity if it hopes to travel beyond the Solar system and colonize other planets. “PrivateAI’s 60x oversubscribed public round followed by a 500% growth of PGPT on the first day of trading indicates there is a massive appetite for the more meaningful, transhumanistic applications of AI that help radically advance science. We are proud to pioneer use cases that others deemed to be impossible.” – said Angel Versetti after the launch. PrivateAI is building collaborations with leading longevity-focused scientific research communities worldwide, having started discussions with the research communities at Oxford University, where Angel Versetti studied for an MSc in Evidence-Based Healthcare. PrivateAI also built partnerships with Lifespan.io and Aging Research Drug Discovery (ARDD) scientific consortia focused on longevity. Angel Versetti a@privateai.com CC admin@privateai.com is available for further interviews. PrivateAI Closes Strategic Round, Commences PGPT Trading On Public Markets, And Launches AI Crowdsourcing Platform To Make Breakthrough Life Extension Discoveries PrivateAI Closes Strategic Round, Commences PGPT Trading On Public Markets, And Launches AI Crowdsourcing Platform To Make Breakthrough Life Extension Discoveries PrivateAI Closes Strategic Round, Commences PGPT Trading On Public Markets, And Launches AI Crowdsourcing Platform To Make Breakthrough Life Extension Discoveries PrivateAI Closes Strategic Round, Commences PGPT Trading On Public Markets, And Launches AI Crowdsourcing Platform To Make Breakthrough Life Extension Discoveries PRIVATEAI (PRIVATEAI.COM), a decentralized AI protocol co-founded by the serial entrepreneur and Forbes 30 under 30 Global Angel Versetti and led by the former executives of Fantom, Filecoin, Dogecoin and Syscoin, announced successful raise of Strategic Round for its token PGPT, with lead investors including Charlie Hu of Bitlayer, DAO Maker, Gains Associates, Dextools Ventures, Connectico Capital, DOGE.ORG, Stone Block Association, 32 Ventures, Lunar Digital Assets, Pinnacle VC, Samara Asset Group, Snova Capital, Meezan Ventures. Immediately after closing the round, PrivateAI’s native token PGPT was launched on the centralized cryptocurrency exchange Bitget, where it debuted with a 500% daily gain in the first 24 hours of trading. serial entrepreneur serial entrepreneur Forbes 30 under 30 Global Forbes 30 under 30 Global daily gain in the first 24 hours of trading. daily gain in the first 24 hours of trading. PrivateAI has also unveiled its AI-native distributed data platform that intends to build the world’s first domain-specific Large Language Model (LLM) for the longevity industry. Powered by the unique architecture of knowledge graphs that process and structure scientific and research data into logic and framework suitable for the machine learning industry, PrivateAI creates monetization opportunities and liquid markets for owners and producers of longevity-related datasets by rewarding them with its liquid and tradeable cryptocurrency PGPT. For companies building their own Generative AI, Large Language Models, and AI-powered data analytics, PrivateAI offers access to unique data from the collective scientific hive-mind and incubation services where a mix of capital and AI tech is employed to accelerate promising early-stage scientific projects. The ultimate goal of PrivateAI is to enable breakthrough discoveries in life extension, also known as longevity. AI-native distributed data platform AI-native distributed data platform Knowledge Graphs give AI-powered systems the ability to understand the wider context of the data that is fed to the machines, enabling AI systems to develop critical thinking, context awareness, and semantic analysis. Importantly, knowledge graphs become living, perpetually updated, and expanded entities as a crowdsourcing community of scientists, researchers, and data providers expand the knowledge. The platform thus becomes the backend for such areas of longevity as AI-based drug discovery, personalized medicine, genomic research, and deep analysis of aging processes. The ultimate dream of Angel Versetti is to harness the collective scientific knowledge and research to enable people to live longer or even forever, which will be essential for humanity if it hopes to travel beyond the Solar system and colonize other planets. “PrivateAI’s 60x oversubscribed public round followed by a 500% growth of PGPT on the first day of trading indicates there is a massive appetite for the more meaningful, transhumanistic applications of AI that help radically advance science. We are proud to pioneer use cases that others deemed to be impossible.” – said Angel Versetti after the launch. PrivateAI is building collaborations with leading longevity-focused scientific research communities worldwide, having started discussions with the research communities at Oxford University, where Angel Versetti studied for an MSc in Evidence-Based Healthcare. PrivateAI also built partnerships with Lifespan.io and Aging Research Drug Discovery (ARDD) scientific consortia focused on longevity. Angel Versetti a@privateai.com CC admin@privateai.com is available for further interviews. a@privateai.com a@privateai.com admin@privateai.com admin@privateai.com

