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Aaron Judge hitting a 464-foot homer at Oracle Park wowed Giants broadcaster Mike Krukow

Aaron Judge made the Giants pay during his Oracle Park debut as San Francisco fell 6-2 to the New York Yankees on Friday.

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Yankees' Aaron Judge lives childhood dream with two HRs in Oracle Park debut

Childhood Giants fan Aaron Judge relished his return to &quot;special&quot; Oracle Park in San Francisco&#x27;s 6-2 loss to the New York Yankees on Friday.

Childhood Giants fan Judge relishes return to ‘special' Oracle Park - Yahoo Sports

Turns out, all Aaron Judge needed was a little bit of time to get going.

Aaron Judge closes out red-hot May with two-homer show at Oracle Park to take MLB's HR lead - CBSSports.com

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Oracle Corp. stock rises Friday, still underperforms market

Sign up for our weekly alerts emails - the easiest way to keep up to date · Oracle is making great progress at the VA. And they want EHR interoperability. Epic doesn’t. Take that, Business Insider! And Judy Faulkner! Ken Glueck, an EVP at Oracle, authored an Oracle blog post (or at least ...

Telehealth & Telecare Aware

In an alternative universe – one that may not have been far off from happening – the Yankees could have been visiting Aaron Judge in his home ballpark for the first time this weekend.

Aaron Judge 'definitely' envisioned alternate Giants reality before...

Oracle announces plans for two new cloud regions in Morocco, emphasizing growth opportunities in Africa.

What's Going On With Oracle Stock Thursday? - Oracle (NYSE:ORCL) - Benzinga

Goracle

goracle

2020 is credited as the year when DeFi took the world by storm. The lockdown, coupled with sky-high inflation, meant many people were quick to adopt this decentralized and transparent mode of finance. By the end of the year, NFTs, DeFi, and cryptocurrencies had become commonplace in almost every discussion. But is that all blockchains are capable of? With the rise of oracle networks that facilitate the transfer of real-world data on-chain, people are discovering that blockchain technology can be leveraged in several other industries like healthcare, supply chain management, insurance, and more. In the panel below, our speakers share their views on decentralized technologies and their impact beyond the financial sector. They also discuss the oracle problem and the advantages and disadvantages of decentralizing real-world industries with smart contracts and oracles. https://youtu.be/TWzNHuMbRS8?embedable=true Before diving into the panel discussion, here are some key concepts to note. Decentralizing Real World Industries Decentralization is a core concept that is closely linked to public blockchain technology. A decentralized system is one in which power and control are distributed across a network of participants, rather than being concentrated in the hands of a single central authority. Decentralization is achieved through the use of cryptographic algorithms that allow transactions to be verified and processed by the network as a whole, rather than relying on a single trusted third party. In the case of public blockchains, decentralization is achieved through the use of that ensure that all participants (nodes) agree on the state (balances & transactions) of the ledger. consensus algorithms Undoubtedly, many industries could potentially benefit from adopting decentralized blockchain technology, such as healthcare, supply chains, government, etc. However, in order to do so, there is a need for new sets of data not found on-chain. The technology that helps bridge real-world data with on-chain environments is called an oracle. Oracle networks like and provide a way for otherwise siloed blockchains to interact with off-chain data such as healthcare data and election reports and incorporate them into smart contracts. Tellor Goracle In the healthcare industry, for example, there are constant concerns about data privacy and sharing. The blockchain could create a safe medium to share medical data globally without revealing patients’ identities. It would also put the patient in control of who has access to that data. In addition, decentralization could impact this sector in drug supply tracing, counterfeit prevention, healthcare insurance, bill payments, and much more. Governmental elections could also benefit from the security of the blockchain. The transparency provided by the network ensures that data cannot be falsified, while immutability could mean an end to voter fraud. In addition, users retain their anonymity, and voting data obtained from oracles can be used in prediction markets. In order for this to work, however, a robust mechanism to ensure individuals’ identities on the blockchain needs to be developed in conjunction with governments and elected officials. Real estate, transportation, cyber-security, law enforcement … The list goes on and on. Moving real-world industries on-chain could bring the much-needed transparency and traceability that these sectors need. It also reduces the reliance on intermediaries. However, some on-chain networks have centralized aspects, and these issues must be addressed before blockchain adoption can become mainstream and truly beneficial in these real-world industries. The Oracle Problem in RWAs In order for a blockchain to be useful for real-world applications, it needs access to data from the outside world, such as stock prices, weather conditions, or shipping information. This means that the data they provide must be accurate and trustworthy. This is particularly challenging when dealing with RWAs. For example, if a smart contract is programmed to trigger a payment once a package arrives at its destination, the system would be vulnerable to corruption and manipulation. If the payment for a particular package (or group of packages) is high enough, bad actors would be incentivized to deceive the smart contract in order to manipulate the outcome. In this example, if the package’s arrival is recorded by a sensor or NFC, the sensors used would have to be as immutable as the blockchain itself, if not a centralized intermediary that can process refunds might be a desired step for end-users. This is an example of the oracle problem in blockchain, which refers to the challenge of connecting public blockchains with real-world data and events. Since blockchains operate in decentralized, trustless environments, they cannot rely on any single source of information. This creates a challenge known as the “oracle problem”: How can the blockchain securely and accurately access external data? If