PGPT Token Now Public: PrivateAI Completes Funding Round

PGPT টোকেন এখন পাবলিক: PrivateAI ফান্ডিং রাউন্ড সম্পূর্ণ করেছে

PGPT-Token jetzt öffentlich: PrivateAI schließt Finanzierungsrunde ab

El token PGPT ahora es público: PrivateAI completa la ronda de financiación

Le jeton PGPT est désormais public : PrivateAI termine le cycle de financement

पीजीपीटी टोकन अब सार्वजनिक: प्राइवेटएआई ने फंडिंग राउंड पूरा किया

PGPTトークンが一般公開：PrivateAIが資金調達ラウンドを完了

PGPT 토큰 공개: PrivateAI, 자금 조달 라운드 완료

Token PGPT agora público: PrivateAI conclui rodada de financiamento

Токен PGPT теперь общедоступен: PrivateAI завершает раунд финансирования

PGPT Tokeni Artık Halka Açık: PrivateAI Finansman Turunu Tamamladı

Mã thông báo PGPT hiện đã được công khai: PrivateAI hoàn thành vòng cấp vốn

PGPT 代币现已公开：PrivateAI 完成融资

Author:
(1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Table of Links Abstract and Introduction
Dancing Links
The Rust Programming Language
RAC: Hardware/Software Co-Assurance at Scale
Rust and RAR
Dancing Links in Rust
Related Work
Conclusion, Acknowledgments, and References 8 Conclusion We have developed a prototype toolchain to allow the Rust programming language to be used as a hardware/software co-design and co-assurance language for critical systems, standing on the shoulders of Russinoff’s team at Arm, and all the great work they have done on Restricted Algorithmic C. We have demonstrated the ability to establish the correctness of several practical data structures commonly found in high-assurance systems (e.g., array-backed singly-linked lists, doubly-linked lists, stacks, and dequeues) through automated formal verification, enabled by automated source-to-source translation from Rust to RAC to ACL2, and have detailed the specification and verification of one such data structure, a circular doubly-linked list employing Knuth’s “Dancing Links” optimization. We have also successfully applied our toolchain to cryptography and data format filtering examples typical of the sorts of algorithms that one encounters in critical systems development. In future work, we will continue to develop our toolchain, increasing the number of Rust features that we can support in the RAR subset, as well as continuing to improve the ACL2 verification libraries in order to increase the ability to discharge RAR correctness proofs automatically. We will also continue to work with our colleagues at Kansas State University on the direct synthesis and verification of RAR code from architectural models, as well as working with colleagues at the University of Kansas on verified synthesis of Rust code from high-level attestation protocol specifications written using the Coq theorem prover. 9 Acknowledgments Many thanks to Donald Knuth for his detailed study of exact cover problems in general, and the “Dancing Links” optimization in particular, that can now be found in Volume 4B of his seminal series, The Art of Computer Programming. It was a pleasure discovering this particular corner of Computer Science, beginning when the author accidentally stumbled upon a previously recorded Knuth “Christmas Lecture” on the subject in late 2022. Previous foundational work on hardware/software co-assurance in Rust was funded by DARPA contract HR00111890001. The views, opinions and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. Many thanks to David Russinoff of Arm for developing and improving the RAC toolchain, without which most of the current work would not be possible. Thanks also go to the anonymous reviewers for their insightful comments. References [1] Ron Amadeo (2021): Google is now writing low-level Android code in Rust. Available at https://arstechnica.com/gadgets/2021/04/ google-is-now-writing-low-level-android-code-in-rust/. [2] Amazon Web Services (2022): Announcing the Kani Rust Verifier Project. Available at https://model-checking.github.io/kani-verifier-blog/2022/ 05/04/announcing-the-kani-rust-verifier-project.html?fbclid=IwAR2M_ B1IEBfkVhIXSuuAxt3McC_QpUnTuzDq9jG40HOaJzxw8z1Nw9XU_i4. [3] V. Astrauskas, A. B´ıl ´y, J. Fiala, Z. Grannan, C. Matheja, P. M ¨uller, F. Poli & A. J. Summers (2022): The Prusti Project: Formal Verification for Rust (invited). In: NASA Formal Methods (14th International Symposium), Springer, pp. 88–108, doi:10.1007/978-3-031-06773-0_5. Available at https://link.springer. com/chapter/10.1007/978-3-031-06773-0_5. [4] Robert S. Boyer & J Strother Moore (2002): Single-Threaded Objects in ACL2. In: Practical Aspects of Declarative Languages, 4th International Symposium, PADL 2002, Portland, OR, USA, January 19-20, 2002, Proceedings, LNCS 2257, Springer, pp. 9–27, doi:10.1007/3-540-45587-6_3. [5] Sally Browning & Philip Weaver (2010): Designing Tunable, Verifiable Cryptographic Hardware Using Cryptol. In David S. Hardin, editor: Design and Verification of Microprocessor Systems for High-Assurance Applications, Springer, pp. 89–143, doi:10.1007/978-1-4419-1539-9_4. [6] Thomas Claburn (2023): Microsoft is busy rewriting core Windows code in memory-safe Rust. Available at https://www.theregister.com/2023/04/27/microsoft_windows_rust/. [7] Darren Cofer, Isaac Amundson, Junaid Babar, David Hardin, Konrad Slind, Perry Alexander, John Hatcliff, Robby, Gerwin Klein, Corey Lewis, Eric Mercer & John Shackleton (2022): Cyber Assured Systems Engineering at Scale. In: IEEE Security & Privacy, pp. 52–64, doi:10.1109/MSEC.2022.3151733. [8] Xavier Denis (2022): Creusot. Available at https://github.com/xldenis/creusot. [9] Peter H. Feiler & David P. Gluch (2012): Model-Based Engineering with AADL: An Introduction to the SAE Architecture Analysis & Design Language, 1st edition. Addison-Wesley Professional. [10] David S. Hardin (2020): Put Me on the RAC. In: Proceedings of the Sixteenth International Workshop on the ACL2 Theorem Prover and its Applications (ACL2-20), pp. 142–145, doi:10.4204/eptcs.327.13. [11] David S. Hardin (2020): Verified Hardware/Software Co-Assurance: Enhancing Safety and Security for Critical Systems. In: Proceedings of the 2020 IEEE Systems Conference, doi:10.1109/SysCon47679. 2020.9381831. [12] David S. Hardin (2022): Hardware/Software Co-Assurance for the Rust Programming Language Applied to Zero-Trust Architecture Development. ACM SIGAda Ada Letters 42(2), pp. 55–61, doi:10.1145/3591335. 3591340. [13] David S. Hardin (2022): Hardware/Software Co-Assurance using the Rust Programming Language and ACL2. In: Proceedings of the Seventeenth International Workshop on the ACL2 Theorem Prover and its Applications (ACL2-22), pp. 202–216, doi:10.4204/EPTCS.359.16. [14] David S. Hardin & Konrad L. Slind (2021): Formal Synthesis of Filter Components for Use in SecurityEnhancing Architectural Transformations. In: Proceedings of the Seventh Workshop on Language-Theoretic Security, 42nd IEEE Symposium and Workshops on Security and Privacy (LangSec 2021), doi:10.1109/ SPW53761.2021.00024. [15] Jane Street Group, LLC (2023): Hardcaml: An OCaml library for designing and testing hardware designs. Available at https://github.com/janestreet/hardcaml. [16] Steve Klabnik & Carol Nichols (2018): The Rust Programming Language. No Starch Press. [17] Donald E. Knuth (2022): The Art of Computer Programming. 4B: Combinatorial Algorithms, Part 2, Addison-Wesley. [18] Ramana Kumar, Magnus O. Myreen, Michael Norrish & Scott Owens (2014): CakeML: a verified implementation of ML. In Suresh Jagannathan & Peter Sewell, editors: The 41st Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL ’14, San Diego, CA, USA, January 20-21, 2014, ACM, pp. 179–192, doi:10.1145/2535838.2535841. [19] Andrea Lattuada, Travis Hance, Chanhee Cho, Matthias Brun, Isitha Subasinghe, Yi Zhou, Jon Howell, Bryan Parno & Chris Hawblitzel (2023): Verus: Verifying Rust Programs Using Linear Ghost Types. Proc. ACM Program. Lang. 7(OOPSLA1), doi:10.1145/3586037. [20] Yusuke Matsushita, Takeshi Tsukada & Naoki Kobayashi (2021): RustHorn: CHC-Based Verification for Rust Programs. ACM Trans. Program. Lang. Syst. 43(4), doi:10.1145/3462205. [21] Mentor Graphics Corporation (2016): Algorithmic C (AC) Datatypes. Available at https://www.mentor. com/hls-lp/downloads/ac-datatypes. [22] Mentor Graphics Corporation (2020): Catapult High-Level Synthesis. Available at https://www.mentor. com/hls-lp/catapult-high-level-synthesis/. [23] Eric Mercer, Konrad Slind, Isaac Amundson, Darren Cofer, Junaid Babar & David Hardin (2023): Synthesizing Verified Components for Cyber Assured Systems Engineering. In: Software and Systems Modeling, 22, pp. 1451–1471, doi:10.1007/s10270-023-01096-3. [24] Matt Miller (2019): A proactive approach to more secure code. Available at https://msrc-blog. microsoft.com/2019/07/16/a-proactive-approach-to-more-secure-code/. [25] Shane Miller & Carl Lerche (2022): Sustainability with Rust. Available at https://aws.amazon.com/ blogs/opensource/sustainability-with-rust/. [26] Razvan Nane, Vlad-Mihai Sima, Christian Pilato, Jongsok Choi, Blair Fort, Andrew Canis, Yu Ting Chen, Hsuan Hsiao, Stephen Brown, Fabrizio Ferrandi, Jason Anderson & Koen Bertels (2016): A Survey and Evaluation of FPGA High-Level Synthesis Tools. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35(10), pp. 1591–1604, doi:10.1109/TCAD.2015.2513673. [27] David M. Russinoff (2022): Formal Verification of Floating-Point Hardware Design: A Mathematical Approach, second edition. Springer, doi:10.1007/978-3-030-87181-9. [28] Geoffry Song (2020): plex: a parser and lexer generator as a Rust procedural macro. Available at https:// github.com/goffrie/plex. [29] Jeff Vander Stoep & Stephen Hines (2021): Rust in the Android platform. Available at https://security. googleblog.com/2021/04/rust-in-android-platform.html. [30] Loup Vaillant (2022): Monocypher: Boring Crypto that Simply Works. Available at https://monocypher. org. [31] Xilinx, Inc. (2018): Vivado Design Suite User Guide: High-Level Synthesis. Available at https://www.xilinx.com/support/documentation/sw_manuals/xilinx2018_3/ ug902-vivado-high-level-synthesis.pdf. This paper is available on arxiv under CC 4.0 license. Author: (1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Author: Author: (1) David S. Hardin, Cedar Rapids, IA USA david.s.hardin@gmail.com. Table of Links Abstract and Introduction Dancing Links The Rust Programming Language RAC: Hardware/Software Co-Assurance at Scale Rust and RAR Dancing Links in Rust Related Work Conclusion, Acknowledgments, and References Abstract and Introduction Abstract and Introduction Dancing Links Dancing Links The Rust Programming Language The Rust Programming Language RAC: Hardware/Software Co-Assurance at Scale RAC: Hardware/Software Co-Assurance at Scale Rust and RAR Rust and RAR Dancing Links in Rust Dancing Links in Rust Related Work Related Work Conclusion, Acknowledgments, and References Conclusion, Acknowledgments, and References 8 Conclusion We have developed a prototype toolchain to allow the Rust programming language to be used as a hardware/software co-design and co-assurance language for critical systems, standing on the shoulders of Russinoff’s team at Arm, and all the great work they have done on Restricted Algorithmic C. We have demonstrated the ability to establish the correctness of several practical data structures commonly found in high-assurance systems (e.g., array-backed singly-linked lists, doubly-linked lists, stacks, and dequeues) through automated formal verification, enabled by automated source-to-source translation from Rust to RAC to ACL2, and have detailed the specification and verification of one such data structure, a circular doubly-linked list employing Knuth’s “Dancing Links” optimization. We have also successfully applied our toolchain to cryptography and data format filtering examples typical of the sorts of algorithms that one encounters in critical systems development. In future work, we will continue to develop our toolchain, increasing the number of Rust features that we can support in the RAR subset, as well as continuing to improve the ACL2 verification libraries in order to increase the ability to discharge RAR correctness proofs automatically. We will also continue to work with our colleagues at Kansas State University on the direct synthesis and verification of RAR code from architectural models, as well as working with colleagues at the University of Kansas on verified synthesis of Rust code from high-level attestation protocol specifications written using the Coq theorem prover. 9 Acknowledgments Many thanks to Donald Knuth for his detailed study of exact cover problems in general, and the “Dancing Links” optimization in particular, that can now be found in Volume 4B of his seminal series, The Art of Computer Programming. It was a pleasure discovering this particular corner of Computer Science, beginning when the author accidentally stumbled upon a previously recorded Knuth “Christmas Lecture” on the subject in late 2022. Previous foundational work on hardware/software co-assurance in Rust was funded by DARPA contract HR00111890001. The views, opinions and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. Many thanks to David Russinoff of Arm for developing and improving the RAC toolchain, without which most of the current work would not be possible. Thanks also go to the anonymous reviewers for their insightful comments. References [1] Ron Amadeo (2021): Google is now writing low-level Android code in Rust. Available at https://arstechnica.com/gadgets/2021/04/ google-is-now-writing-low-level-android-code-in-rust/. [2] Amazon Web Services (2022): Announcing the Kani Rust Verifier Project. Available at https://model-checking.github.io/kani-verifier-blog/2022/ 05/04/announcing-the-kani-rust-verifier-project.html?fbclid=IwAR2M_ B1IEBfkVhIXSuuAxt3McC_QpUnTuzDq9jG40HOaJzxw8z1Nw9XU_i4. [3] V. Astrauskas, A. B´ıl ´y, J. Fiala, Z. Grannan, C. Matheja, P. M ¨uller, F. Poli & A. J. Summers (2022): The Prusti Project: Formal Verification for Rust (invited). In: NASA Formal Methods (14th International Symposium), Springer, pp. 88–108, doi:10.1007/978-3-031-06773-0_5. Available at https://link.springer. com/chapter/10.1007/978-3-031-06773-0_5. [4] Robert S. Boyer & J Strother Moore (2002): Single-Threaded Objects in ACL2. In: Practical Aspects of Declarative Languages, 4th International Symposium, PADL 2002, Portland, OR, USA, January 19-20, 2002, Proceedings, LNCS 2257, Springer, pp. 9–27, doi:10.1007/3-540-45587-6_3. [5] Sally Browning & Philip Weaver (2010): Designing Tunable, Verifiable Cryptographic Hardware Using Cryptol. In David S. Hardin, editor: Design and Verification of Microprocessor Systems for High-Assurance Applications, Springer, pp. 89–143, doi:10.1007/978-1-4419-1539-9_4. [6] Thomas Claburn (2023): Microsoft is busy rewriting core Windows code in memory-safe Rust. Available at https://www.theregister.com/2023/04/27/microsoft_windows_rust/. [7] Darren Cofer, Isaac Amundson, Junaid Babar, David