trust in oracles is required, are blockchains truly trustless? In an attempt to solve this problem, decentralized oracle networks allow multiple oracles to contribute data, with consensus mechanisms being used to aggregate the results and arrive at a single, agreed-upon value. This helps to improve the accuracy and reliability of the data being sent to the blockchain. There are three criteria for evaluating an oracle network. They are , and . Correctness refers to the authenticity of the data and how the oracle guarantees the information was from valid sources and was unaltered before being brought on-chain. The feature of an oracle that allows smart contracts to execute without delay is its data availability. Lastly, oracle networks must have methods for user accountability and rewards or penalties depending on the accuracy of provided data. correctness availability, incentive compatibility While there are many approaches to solving the oracle problem, no network is 100% perfect. When attempting to move real-world industries onto the blockchain, each sector must consider the trade-offs of different networks and choose the most appropriate set of trade-offs based on each individual use case and priority. This goes into more detail on oracles and the different approaches to the oracle problem. article Layer 1 Blockchains blockchains or networks refer to the underlying network where the basic operations occur. They have their own consensus mechanism, security protocols, and transaction processing rules, and they form the foundation upon which other blockchain applications can be built. Examples of Layer 1 chains are and . Layer 1 Bitcoin Ethereum In contrast, layer 2 blockchains are built on top of layer 1 blockchains and are designed to provide additional functionality and scalability without compromising overall network security. Examples of Layer 2 networks include Optimism and Arbitrum. Multi-Signature Wallets In some oracle networks, multi-sigs are used to verify consensus across multiple nodes, in order to confirm that the data is, in fact, accurate. Unlike regular crypto wallets, multi-signature wallets (also known as multi-sigs) refer to cryptocurrency wallets that require more than one signature or private key to approve a transaction. They are useful in ensuring that certain transactions can only occur with the approval of the majority of the signers. Multi-signature wallets, therefore, have greater security and can better resist hacks caused by stolen private keys. While multi-sigs can provide greater transparency and prevent single points of failure, they still allow for important decisions to be made by a small handful of multi-sig signers. There is no 100% guarantee that these signers will not collude to sway any major decision or vote in their favor. This from Binance Academy gives a more in-depth understanding of multi-sig wallets. post NFTs and Blockchain Traceability Non-Fungible Tokens or NFTs refer to unique digital tokens on the blockchain often used to certify ownership. Unlike traditional currencies or cryptocurrencies, an NFT cannot simply be replicated. In some cases, physical items are “tokenized” as NFTs so that the owners can enjoy the security and immutability of the blockchain. NFTs are excellent ownership-proofs because they are unique and traceable. Blockchain traceability allows users to trace the NFT from its creator to every subsequent buyer. This is because all network users have an immutable copy of the transactions, which shows clear evidence of who created the NFT and offers security in the form of a private key such that only the owner can authorize a transfer. Many real-world industries could benefit from adopting NFTs. How To Attach Physical Objects To The Blockchain Physical NFTs are helping to bridge real-world items to the blockchain. They enable many new applications, including event tickets and property deeds. To create physical NFTs, one must first issue a digital asset on a blockchain using smart contracts. After this, the physical asset is linked to a unique ID like a QR code which, when scanned, will connect automatically to the tokenized version of the item. are some examples of how top brands are using physical NFTs. Here Moving real-world industries on-chain will help to prevent counterfeit fraud and verify ownership due to increased transparency and immutability. Also, fair pricing will be ensured through transparency of sale history and the removal of intermediary presence and fees. Our Panelists: Nicholas Fett, Co-founder/CTO, Tellor Nicholas Fett is the CTO of Tellor. Formerly an economist at the CFTC, EF Grantee, and CEO of Daxia, he specializes in applying game theory and economics to build and launch products that are truly decentralised and work to add value to communities. He also enjoys arm wrestling, scotch, prog metal, and foosball. Tellor Website Nicholas Fett Twitter Andreas Dittrich, Managing Director, Finoa Consensus Services Dr. Andreas Dittrich is a computer scientist with a professional track record of 25 years in the IT industry. He worked in diverse roles as engineer, architect, consulting and management. His focus was on the security of service and cloud infrastructures. After several years in academia he started working for Deutsche Telekom (DT) where since 2019 he was heading the transformation of DT’s enterprise blockchain business to focus on supporting and promoting public blockchains. At the time of recording, Andreas was Managing Director at Finoa Consensus Services. He has since been promoted to CTO. Finoa Website Andreas Dittrich Twitter Abdul Osman, Founder/CEO, Goracle Abdul has a background in both Business Administration and Computer Science. He’s helped high level executives plan and execute short and long term business strategies. Abdul has also been part of teams that have developed banking software used by millions of Canadians daily. He believes secure and fast Oracles are key to realizing the potential of blockchain applications. Goracle Website Abdul Osman Twitter Saša Milić, Blockchain/Cryptography Researcher, Independent Saša is an independent researcher in the cryptography and blockchain space. She is one of the co-authors of the API3 whitepaper, and previously worked as a data scientist for Gauntlet Networks. She has an academic background in computer science and statistics. Saša Milić Twitter The Blockchain Oracle Summit was the world’s first conference to focus solely on the important role of oracles in the wider blockchain ecosystem and their limitations. Leading speakers from across the world gathered in Berlin to share their work and experience building and using oracle solutions. Also published here.

Decentralizing Real-World Industries: The On-Chain Revolution

A Step-by-Step Guide to Building Secure Oracles with Oasis ROFL

Vienna, September 25th, 2024 – Morpher GmbH, a blockchain trading platform for stocks, cryptos, forex, indices and unique markets such as sneakers and watches, has released an open source data oracle to improve access to reliable trading data. A blockchain oracle is a way of bringing data into a blockchain from external sources, including other blockchains. The oracles currently available suffer from the following problems: they have limited data availability, are not actually real-time, and have to battle licensing problems or usability problems (e.g. pull oracle data is visible before its being used). Oracles represent a single point of failure: if one of the currently available oracles goes down, so do all their feeds. This leaves blockchain applications depending on real-world data at a distinct disadvantage against regular platforms. To combat these shortcomings, Morpher’s Oracle has been built as an open source protocol, with multiple data sources aggregated. This allows for an increase in speed, accuracy, and reliability of data, which is a necessity for every settlement platform to operate. The Morpher Oracle comes in two flavors: a pull basedon-chain attestation data-service and a novel intent based oracle for EVM based chains. Both will include Data Feeds for US Equities, Commodities, Forex, and Crypto from the launch. The data is available in real-time, trustable, and able to be licensed to partners/developers. Morpher’s CEO Martin Froehler stated “Existing oracles could not power a real-time trading platform like Morpher. So we developed our own next generation, multi-sourced oracle which we are now making available to other projects on Radix and EVM chains.” Thomas Wiesner, Morpher’s CTO shares his vision for the oracle as "Our vision for the Morpher Oracle is to have the dev community continue to grow its robustness, adding more data streams, increasing the number of chains and further expanding the use cases past what we can currently imagine. We want to give a new tool to bring even more trust into blockchain." “We are super excited to see the release of the Morpher oracle live on Radix and available to use from today onwards - Morpher’s stack has already proven to be incredibly flexible and I look forward to what can be built, using their many data feeds, on Radix in the coming months.”
-Piers Ridyard, CEO of RDX Works Available to use today for all developers and see how quickly and accurately the Radix coin price is shown in USD. About Morpher Morpher, headquartered in Vienna, Austria, has been at the cutting edge of decentralized finance since 2018. The platform empowers users to trade virtual copies of real-world financial markets using its proprietary protocol and MPH token. Supported by prominent investors like Tim Draper, Morpher is dedicated to making global financial markets universally accessible. For more information, visit https://www.morpher.com/new. PR Contact Nick Stein Head of Growth nick@morpher.com +436603172205 Vienna, September 25th, 2024 – Morpher GmbH , a blockchain trading platform for stocks, cryptos, forex, indices and unique markets such as sneakers and watches, has released an open source data oracle to improve access to reliable trading data. Vienna, September 25th, 2024 Morpher GmbH Morpher GmbH open source data oracle open source data oracle A blockchain oracle is a way of bringing data into a blockchain from external sources, including other blockchains. The oracles currently available suffer from the following problems: they have limited data availability, are not actually real-time, and have to battle licensing problems or usability problems (e.g. pull oracle data is visible before its being used). Oracles represent a single point of failure: if one of the currently available oracles goes down, so do all their feeds. This leaves blockchain applications depending on real-world data at a distinct disadvantage against regular platforms. To combat these shortcomings, Morpher’s Oracle has been built as an open source protocol, with multiple data sources aggregated. This allows for an increase in speed, accuracy, and reliability of data, which is a necessity for every settlement platform to operate. The Morpher Oracle comes in two flavors: a pull basedon-chain attestation data-service and a novel intent based oracle for EVM based chains. Both will include Data Feeds for US Equities, Commodities, Forex, and Crypto from the launch. The data is available in real-time, trustable, and able to be licensed to partners/developers. Morpher’s CEO Martin Froehler stated “Existing oracles could not power a real-time trading platform like Morpher. So we developed our own next generation, multi-sourced oracle which we are now making available to other projects on Radix and EVM chains.” Thomas Wiesner, Morpher’s CTO shares his vision for the oracle as "Our vision for the Morpher Oracle is to have the dev community continue to grow its robustness, adding more data streams, increasing the number of chains and further expanding the use cases past what we can currently imagine. We want to give a new tool to bring even more trust into blockchain." “We are super excited to see the release of the Morpher oracle live on Radix and available to use from today onwards - Morpher’s stack has already proven to be incredibly flexible and I look forward to what can be built, using their many data feeds, on Radix in the coming months.” -Piers Ridyard, CEO of RDX Works “We are super excited to see the release of the Morpher oracle live on Radix and available to use from today onwards - Morpher’s stack has already proven to be incredibly flexible and I look forward to what can be built, using their many data feeds, on Radix in the coming months.” -Piers Ridyard, CEO of RDX Works Available to use today for all developers and see how quickly and accurately the Radix coin price is shown in USD. About Morpher Morpher, headquartered in Vienna, Austria, has been at the cutting edge of decentralized finance since 2018. The platform empowers users to trade virtual copies of real-world financial markets using its proprietary protocol and MPH token. Supported by prominent investors like Tim Draper, Morpher is dedicated to making global financial markets universally accessible. For more information, visit https://www.morpher.com/new. https://www.morpher.com/new . https://www.morpher.com/new PR Contact Nick Stein Head of Growth nick@morpher.com nick@morpher.com nick@morpher.com +436603172205