Hardin, Konrad Slind, Perry Alexander, John Hatcliff, Robby, Gerwin Klein, Corey Lewis, Eric Mercer & John Shackleton (2022): Cyber Assured Systems Engineering at Scale. In: IEEE Security & Privacy, pp. 52–64, doi:10.1109/MSEC.2022.3151733. [8] Xavier Denis (2022): Creusot. Available at https://github.com/xldenis/creusot. [9] Peter H. Feiler & David P. Gluch (2012): Model-Based Engineering with AADL: An Introduction to the SAE Architecture Analysis & Design Language, 1st edition. Addison-Wesley Professional. [10] David S. Hardin (2020): Put Me on the RAC. In: Proceedings of the Sixteenth International Workshop on the ACL2 Theorem Prover and its Applications (ACL2-20), pp. 142–145, doi:10.4204/eptcs.327.13. [11] David S. Hardin (2020): Verified Hardware/Software Co-Assurance: Enhancing Safety and Security for Critical Systems. In: Proceedings of the 2020 IEEE Systems Conference, doi:10.1109/SysCon47679. 2020.9381831. [12] David S. Hardin (2022): Hardware/Software Co-Assurance for the Rust Programming Language Applied to Zero-Trust Architecture Development. ACM SIGAda Ada Letters 42(2), pp. 55–61, doi:10.1145/3591335. 3591340. [13] David S. Hardin (2022): Hardware/Software Co-Assurance using the Rust Programming Language and ACL2. In: Proceedings of the Seventeenth International Workshop on the ACL2 Theorem Prover and its Applications (ACL2-22), pp. 202–216, doi:10.4204/EPTCS.359.16. [14] David S. Hardin & Konrad L. Slind (2021): Formal Synthesis of Filter Components for Use in SecurityEnhancing Architectural Transformations. In: Proceedings of the Seventh Workshop on Language-Theoretic Security, 42nd IEEE Symposium and Workshops on Security and Privacy (LangSec 2021), doi:10.1109/ SPW53761.2021.00024. [15] Jane Street Group, LLC (2023): Hardcaml: An OCaml library for designing and testing hardware designs. Available at https://github.com/janestreet/hardcaml. [16] Steve Klabnik & Carol Nichols (2018): The Rust Programming Language. No Starch Press. [17] Donald E. Knuth (2022): The Art of Computer Programming. 4B: Combinatorial Algorithms, Part 2, Addison-Wesley. [18] Ramana Kumar, Magnus O. Myreen, Michael Norrish & Scott Owens (2014): CakeML: a verified implementation of ML. In Suresh Jagannathan & Peter Sewell, editors: The 41st Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL ’14, San Diego, CA, USA, January 20-21, 2014, ACM, pp. 179–192, doi:10.1145/2535838.2535841. [19] Andrea Lattuada, Travis Hance, Chanhee Cho, Matthias Brun, Isitha Subasinghe, Yi Zhou, Jon Howell, Bryan Parno & Chris Hawblitzel (2023): Verus: Verifying Rust Programs Using Linear Ghost Types. Proc. ACM Program. Lang. 7(OOPSLA1), doi:10.1145/3586037. [20] Yusuke Matsushita, Takeshi Tsukada & Naoki Kobayashi (2021): RustHorn: CHC-Based Verification for Rust Programs. ACM Trans. Program. Lang. Syst. 43(4), doi:10.1145/3462205. [21] Mentor Graphics Corporation (2016): Algorithmic C (AC) Datatypes. Available at https://www.mentor. com/hls-lp/downloads/ac-datatypes. [22] Mentor Graphics Corporation (2020): Catapult High-Level Synthesis. Available at https://www.mentor. com/hls-lp/catapult-high-level-synthesis/. [23] Eric Mercer, Konrad Slind, Isaac Amundson, Darren Cofer, Junaid Babar & David Hardin (2023): Synthesizing Verified Components for Cyber Assured Systems Engineering. In: Software and Systems Modeling, 22, pp. 1451–1471, doi:10.1007/s10270-023-01096-3. [24] Matt Miller (2019): A proactive approach to more secure code. Available at https://msrc-blog. microsoft.com/2019/07/16/a-proactive-approach-to-more-secure-code/. [25] Shane Miller & Carl Lerche (2022): Sustainability with Rust. Available at https://aws.amazon.com/ blogs/opensource/sustainability-with-rust/. [26] Razvan Nane, Vlad-Mihai Sima, Christian Pilato, Jongsok Choi, Blair Fort, Andrew Canis, Yu Ting Chen, Hsuan Hsiao, Stephen Brown, Fabrizio Ferrandi, Jason Anderson & Koen Bertels (2016): A Survey and Evaluation of FPGA High-Level Synthesis Tools. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 35(10), pp. 1591–1604, doi:10.1109/TCAD.2015.2513673. [27] David M. Russinoff (2022): Formal Verification of Floating-Point Hardware Design: A Mathematical Approach, second edition. Springer, doi:10.1007/978-3-030-87181-9. [28] Geoffry Song (2020): plex: a parser and lexer generator as a Rust procedural macro. Available at https:// github.com/goffrie/plex. [29] Jeff Vander Stoep & Stephen Hines (2021): Rust in the Android platform. Available at https://security. googleblog.com/2021/04/rust-in-android-platform.html. [30] Loup Vaillant (2022): Monocypher: Boring Crypto that Simply Works. Available at https://monocypher. org. [31] Xilinx, Inc. (2018): Vivado Design Suite User Guide: High-Level Synthesis. Available at https://www.xilinx.com/support/documentation/sw_manuals/xilinx2018_3/ ug902-vivado-high-level-synthesis.pdf. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Rust Implementation of Knuth's Dancing Links: Conclusion, Acknowledgments, and References