Blockchain Trading Platform Morpher Releases  Open Source Data Oracle

La plataforma de comerç de Blockchain Morpher llança Oracle de dades de codi obert

La plataforma de comercio blockchain Morpher publica datos de código abierto de Oracle

A Morpher Blockchain Kereskedelmi Platform kiadja a nyílt forráskódú Oracle-t

ブロックチェーン取引プラットフォームMorpherがオープンソースデータOracleをリリース

ბლოკჩეინ სავაჭრო პლატფორმა Morpher ავრცელებს ღია კოდის მონაცემთა Oracle-ს

Blockchain Trading Platform Morpher Oracle ачык булак маалыматтарын чыгарат

Blockchain Trading Platform Morpher Oracle-ийн нээлттэй эхийн өгөгдлийг гаргажээ

د بلاکچین سوداګرۍ پلیټ فارم مورفر د خلاصې سرچینې ډیټا اوریکل خپروي

Blockchain Trading Platform Morpher විවෘත මූලාශ්‍ර දත්ත ඔරකල් නිකුත් කරයි

Blockchain Trading Platform Morpher wuxuu siidaayaa Xogta Oracle Isha Furan

Blockchain Ticaret Platformu Morpher Açık Kaynaklı Veri Oracle'ı Yayınladı

区块链交易平台 Morpher 发布开源数据预言机

Yield Protocol is now dead, but not everything went to waste. One of the parts I thought was worth saving was its oracle layer. It was built over the simple concept of using token amounts instead of token prices, which apparently was a novel thing to do at the time. Over time, others agreed that it was a good idea. The contracts that I deployed, providing a consistent interface to Uniswap v2, Chainlink, Lido, and many others still work. Anyone can use them, but they are not very friendly to use. For a long time, I thought about fixing and redeploying them, as a gift to the commons. It bothered me that too many builders were reimplementing the same contracts once and again. I recently assisted a founder in reimplementing an oracle layer for a lending protocol. Again coding the same adapters for Chainlink, Uniswap, and other popular data providers. It was then that I decided something really needed to be done. We all have better things to do. So, I assembled a team, nerdsniped from Twitter, and started work on an Oracle layer that would be easy to use, robust, and permissionless. I didn’t want to do another ERC because I wanted to make sure it was fit for purpose before being cast in stone. I wanted to create something useful first. It was then that I decided something really needed to be done. However, this oracle layer would have an ERC-like specification. We would create a number of oracles, builders would adopt our contracts, and code more oracles to fill in the gaps. If the specification was fit for purpose, it would become a de facto standard, and only then would we propose it as an ERC. We created a number of basic oracles like ERC4626, Lido, and Chainlink. I was in the process of coding the Uniswap v3 oracle when Euler Labs made public their own oracle layer, using a compatible specification. That is not really a surprise if you consider that one of the leading members of our team of volunteers was also working for Euler. This happened much earlier than expected, but I recognized Euler’s work as a strong early adopter. I didn’t need to code any new oracles anymore because, with the ones in our own repo and the ones from Euler, we now cover the needs of a large proportion of users. Success is now inevitable. The days in which yet another adapter for Chainlink is implemented are counted. You definitely shouldn’t implement one, because now you know you can use an __ERC-7726 __for that. How to Use ERC-7726 Maybe this article of mine is the best introduction to the problem that we are trying to solve, which is to never deal with decimals again. You can then read this __whitepaper from Euler __for a more in-depth walkthrough on oracles.You could also ignore all previous instructions and just readthe spec: ERC-7726 oracles have a single `quoteOf` function, which takes the address for the base asset, the amount of the base asset, and an address for the quote asset. It will return the amount of the quote asset that would be equal in value to the amount of the base asset. The key point is that by focusing on token amounts instead of prices, ERC-7726 enforces an interaction pattern that is more intuitive and therefore safer from human mistakes. This is because, in ERC-7726, decimal manipulation and rounding are handled by the Oracle adapter, rather than the integrating application. Another key point is that ERC-7726 returns much less data than other oracles such as Chainlink. Instead of returning data for you to assess if the oracle is malfunctioning, it will revert if it considers its data not to be trusted. This is because we believe that the end user shouldn’t be the one to decide if the oracle is malfunctioning. It was built over the simple concept of using token amounts instead of token prices If you are developing an oracle that conforms to ERC-7726, you are responsible to the best of your ability for the oracle either returning a value that can be trusted, or reverting. Your trust assumptions should be clearly included in the natspec of the oracle for the end user to consider, as it’s probably impossible to create a perfect oracle. Then it is up to the user to decide whether they use the oracle with its trust assumptions, or not. Ideally, users who decide that the oracle is not good enough for their purposes will code an ERC-7726 oracle that does. Usually, more robust data feeds come as a trade-off on other oracle qualities such as gas cost, and end users will be then able to choose between several oracles with different trade-off choices. The oracles that we have developed and the ones that Euler has developed are permissionless, but ERC-7726 doesn’t demand that. It is possible that some oracles might need a degree of governance to provide robust data, and if so, they can still conform to ERC-7726.That’s all, there is nothing more to it. There are a bunch of oracles already coded that you can use. They use data from the most popular sources, they deal in token amounts, and they revert if they don’t trust their return data themselves. Contributing There is plenty to do to contribute, and none of it is too hard. Just in awesome-oracles you can: Code new oracles
Audit the existing ones
Deploy the existing ones
Add content like other repos for ERC-7726 oracles, articles, tooling, and so on. We’ve got a telegram group that you can join if you want to chat, otherwise, you can get on using the code and submitting PRs. Thank you! Yield Protocol is now dead, but not everything went to waste. One of the parts I thought was worth saving was its oracle layer. It was built over the simple concept of using token amounts instead of token prices, which apparently was a novel thing to do at the time. Over time, others agreed that it was a good idea. The contracts that I deployed, providing a consistent interface to Uniswap v2, Chainlink, Lido, and many others still work. Anyone can use them, but they are not very friendly to use. For a long time, I thought about fixing and redeploying them, as a gift to the commons. It bothered me that too many builders were reimplementing the same contracts once and again. I recently assisted a founder in reimplementing an oracle layer for a lending protocol. Again coding the same adapters for Chainlink, Uniswap, and other popular data providers. It was then that I decided something really needed to be done. We all have better things to do. So, I assembled a team, nerdsniped from Twitter, and started work on an Oracle layer that would be easy to use, robust, and permissionless. I didn’t want to do another ERC because I wanted to make sure it was fit for purpose before being cast in stone. I wanted to create something useful first. It was then that I decided something really needed to be done. It was then that I decided something really needed to be done. However, this oracle layer would have an ERC-like specification. We would create a number of oracles, builders would adopt our contracts, and code more oracles to fill in the gaps. If the specification was fit for purpose, it would become a de facto standard, and only then would we propose it as an ERC. We created a number of basic oracles like ERC4626, Lido, and Chainlink. I was in the process of coding the Uniswap v3 oracle when Euler Labs made public their own oracle layer , using a compatible specification. That is not really a surprise if you consider that one of the leading members of our team of volunteers was also working for Euler. basic oracles basic oracles oracle layer oracle layer This happened much earlier than expected, but I recognized Euler’s work as a strong early adopter. I didn’t need to code any new oracles anymore because, with the ones in our own repo and the ones from Euler, we now cover the needs of a large proportion of users. Success is now inevitable. The days in which yet another adapter for Chainlink is implemented are counted. You definitely shouldn’t implement one, because now you know you can use an __ ERC-7726 __for that. ERC-7726 How to Use ERC-7726 Maybe this article of mine is the best introduction to the problem that we are trying to solve, which is to never deal with decimals again. You can then read this __ whitepaper from Euler __for a more in-depth walkthrough on oracles. You could also ignore all previous instructions and just read the spec : ERC-7726 oracles have a single `quoteOf` function, which takes the address for the base asset, the amount of the base asset, and an address for the quote asset. It will return the amount of the quote asset that would be equal in value to the amount of the base asset. this article of mine this article of mine whitepaper from Euler the spec the spec The key point is that by focusing on token amounts instead of prices, ERC-7726 enforces an interaction pattern that is more intuitive and therefore safer from human mistakes. This is because, in ERC-7726, decimal manipulation and rounding are handled by the Oracle adapter, rather than the integrating application. Another key point is that ERC-7726 returns much less data than other oracles such as Chainlink. Instead of returning data for you to assess if the oracle is malfunctioning, it will revert if it considers its data not to be trusted. This is because we believe that the end user shouldn’t be the one to decide if the oracle is malfunctioning. It was built over the simple concept of using token amounts instead of token prices It was built over the simple concept of using token amounts instead of token prices If you are developing an oracle that conforms to ERC-7726, you are responsible to the best of your ability for the oracle either returning a value that can be trusted, or reverting. Your trust assumptions should be clearly included in the natspec of the oracle for the end user to consider, as it’s probably impossible to create a perfect oracle. Then it is up to the user to decide whether they use the oracle with its trust assumptions, or not. Ideally, users who decide that the oracle is not good enough for their purposes will code an ERC-7726 oracle that does. Usually, more robust data feeds come as a trade-off on other oracle qualities such as gas cost, and end users will be then able to choose between several oracles with different trade-off choices. The oracles that we have developed and the ones that Euler has developed are permissionless, but ERC-7726 doesn’t demand that. It is possible that some oracles might need a degree of governance to provide robust data, and if so, they can still conform to ERC-7726. That’s all, there is nothing more to it. There are a bunch of oracles already coded that you can use. They use data from the most popular sources, they deal in token amounts, and they revert if they don’t trust their return data themselves. Contributing There is plenty to do to contribute, and none of it is too hard. Just in awesome-oracles you can: awesome-oracles awesome-oracles Code new oracles Audit the existing ones Deploy the existing ones Add content like other repos for ERC-7726 oracles, articles, tooling, and so on. Code new oracles Audit the existing ones Deploy the existing ones Add content like other repos for ERC-7726 oracles, articles, tooling, and so on. We’ve got a telegram group that you can join if you want to chat, otherwise, you can get on using the code and submitting PRs. Thank you! a telegram group that you can join a telegram group that you can join

ERC-7726: Never Code an Oracle in Ethereum Again

Flare, has unveiled the second version of its Flare Time Series Oracle (FTSO) on the mainnet. Building upon the robust foundation of FTSOv1, which has consistently delivered dependable decentralized data feeds for the past two years without any downtime or failures, FTSOv2 introduces significant improvements in latency, scalability, and cost-efficiency. Elevating Decentralized Data with Flare Flare is a blockchain platform meticulously designed to support data-intensive applications such as machine learning, artificial intelligence, real-world asset tokenization, gaming, and social applications. At the heart of Flare’s ecosystem lies its decentralized oracle system, secured at the network layer. This unique architecture makes Flare the only smart contract platform optimized for decentralized data acquisition, encompassing price feeds, blockchain data, and web2 APIs. By offering developers trustless access to a vast array of data that is both scalable and affordable, Flare is expanding the utility of blockchain technology and enabling a multitude of innovative use cases. Key Enhancements in FTSOv2 One of the standout features of FTSOv2 is its reduced latency. The upgraded system now updates with every new block on Flare, approximately every 1.8 seconds. This rapid update cycle allows developers and users to access the most current and reliable data swiftly, which is crucial for applications that rely on real-time information. Despite this significant speed boost, decentralization remains a cornerstone of the system. Each data feed is supported by around 100 independent data providers, selected by users who delegate their stake. This selection process ensures that economic penalties are imposed for any malicious behavior, maintaining the integrity of the data. Currently, approximately 67% of the circulating FLR tokens are dedicated to securing the FTSO, underscoring the community’s commitment to a secure and decentralized data infrastructure. Scalability is another major improvement in FTSOv2. The system can now support up to 1,000 data feeds across various asset classes, including cryptocurrencies, equities, and commodities. Even with this expanded capacity, querying crypto feeds on-chain remains free, making FTSOv2 a highly cost-effective solution for developers and users alike. Real-World Applications of FTSOv2 The advancements in FTSOv2 open up numerous possibilities across different sectors: Lending and Borrowing Platforms: Enhanced speed ensures more efficient collateral utilization and safeguards users against bad liquidations.
Perpetual Futures and Options Markets: Quicker oracle inputs enhance risk management, providing more accurate and timely data for traders.
Cross-Chain Order Books: Accurate pricing data facilitates smooth and secure transactions between different blockchain networks.
Real-World Assets: The system’s ability to handle on-chain treasury yields bridges the gap between traditional finance and blockchain technology, enabling seamless integration of real-world financial instruments. Behind the Scenes: How FTSOv2 Works FTSOv2 employs a sophisticated, manipulation-resistant randomness algorithm to select data providers every 1.8 seconds, allowing them to submit regular updates to the data feeds. To ensure long-term accuracy, all data providers participate in a commit-reveal process every 90 seconds. This mechanism maintains data integrity and prevents manipulation. Additionally, during periods of high market volatility, the system can call upon more data providers to ensure timely and accurate price updates, maintaining the reliability of the data under all market conditions. For developers looking to integrate FTSOv2 into their applications, the process is straightforward. Accessing real-time data, such as FLR/USD prices, requires fewer than 10 lines of code. Flare supports this integration with extensive resources available through its Developer Hub and a supportive community on Discord, where developers can seek additional assistance and collaborate with peers. Expanding Blockchain Utility with Flare The launch of FTSOv2 marks a significant milestone for Flare, reinforcing its position as a leader in decentralized data solutions. By enhancing latency, scalability, and cost-efficiency, Flare is not only improving the performance of its oracle system but also broadening the horizons for what blockchain technology can achieve. As Flare continues to innovate and expand its capabilities, it is poised to drive the next wave of advancements in decentralized applications, making blockchain technology more accessible and versatile for developers and users worldwide. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Flare , has unveiled the second version of its Flare Time Series Oracle (FTSO) on the mainnet. Building upon the robust foundation of FTSOv1, which has consistently delivered dependable decentralized data feeds for the past two years without any downtime or failures, FTSOv2 introduces significant improvements in latency, scalability, and cost-efficiency. Flare Elevating Decentralized Data with Flare Flare is a blockchain platform meticulously designed to support data-intensive applications such as machine learning, artificial intelligence, real-world asset tokenization, gaming, and social applications. At the heart of Flare’s ecosystem lies its decentralized oracle system, secured at the network layer. This unique architecture makes Flare the only smart contract platform optimized for decentralized data acquisition, encompassing price feeds, blockchain data, and web2 APIs. By offering developers trustless access to a vast array of data that is both scalable and affordable, Flare is expanding the utility of blockchain technology and enabling a multitude of innovative use cases. Key Enhancements in FTSOv2 One of the standout features of FTSOv2 is its reduced latency. The upgraded system now updates with every new block on Flare, approximately every 1.8 seconds. This rapid update cycle allows developers and users to access the most current and reliable data swiftly, which is crucial for applications that rely on real-time information. Despite this significant speed boost, decentralization remains a cornerstone of the system. Each data feed is supported by around 100 independent data providers, selected by users who delegate their stake. This selection process ensures that economic penalties are imposed for any malicious behavior, maintaining the integrity of the data. Currently, approximately 67% of the circulating FLR tokens are dedicated to securing the FTSO, underscoring the community’s commitment to a secure and decentralized data infrastructure. Scalability is another major improvement in FTSOv2. The system can now support up to 1,000 data feeds across various asset classes, including cryptocurrencies, equities, and commodities. Even with this expanded capacity, querying crypto feeds on-chain remains free, making FTSOv2 a highly cost-effective solution for developers and users alike. Real-World Applications of FTSOv2 The advancements in FTSOv2 open up numerous possibilities across different sectors: Lending and Borrowing Platforms: Enhanced speed ensures more efficient collateral utilization and safeguards users against bad liquidations. Perpetual Futures and Options Markets: Quicker oracle inputs enhance risk management, providing more accurate and timely data for traders. Cross-Chain Order Books: Accurate pricing data facilitates smooth and secure transactions between different blockchain networks. Real-World Assets: The system’s ability to handle on-chain treasury yields bridges the gap between traditional finance and blockchain technology, enabling seamless integration of real-world financial instruments. Lending and Borrowing Platforms: Enhanced speed ensures more efficient collateral utilization and safeguards users against bad liquidations. Lending and Borrowing Platforms: Perpetual Futures and Options Markets: Quicker oracle inputs enhance risk management, providing more accurate and timely data for traders. Perpetual Futures and Options Markets: Cross-Chain Order Books: Accurate pricing data facilitates smooth and secure transactions between different blockchain networks. Cross-Chain Order Books: Real-World Assets: The system’s ability to handle on-chain treasury yields bridges the gap between traditional finance and blockchain technology, enabling seamless integration of real-world financial instruments. Real-World Assets: Behind the Scenes: How FTSOv2 Works FTSOv2 employs a sophisticated, manipulation-resistant randomness algorithm to select data providers every 1.8 seconds, allowing them to submit regular updates to the data feeds. To ensure long-term accuracy, all data providers participate in a commit-reveal process every 90 seconds. This mechanism maintains data integrity and prevents manipulation. Additionally, during periods of high market volatility, the system can call upon more data providers to ensure timely and accurate price updates, maintaining the reliability of the data under all market conditions. For developers looking to integrate FTSOv2 into their applications, the process is straightforward. Accessing real-time data, such as FLR/USD prices, requires fewer than 10 lines of code. Flare supports this integration with extensive resources available through its Developer Hub and a supportive community on Discord, where developers can seek additional assistance and collaborate with peers. Expanding Blockchain Utility with Flare The launch of FTSOv2 marks a significant milestone for Flare, reinforcing its position as a leader in decentralized data solutions. By enhancing latency, scalability, and cost-efficiency, Flare is not only improving the performance of its oracle system but also broadening the horizons for what blockchain technology can achieve. As Flare continues to innovate and expand its capabilities, it is poised to drive the next wave of advancements in decentralized applications, making blockchain technology more accessible and versatile for developers and users worldwide. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

Flare Launches Enhanced Time Series Oracle v2, Boosting Decentralized Data Capabilities

Flare تطلق Oracle v2 المحسّنة للسلاسل الزمنية، مما يعزز قدرات البيانات اللامركزية

Flare lansira poboljšanu vremensku seriju Oracle v2, povećavajući mogućnosti decentraliziranih podataka

Flare lanza Oracle v2 de series temporales mejoradas, que potencia las capacidades de datos descentralizados

Flare-k Time Series Oracle v2 hobetua abiarazten du, datu deszentralizatuen gaitasunak areagotuz

Flare が強化された Time Series Oracle v2 をリリースし、分散データ機能を強化

Flare ເປີດຕົວຊຸດເວລາທີ່ມີການປັບປຸງ Oracle v2, ເພີ່ມຄວາມສາມາດຂອງຂໍ້ມູນແບບກະຈາຍ

„Flare“ pristato patobulintą laiko seriją „Oracle v2“, padidinančią decentralizuotų duomenų galimybes

Flare лансира подобрена временска серија Oracle v2, зголемувајќи ги способностите за децентрализирани податоци

Flare lança o Enhanced Time Series Oracle v2, impulsionando os recursos de dados descentralizados

Flare запускает улучшенный временной ряд Oracle v2, расширяя возможности децентрализованных данных

Flare Inotangisa Enhanced Time Series Oracle v2, Boosting Decentralized Data Kugona

ஃப்ளேர் மேம்படுத்தப்பட்ட நேரத் தொடர் ஆரக்கிள் v2 ஐ அறிமுகப்படுத்துகிறது, பரவலாக்கப்பட்ட தரவு திறன்களை அதிகரிக்கிறது