101 Stories To Learn About Binance

Let's learn about via these 59 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Zero Knowledge Proofs /Learn Repo 1. Layer 2 Rollups Projects in 2021: A Comparison Ethereum layer 2 is a collection of solutions that are specifically designed to scale applications by handling transactions off the Ethereum Mainnet, Layer 1. 2. KZG10, IPA, FRI, and DARKS: Analysis Of Polynomial Commitment Schemes Among all popular polynomial commitment schemes, KZG is the best scheme in terms of succinctness but triggers security concerns. 3. Understanding the Zero-Knowledge Proof Method One of the biggest advantages of blockchain technology is the degree of information transparency it offers. 4. zKPs OR Zero-Knowledge Proofs: The Tiny Privacy Algorithm Behind Super Lightweight Blockchains Distributed public networks face a trilemma: digital transactions must provide privacy while meeting compliance requirements in a trustless environment. 5. Zero-Knowledge Proof Algorithm, PLONK—Protocol: Sin7Y Tech Review (17) In this report, Sin7Y will analyze the details of the PLONK protocol and elaborate on how the constraint relationship of the gate is valid. 6. Zero-Knowledge Proof Algorithm: ZK-Stark-FRI Protocol We reach the conclusion of the series “Understanding the value of a zero-knowledge proof algorithm - Zk-stark". 7. Lowering the Barrier of Entry to Zero Knowledge Proofs Next Generation Semiconductors: Designing accelerators for advanced cryptography 8. AppliedZKP zkEVM Circuit Code: A Guide This text aims to provide an easy guide to the basic framework and logic of the AppliedZKP zkEVM code base. 9. How to Create an Anonymous Voting System on the Blockchain Using Zero-Knowledge Proofs How to create an anonymous voting system on the blockchain using zero-knowledge proofs 10. True Privacy is When Users Decide Who Sees and Uses Their Data: Unhased #24 Unhashed is a QnA series where I speak with top execs of new and established blockchain projects to unravel the mystery of blockchain & crypto. 11. The Leo Programming Language Will Make Waves in Web3 Aleo is building a brand new programming language, Leo, which is used to build private web3 applications. 12. The Magic of Zero-Knowledge Proofs through the Source Code of Tornado Cash Understanding Zero-Knowledge Proofs through the source code of Tornado Cash 13. Why SNARKs Are the Technology of the Coming Decade Welcome to the SNARK Age, a pop-up newsletter exploring and celebrating a technology that we believe will have fundamental and deterministic impacts on privacy, computing, cryptography, and money in the years to come. We’ll be sharing (mostly) bite-sized issues highlighting the key events, milestones and people in the space. 14. JavaScript tutorial for Zero-Knowledge Proofs Using SnarkJS and Circom In this article, I will show you how you can use zk-SNARK in your JavaScript project by using circom and snarkjs. 15. "Defi & Traditional Finance Aren't Much Different, But Defi Requires Lesser Trust" - Alex Lee This interview discusses zero-knowledge proof and the use of ZKs for establishing trust in a blockchain system. 16. TinyRAM Review: Architecture, Design, and Assembly Instructions TinyRAM can be used to perform non-deterministic computations easily and plays an important role in zero-knowledge-proof systems. 17. Zero-Knowledge Proofs: The Simplest Explanation on the Internet history, concepts, principles, technical implementation, and development status of zero-knowledge proofs in the simplest language ever 18. Understanding Zero-Knowledge Proofs: Privacy is Freedom The metaverse will likely be a disaster for user privacy unless that is solved unless that privacy is solved. 19. How we can Better Understand PLONK Permutations over Lagrange-bases for Oecumenical Noninteractive arguments of Knowledge, or PLONKS are a new general-purpose zer-knowledge proof scheme. 20. A Refresher on Zero Knowledge Proof Systems and A New Contender Before we give our hero the undivided attention it deserves, let us try and explain zero-knowledge proof in one sentence. Zero-knowledge proofs allow you to prove that you know a ‘secret’, without actually telling and revealing the secret to the other. 21. How Are zk-SNARKs Possible? Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs. 22. How Private Are Your Blockchain Transactions? Multiple projects have been working on various blockchain scaling solutions, such as Sharding and Plasma offer greater scalability and Privacy. 23. Using Cloud-ZK for Developing ZKP Acceleration in the Cloud Cloud-ZK: A Toolkit for developing ZKP acceleration in the cloud 24. An Intro to Zero-Knowledge Proofs (ZKP) and Identity Learn about Zero Knowledge claims and how they can help in securing your Identity. 25. ZKPs or Zero Knowledge Proofs Are Evolving Blockchains [Explained in non-technical terms] ZKP can be used for much more than just privacy. ZKPs are so versatile that it may redefine how blockchains work. 26. Fflonk - A New Plonk Protocol: Sin7Y Tech Review (13) Through careful research, we found that a simple transformation can improve the performance of Verify significantly. 27. Elusiv Raises $3.5 million in Seed Funding Round Co-led by LongHash Ventures to Build Web3 Privacy Elusiv, a privacy protocol that is Zero-Knowledge based and compliant, has raised $3.5 million in a seed investment round 28. Is Data Monetization Dead? The advent of cryptocurrency and web3 has led to investigations and experiments into what ways could a total decentralized digital society manifest. 29. Understanding the Sinsemilla Hash Function in OlaVM Read on to know the Security Properties of a Cryptographic Hash Function, Random Oracle, and the Sinsemilla Hash Function. 30. On Zero-Knowledge Proofs And Why They Matter There is a lot of enthusiasm for the application of zero-knowledge proof systems, at Dusk Network we’ve developed the open-source PLONK zero-knowledge proof system. It can be used for many things, and what better way to demonstrate its potential with an example! 31. 🟧 un.Block #39: Design of Cross-chain Bridges; Let's Go Snail Trail! In the last year, cross-chain bridges have been one of the hottest theses. 32. zk-SNARK Concepts Explained In Different Levels of Complexity I’ve decided to write an ELI15 for zk-SNARK jargon since I’ve yet to come across something similar during my studies. 33. Zerocoin Flaws, Private Atomic Swap Adoption, and UX [An Analysis] We started as a PoW coin however soon realised for the sake of security (namely preventing 51% attacks and ASIC miners), we'd be better suited to having a Proof-of-Stake consensus mechanism. So we moved over from mining to staking without a hitch and took advantage of this new setup by developing our own 'Leased Proof-of-Stake' mechanism, which allows users to stake their coins via a service provider who take a small percentage from each staking reward for running the service. 34. How to Design the ZKVM Circuit We will not perform the field division operation at the circuit level, instead, we will make it by verifying the following logical relationship. 35. The Power of Zero-Knowledge Proofs - Exploring the New ConsenSys zkEVM See how ConsenSys zk-rollups are evolving at a rapid pace and leading the way in helping Ethereum to scale to new levels. 36. Zero-Knowledge Proof Algorithm, PLONK —Circuit: Sin7Y Tech Review (16) We recently investigated the Zero-Knowledge proof algorithm-PLONK. Read on to know our learning experience. 37. Using Zero-Knowledge Proofs to Prove Legal Fishing Ranges with Fluree [A Step by Step Guide] It’s a rainy Sunday afternoon, and my friend, Alice, and I are playing “Where’s Waldo.”* This page is a particularly challenging one, and we’ve been looking for nearly twenty minutes.  I’m about ready to give up, when- finally- I spot Waldo, and I yell out, “I got him!” 38. Zero-Knowledge Proofs: An Intersection of Data Verification and Privacy Dive into the world of zero-knowledge proofs & learn about the challenges and opportunities that will arise by combining them with oracles. 39. How to Use Zero Knowledge Dapp Boilerplate Learn how to build zero knowledge dapps, using zero knowledge proofs boilerplate. Build age verification dapp using zero knowledge proofs. 40. ZoKrates - zkSNARKs On Ethereum (made easy) ZkSNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) or sometimes called "black magic" by some developers are generally considered hard to get into. 41. In Search For Future Crypto Trends Future trends in crypto might revolve around metaverse and NFT, Zero Knowledge proofs, evolution of DeFi, growth of Social Identity importance, and Multi-Chain. 42. What is Zero-Knowledge Proof ? Let’s explain exactly what that term means in one sentence: 43. ZK-Rollups are the Most Promising Way for the Blockchain Industry to Scale Smart Contracts Jagdeep Sidhu is the lead core developer of Syscoin and CTO of the publicly-traded company, Blockchain Foundry Inc who talks with us on ZK Roll ups. 44. How I Built an Anonymous Voting System on the Ethereum Blockchain Using Zero-Knowledge Proof How I built an anonymous voting system on the Ethereum blockchain using zero-knowledge proof 45. Enforcing Scalability and Data Integrity on Blockchain with Zero-Knowledge Proof Layer 2 and sidechain protocols have deployed the use of zero-knowledge proof to perform batch transfer processing rolled into a single off-chain transaction. 46. Why You Need To Add A Dash of Zero-Knowledge Proof to Your Projects Advanced technologies such as zero-knowledge proof systems require extensive knowledge from developers, making it difficult for businesses to adopt. Without a deep understanding of the underlying cryptographic logic, it is quite frankly impossible to implement correctly. 47. Trade it Like it is HOT: A Review of Popular ZK Projects and the Zero-Knowledge Proof Technology Privacy has always been regarded as one of the most valuable features in the cryptocurrency community. 48. ZK Rollup: The Most Preferred Ethereum Layer 2 Scaling Solution In this article, I explained the Ethereum zkrollup for beginners.and I started with discussing rollup before zkrollup and Optimistic rollup. 49. "Privacy and Zero-Knowledge Proof Are Going To Be Critical for A Free Society" - Kieran Mesquita This article talks about zero-knowledge proof and how zero-knowledge proofs work establishing trust with technology. 50. HashKey Capital's Deng Chao Talks About Market Developments and the Future of Web3 in 2023 Deng Chao, a representative of HashKey Group, a blockchain-focused investment firm, discusses the market developments in the web3 space in 2022. 51. Building an AI On-Chain Modulus Labs is a Web3 project that aims to bring AI capabilities to the blockchain in a decentralized manner, enabling creators to own and control their models 52. Exploring Popular zkEVM Solutions:  AppliedZKP, Matter Labs, Hermez, and Sin7Y zkEVM is said to be the crown jewel of Ethereum scaling schemes. Our 5th article compares and contrasts popular zkEVM solutions and proposes several questions. 53. Developing a Stable Coins Architecture on the ALEO Blockchain In this work we not only propose a mechanism of a stable coin, but a monetary system of two interconnected coins within a ALEO blockchain. 54. Zero Knowledge Proof: Explain it Like I’m 5 (Halloween Edition) Explaining crypto is hard, explaining crypto in simple words is harder. Explaining Zero Knowledge Proof to a child? Easy! So here you go — ZKP explained with some Halloween candy. 55. Zero-Knowledge Proofs: Adventures in the Dark Forest An RTS game on Ethereum… WHAT?! That's possible?! That’s exactly what the Dark Forest, an innovative blockchain game named after Liu Cixin’s eponymous second novel of the Remembrance of Earth’s Past trilogy, is. In fact, it is the first real-time strategy game running on Ethereum in existence. 56. Going Deep into the Specification for Marlin Read on to know about zero-knowledge proof algorithm Marlin which is a R1CS based proof system. 57. Privacy Scales Better: Understanding Zcash, Zero Knowledge Proofs (zKP) & Electric Coin Company innovations at the ECC show not only  that Privacy and Scalability are correlated but also that Governance and Development is more fruitful when rewarded. 58. ZK Rollups in 2023: From SNARK to STARK and Beyond ZK rollups are capturing the attention of the industry. Will they be the future of rollups? Are they good investments? Read this complete guide and research. 59. 20 Future Technologies That Will Change the World by 2050 I recently shared an article called “The “Next Big Thing” in Technology : 20 Inventions That Will Change the World”, which got a few dozen thousand hits in the past couple of weeks. This calls for a sequel. The previous 20 technologies were specifically centered on the next 20 years of technology development; but there’s a lot more to unravel when looking beyond the near future, though certainty obviously decreases with time. Thank you for checking out the 59 most read stories about Zero Knowledge Proofs on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