A Step-by-step guide on how to use the .Net Aspire Oracle component in Visual Studio. .Net Aspire framework is used to develop cloud and production-ready distributed applications. It consists of components to handle cloud-native concerns such as Redis, Postgres, etc. Prerequisites Install .Net 8
Install Visual Studio 2022 version 17 or higher
.Net Aspire Workload
Container runtime such as Docker Desktop 10 Day .Net Aspire Challenge Objectives Learn how to create a starter project using .Net Aspire with the Oracle EF Core component. Github Sample: The solution structure is divided into the following projects:- DotnetAspireChallenge.ApiService
DotnetAspireChallenge.AppHost
DotnetAspireChallenge.ServiceDefaults
DotnetAspireChallenge.Web Getting Started Step 1: Install the following NuGet package Install the following Nuget package into the subsequent project “DotnetAspireChallenge.AppHost” dotnet add package Aspire.Hosting.Oracle In the above project, register a server database and consume the Oracle connection using the following code. var oracle = builder.AddOracle("oracle")
                        .AddDatabase("oracledb");
    
    var apiService = builder.AddProject<Projects.DotnetAspireChallenge_ApiService>("apiservice")
        .WithReference(oracle); Step 2: Install another NuGet package Install the following Nuget package into the subsequent project “DotnetAspireChallenge.ApiService” dotnet add package Aspire.Oracle.EntityFrameworkCore then register the context into the Program.cs file as follows builder.AddOracleDatabaseDbContext<OracleDbContext>("oracledb"); Step 3: Create a “Customer” class public class Customer
    {
        public int Id { get; set; }
        
        [Required]
        public string Title { get; set; } = string.Empty;
        
        [Required]
        public string Description { get; set; } = string.Empty;
    } Step 4: Create an extension class Create an extension class and register a minimal API get method to demonstrate the Oracle EF context usage in the API Service public static class AspireOracleExtension
    {
        public static void MapOracleAspireEndpoint(this WebApplication app)
        {
            app.MapGet("/oracle", async (OracleDbContext oracleDbContext) =>
            {
                  await oracleDbContext.Customer.AddAsync(new Customer()
                  {
                      Title = "test@gmail.com",
                      Description = "sukh"
                  });
                  int rows = await oracleDbContext.SaveChangesAsync();
                  if (rows > 0)
                  {
                      return await oracleDbContext.Customer.FirstOrDefaultAsync();
                  }
                  else
                  {
                      return null;
                  }
            });
    
        }
    }
    
    
    internal class OracleDbContext(DbContextOptions options) : DbContext(options)
    {
        public DbSet<Customer> CustomersPgsql => Set<Customer>();
    } and finally, register in the Program.cs file app.MapOracleAspireEndpoint(); Step 5: Hit the GET endpoint Finally, navigate to the GET URL shown below in your browser. It will insert the specified customer into the Oracle database, retrieve the most recently inserted row, and display it as a response. Add additional connection string properties using the JSON syntax {
      "Aspire": {
        "Oracle": {
          "EntityFrameworkCore": {
            "DisableHealthChecks": true,
            "DisableTracing": true,
            "DisableMetrics": false,
            "DisableRetry": false,
            "Timeout": 30
          }
        }
      }
    } Congratulations..!! You’ve successfully integrated the Oracle component into the .Net Aspire project. Github Project: GitHub - ssukhpinder/DotnetAspireChallenge: 10 Day .Net Aspire Challenge
Cheatsheet: Cheat Sheets — .Net A Step-by-step guide on how to use the .Net Aspire Oracle component in Visual Studio. .Net Aspire framework is used to develop cloud and production-ready distributed applications. It consists of components to handle cloud-native concerns such as Redis , Postgres , etc. Redis Postgres Prerequisites Install .Net 8 Install Visual Studio 2022 version 17 or higher .Net Aspire Workload Container runtime such as Docker Desktop Install .Net 8 .Net 8 Install Visual Studio 2022 version 17 or higher Visual Studio 2022 .Net Aspire Workload Container runtime such as Docker Desktop Docker Desktop 10 Day .Net Aspire Challenge 10 Day .Net Aspire Challenge 10 Day .Net Aspire Challenge Objectives Learn how to create a starter project using .Net Aspire with the Oracle EF Core component. Github Sample : The solution structure is divided into the following projects:- Github Sample DotnetAspireChallenge.ApiService DotnetAspireChallenge.AppHost DotnetAspireChallenge.ServiceDefaults DotnetAspireChallenge.Web DotnetAspireChallenge.ApiService DotnetAspireChallenge.AppHost DotnetAspireChallenge.ServiceDefaults DotnetAspireChallenge.Web Getting Started Step 1: Install the following NuGet package Install the following Nuget package into the subsequent project “ DotnetAspireChallenge.AppHost ” DotnetAspireChallenge.AppHost dotnet add package Aspire.Hosting.Oracle dotnet add package Aspire.Hosting.Oracle In the above project, register a server database and consume the Oracle connection using the following code. var oracle = builder.AddOracle("oracle")
                        .AddDatabase("oracledb");
    
    var apiService = builder.AddProject<Projects.DotnetAspireChallenge_ApiService>("apiservice")
        .WithReference(oracle); var oracle = builder.AddOracle("oracle")
                        .AddDatabase("oracledb");
    
    var apiService = builder.AddProject<Projects.DotnetAspireChallenge_ApiService>("apiservice")
        .WithReference(oracle); Step 2: Install another NuGet package Install the following Nuget package into the subsequent project “ DotnetAspireChallenge.ApiService ” DotnetAspireChallenge.ApiService dotnet add package Aspire.Oracle.EntityFrameworkCore dotnet add package Aspire.Oracle.EntityFrameworkCore then register the context into the Program.cs file as follows builder.AddOracleDatabaseDbContext<OracleDbContext>("oracledb"); builder.AddOracleDatabaseDbContext<OracleDbContext>("oracledb"); Step 3: Create a “Customer” class public class Customer
    {
        public int Id { get; set; }
        
        [Required]
        public string Title { get; set; } = string.Empty;
        
        [Required]
        public string Description { get; set; } = string.Empty;
    } public class Customer
    {
        public int Id { get; set; }
        
        [Required]
        public string Title { get; set; } = string.Empty;
        
        [Required]
        public string Description { get; set; } = string.Empty;
    } Step 4: Create an extension class Create an extension class and register a minimal API get method to demonstrate the Oracle EF context usage in the API Service public static class AspireOracleExtension
    {
        public static void MapOracleAspireEndpoint(this WebApplication app)
        {
            app.MapGet("/oracle", async (OracleDbContext oracleDbContext) =>
            {
                  await oracleDbContext.Customer.AddAsync(new Customer()
                  {
                      Title = "test@gmail.com",
                      Description = "sukh"
                  });
                  int rows = await oracleDbContext.SaveChangesAsync();
                  if (rows > 0)
                  {
                      return await oracleDbContext.Customer.FirstOrDefaultAsync();
                  }
                  else
                  {
                      return null;
                  }
            });
    
        }
    }
    
    
    internal class OracleDbContext(DbContextOptions options) : DbContext(options)
    {
        public DbSet<Customer> CustomersPgsql => Set<Customer>();
    } public static class AspireOracleExtension
    {
        public static void MapOracleAspireEndpoint(this WebApplication app)
        {
            app.MapGet("/oracle", async (OracleDbContext oracleDbContext) =>
            {
                  await oracleDbContext.Customer.AddAsync(new Customer()
                  {
                      Title = "test@gmail.com",
                      Description = "sukh"
                  });
                  int rows = await oracleDbContext.SaveChangesAsync();
                  if (rows > 0)
                  {
                      return await oracleDbContext.Customer.FirstOrDefaultAsync();
                  }
                  else
                  {
                      return null;
                  }
            });
    
        }
    }
    
    
    internal class OracleDbContext(DbContextOptions options) : DbContext(options)
    {
        public DbSet<Customer> CustomersPgsql => Set<Customer>();
    } and finally, register in the Program.cs file app.MapOracleAspireEndpoint(); app.MapOracleAspireEndpoint(); Step 5: Hit the GET endpoint Finally, navigate to the GET URL shown below in your browser. It will insert the specified customer into the Oracle database, retrieve the most recently inserted row, and display it as a response. Add additional connection string properties using the JSON syntax {
      "Aspire": {
        "Oracle": {
          "EntityFrameworkCore": {
            "DisableHealthChecks": true,
            "DisableTracing": true,
            "DisableMetrics": false,
            "DisableRetry": false,
            "Timeout": 30
          }
        }
      }
    } {
      "Aspire": {
        "Oracle": {
          "EntityFrameworkCore": {
            "DisableHealthChecks": true,
            "DisableTracing": true,
            "DisableMetrics": false,
            "DisableRetry": false,
            "Timeout": 30
          }
        }
      }
    } Congratulations..!! You’ve successfully integrated the Oracle component into the .Net Aspire project. Github Project: GitHub - ssukhpinder/DotnetAspireChallenge: 10 Day .Net Aspire Challenge Cheatsheet: Cheat Sheets — .Net Github Project: GitHub - ssukhpinder/DotnetAspireChallenge: 10 Day .Net Aspire Challenge Github Project: GitHub - ssukhpinder/DotnetAspireChallenge: 10 Day .Net Aspire Challenge Cheatsheet: Cheat Sheets — .Net Cheatsheet: Cheat Sheets — .Net

10 Days of .Net Aspire: Day 4 — Using Oracle Component in Visual Studio 

Oracles are another interesting way to customize your experience in the Obyte ecosystem. They're like bridges that connect decentralized networks to the outside world. Distributed ledgers are excellent at securely storing and verifying data, but they can't access real-world information on their own. Oracles solve this by fetching data from external sources and feeding it into their system, enabling smart contracts to interact with real-world events, prices, and information. Oracles work by collecting data from various sources like APIs, websites, sensors, or other off-chain data providers. They upload this data to the chain and then you can find it by the address of the one who posted it (e.g., this is an Obyte oracle address, identical to any other wallet address: I2ADHGP4HL6J37NQAD73J7E5SKFIXJOT). Some oracles use a decentralized approach where multiple data sources are used to ensure accuracy and prevent manipulation. This mechanism helps ensure that the data is trustworthy and tamper-proof. On the other hand, you can easily set up your own personal oracle (data feed) for your specific use case, or let it be created by a close party, like a member of your family or coworker. This way, the oracle can offer any personalized information you can count on to make transactions among your inner circle, or with business partners. In Obyte, it’s possible to create your own oracle in a few minutes, without coding or technical steps. Potential Uses The use cases for oracles are vast and varied. In finance, they can provide real-time price feeds for cryptocurrencies and traditional assets, enabling decentralized finance (DeFi) applications like lending, trading, and insurance. In supply chain management, oracles can track and verify the status of goods in transit. They can also be used in gaming to bring in real-world events to affect gameplay, or in weather forecasting to trigger payouts in weather-based insurance policies. As for a personal oracle, the uses are only defined by yourself, because the data can only come from yourself. For instance, we can register the successful completion of a specific task by Alice (a daughter, a coworker, a partner, etc.). A conditional payment from the wallet could use this information to release funds automatically if we use that oracle address (the wallet address of the oracle operator) to create the smart contract (Chat – [Registered Contact] - Recipient’s address – Offer smart contract). **  ** Human or customized oracles could also work for rewards in family tokens. For example, parents can create an oracle that tracks if specific tasks are completed by their children. A supervisor (such as a parent) can create an oracle by sending data into the Obyte DAG, such as a task's completion status. When a child completes a task, the supervisor updates the oracle with a value like "Yes." The family token system can then automatically trigger a reward, sending the predefined tokens from the family treasury to the child’s wallet as a reward for completing the task. The same principle could apply to anything you like to use it for. Steps without coding First of all, you’ll need to download and back up an Obyte wallet, available as a light app for desktop and mobile. Next, in the “Receive” section, you can click “Get Me Coins” to buy some GBYTEs, needed for transaction fees —you’ll need around $0.00001 per transaction. There are other ways to buy GBYTEs with traditional money, and you can consult them in this full guide. Once the app is installed and with some GBYTEs available to spend, go to the “Send” section of the wallet. At the top of this page, you should see “What to send,” and a list below. From that list, instead of any asset, select “Data into datafeed (searchable).” To advance further, your account needs to be of a single address. If it’s not, then you’ll need to switch to your already created single-address account or create a new one from the main menu (Add account – Plain Account – Single Address Account). All new accounts are single-address by default. Beyond this, you’ll only need to fill the values of your data feed (oracle) in any way you want, including a name/title, and a result/answer. For instance, the name could be “Mary’s task,” and the result could be “Done.” Press “Send,” type your password if required, and that’s it! A small transaction fee will be taken from your wallet, and the oracle will be published on the Obyte DAG, available for everyone to consult —including smart contracts. **  ** Creating your own oracle here is easy, fast, secure, and inexpensive. Now, if you know how to code and want to make it more advanced, you can always check our documentation to create an oracle from scratch. Featured Vector Image by Freepik Oracles are another interesting way to customize your experience in the Obyte ecosystem. They're like bridges that connect decentralized networks to the outside world. Distributed ledgers are excellent at securely storing and verifying data, but they can't access real-world information on their own. Oracles solve this by fetching data from external sources and feeding it into their system, enabling smart contracts to interact with real-world events, prices, and information. Oracles work by collecting data from various sources like APIs, websites, sensors, or other off-chain data providers. They upload this data to the chain and then you can find it by the address of the one who posted it (e.g., this is an Obyte oracle address, identical to any other wallet address: I2ADHGP4HL6J37NQAD73J7E5SKFIXJOT). Some oracles use a decentralized approach where multiple data sources are used to ensure accuracy and prevent manipulation. This mechanism helps ensure that the data is trustworthy and tamper-proof. They upload this data to the chain and then you can find it by the address of the one who posted it On the other hand, you can easily set up your own personal oracle (data feed) for your specific use case, or let it be created by a close party, like a member of your family or coworker. This way, the oracle can offer any personalized information you can count on to make transactions among your inner circle, or with business partners. In Obyte, it’s possible to create your own oracle in a few minutes, without coding or technical steps. Potential Uses The use cases for oracles are vast and varied. In finance, they can provide real-time price feeds for cryptocurrencies and traditional assets, enabling decentralized finance (DeFi) applications like lending, trading, and insurance. In supply chain management, oracles can track and verify the status of goods in transit. They can also be used in gaming to bring in real-world events to affect gameplay, or in weather forecasting to trigger payouts in weather-based insurance policies. As for a personal oracle, the uses are only defined by yourself, because the data can only come from yourself. For instance, we can register the successful completion of a specific task by Alice (a daughter, a coworker, a partner, etc.). A conditional payment from the wallet could use this information to release funds automatically if we use that oracle address (the wallet address of the oracle operator) to create the smart contract (Chat – [Registered Contact] - Recipient’s address – Offer smart contract). As for a personal oracle, the uses are only defined by yourself, because the data can only come from yourself. the smart contract the smart contract ** ** Human or customized oracles could also work for rewards in family tokens . For example, parents can create an oracle that tracks if specific tasks are completed by their children. A supervisor (such as a parent) can create an oracle by sending data into the Obyte DAG, such as a task's completion status. family tokens family tokens When a child completes a task, the supervisor updates the oracle with a value like "Yes." The family token system can then automatically trigger a reward, sending the predefined tokens from the family treasury to the child’s wallet as a reward for completing the task. The same principle could apply to anything you like to use it for. Steps without coding Steps without coding First of all, you’ll need to download and back up an Obyte wallet , available as a light app for desktop and mobile. Next, in the “Receive” section, you can click “ Get Me Coins ” to buy some GBYTEs, needed for transaction fees —you’ll need around $0.00001 per transaction. There are other ways to buy GBYTEs with traditional money, and you can consult them in this full guide . Obyte wallet Obyte wallet Get Me Coins Get Me Coins this full guide this full guide Once the app is installed and with some GBYTEs available to spend, go to the “Send” section of the wallet. At the top of this page, you should see “What to send,” and a list below. From that list, instead of any asset, select “Data into datafeed (searchable).” To advance further, your account needs to be of a single address. If it’s not, then you’ll need to switch to your already created single-address account or create a new one from the main menu (Add account – Plain Account – Single Address Account). All new accounts are single-address by default. Once the app is installed and with some GBYTEs available to spend, go to the “Send” section of the wallet. Beyond this, you’ll only need to fill the values of your data feed (oracle) in any way you want, including a name/title, and a result/answer. For instance, the name could be “Mary’s task,” and the result could be “Done.” Press “Send,” type your password if required, and that’s it! A small transaction fee will be taken from your wallet, and the oracle will be published on the Obyte DAG , available for everyone to consult —including smart contracts. Obyte DAG Obyte DAG ** ** Creating your own oracle here is easy, fast, secure, and inexpensive. Now, if you know how to code and want to make it more advanced, you can always check our documentation to create an oracle from scratch. our documentation our documentation Featured Vector Image by Freepik Featured Vector Image by Freepik Freepik Freepik