59 Stories To Learn About Zero Knowledge Proofs

287 Stories To Learn About Blockchain Development

122 Stories To Learn About Cybercrime

Blockchain aims to take transaction transparency to a whole new level with self-executing contracts. As technology progresses, the number of B2B cross-border transactions on the blockchain will reach by 2025. With such emphasis on this blockchain network, authorities must assess risk and develop guidelines for its fair use. 745 million Businesses and legal authorities use blockchain analytic tools to cluster and regulate the information on distributed ledgers. The difference between how each tool works lies in data attribution, i.e., the back-end data processing associated with distinct blockchain elements such as addresses, entities, and transactions. This article will evaluate each analytic tool with a primary focus on the capabilities and data attribution. blockchain Blockchain Analytic Tools - Why are they Important? Blockchain analytic tools streamline the process of categorizing the necessary information across the blockchain network. These solutions use AI and clustering algorithms to refine the data and help businesses and regulatory bodies assess risk, detect fraud, and understand transactions. From the cryptocurrency space to dApp development, these tools play a pivotal role. As businesses adopt blockchain, addressing security and compliance concerns is essential. like documentation, governance, access, and privacy arise with the utilization of this technology. Blockchain analytic tools provide a comprehensive overview of the information on the distributed ledger, highlighting the context of transactions and exposure to risks. Issues The Big Names in Blockchain Analytics When it comes to analyzing blockchain networks, these are the four key players in the industry:\ Chainalysis TRM Labs Blockchain Intelligence Group CipherTrace All these SaaS platforms offer complete analysis tools such as security, compliance, crypto, and fraud detection. For Know Your Transaction (KYT) solutions, organizations choose the right tools specific to their domain, pricing, and data attribution capabilities. These tools provide Application Programming Interface (API) access to incorporate the solution, allowing a seamless and swift transaction analysis. When paired with AI, these tools process data at excellent speeds. The Pros and Cons - A Comparison Chainalysis Many elements differentiate Chainalysis from its competitors, starting with how it processes data. Chainalysis uses clustering algorithms to refine information on the blockchain. It has monitored over $10 trillion worth of transactions in 2023, as mentioned on the website. Pros: Extensive documentation with webinars Offers both In-Premises and SaaS platform solutions Provides 24/7 live support to its clients worldwide Integrates into various cryptocurrency platforms such as Kassio, Macrobank, and SCRYPT Digital Extensive audience covering businesses, investigators, compliance experts, financial institutions, and cryptocurrency trading firms Cons: No Free/Trial version is available for users. For novice analysts, the learning curve might be rather severe Charges fee for every additional hour of customer support TRM Labs TRM Labs offers Know Your VASP (Virtual Asset Service Provider) as the leading solution. It helps businesses identify the risk profiles with on-chain activity analysis across different blockchains. Better capability to integrate with new blockchains/cover new assets is the differentiating factor of TRM Labs in the industry. Pros: Higher security with cross-chain tracing capability Dynamic and configurable risk scoring for transactions Integrates directly with Bitcoin and Ethereum networks Extensive training and support for customers User-centric design is intuitive and easy to navigate Cons: No Free/Trial version is available for users. Limited category coverage across blockchain, m\ore niche-specific. CipherTrace Acquired by Mastercard in 2021, CipherTrace works on cryptocurrency risk and fraud inspection. AML and travel rule compliance using blockchain autofill solutions differentiate it. With a strong reputation after the acquisition, it is considered the platform for extensive cryptocurrency coverage, including privacy-focused coins. Pros: Offers the most extensive category coverage across blockchain analytic tools Provides blockchain search and autofill for quick and easy investigation of cryptocurrency transactions, IDs, and addresses. Offers a localized and mobile-friendly interface Integrates case management solution to replay blockchain searches into new files Cons: No Free/Trial version is available for users. No API access to all services Limited integrations to digital asset platforms Blockchain Intelligence Group Blockchain intelligence offers different analytic tools that help organizations monitor transactions with end-to-end data processing. Designed by a US government investigator to provide comprehensive insights into risk management with a privacy-first approach. Pros: Law enforcement trusted platform with legal cases won using blockchain evidence Supports Multi-currency assessment and addresses risk assessment The only solution to support Syscoin, future-proof payments, tokens, and Asset transfers Allows users to customize transaction monitoring to their specific needs with API Free customer support with no hour limitation Cons: No Free/Trial version is available for users. Built for government and law enforcement agencies, niche-specific. The Role of Data Attribution Data attribution is what differentiates each blockchain analytic tool. It is the way each software system processes data available on the blockchain network. Since the distributed ledger system promotes transparency, businesses still need to refine each data point to make intelligent financial decisions. Chainalysis is among the most versatile industry solutions with its wide range of offerings and industry use cases. TRM Labs and CipherTrace are more powerful tools with comprehensive insights into transaction monitoring and compliance across the . Blockchain intelligence group is the first choice for legal authorities to assess risk and fraudulent attempts across digital channels. blockchain network Final Thoughts Blockchain analytic tools provide businesses and law enforcement agencies with a solid foundation to understand information on the distributed ledger. Chainalysis, TRM Labs, Blockchain Analysis Group, and CipherTrace are prominent names specializing in blockchain analytics and KYC crypto compliance solutions. All these solutions have pros and cons but can process blockchain data at significant speeds. The future of finance is blockchain, and these tools are here to help firms report and document transactions, assess risk, fraud detection and prevention, and understand their customers better.

Stories, News & Mentions about SYSCO

Sysco’s Stories on HackerNoon

Sysco's News & Mentions