Educational Byte: How to and why create your own oracle on Obyte?

শিক্ষাগত বাইট: কীভাবে এবং কেন ওবাইটে আপনার নিজের ওরাকল তৈরি করবেন?

Bildungsbyte: Wie und warum erstellen Sie Ihr eigenes Orakel auf Obyte?

Byte educativo: ¿Cómo y por qué crear tu propio oráculo en Obyte?

Educational Byte : Comment et pourquoi créer son propre oracle sur Obyte ?

शैक्षिक बाइट: ओबाइट पर अपना स्वयं का ओरेकल कैसे और क्यों बनाएं?

教育バイト: Obyte で独自のオラクルを作成する方法とその理由

Educational Byte: Obyte에서 자신만의 오라클을 만드는 방법과 이유는 무엇입니까?

Byte Educacional: Como e por que criar seu próprio oráculo no Obyte?

Educational Byte: Как и зачем создать свой собственный оракул на Obyte?

Eğitim Baytı: Obyte'de kendi kehanetinizi nasıl ve neden yaratabilirsiniz?

Byte giáo dục: Làm thế nào và tại sao lại tạo oracle của riêng bạn trên Obyte?

教育字节：如何以及为什么在 Obyte 上创建自己的 oracle？

I was inspired to write this blog post after reading a paper called "The Oracle Problem — Why Decentralising Everything is More Difficult than it Sounds" by Victor Hogrefe. As the title suggests, Victor argues that there are no good solutions for handling oracles on the blockchain. It may have been true six years ago when the paper was written, so kudos to Victor for proposing some potential ones back then. However, what struck me the most was that the author failed to consider that the oracles themselves can be decentralized. In this post, I'll explain why it's actually "not that difficult" to decentralize everything and how this issue has already been solved with the help of decentralized oracles. But first, let's take a small step back and learn what oracles are exactly. The Role Of Oracles Smart contracts are designed in a way to provide deterministic results. Their job is to take input, execute logic, and modify the state of the blockchain irreversibly. But the majority of events still happen off-chain. Allowing smart contracts to interact with these events has always been a double-edged sword. On one hand, this significantly increases the potential blockchain use cases but on the other —  poses serious security risks and trust issues. Oracles are here to help. They act as a bridge between blockchains and the external world and enable smart contracts to execute code based on real-world events and conditions. For example, to be able to bet on the outcome of a tennis match between Roger Federer and Novak Djokovic, you need a way to tell the smart contract who won. Since we don't live in the Metaverse yet, a smart contract can't know the outcome of the match — someone has to tell it who the winner is, so that the contract can payout to the winners. The big question is: who will be the one to tell the smart contract who won? We would need to trust this person or entity to be correct and honest... But wait a minute... Trust? That's not how things work in Web3. We don't want to trust. We want trustless. Decentralized Oracles In the original paper I mentioned in the beginning, the author overlooks the possibility of oracles being decentralized and is rather focused on discussing different algorithmic solutions, weaknesses, and potential attack vectors. What he doesn't consider is that the oracles themselves can be decentralized. Decentralized oracles, unlike the normal ones, rely on multiple independent nodes to fetch and validate information. This means there's no single point of failure, making it much harder to compromise the system. By using various mechanisms, such as multiple data sources, multiple oracles, or the need to have a stake in the system, decentralized oracles can prevent different sorts of malicious attacks, data corruption, or bribery. One such mechanism has been implemented by the UMA Protocol. UMA's Optimistic Oracles UMA is a leader in the oracles space, alongside Chainlink, which is the largest oracle protocol in the world. UMA's oracle system consists of two main components: the Optimistic Oracle and the Data Verification Mechanism (DVM). The principle is straightforward: anyone can submit an answer on-chain, and a dispute arises only if the answer is incorrect. The first layer of UMA's oracle system is the Optimistic Oracle. This layer is designed to quickly verify data optimistically, meaning that all submitted statements are true by default unless challenged. The second layer is the DVM (Data Verification Mechanism), which serves as a fallback for the Optimistic Oracle by resolving disputes if they occur. The entire system is efficient and cheap because it aims to prevent disputes in the first place. Here’s how it works: A smart contract requests a piece of data and sets a dispute period.
A proposer posts a bond and submits the data.
If no one disputes the data within the dispute period, the data is finalized, and the proposer gets their bond back.
If a dispute arises, the disputer posts a bond equal to the proposer’s bond and escalates the dispute to the DVM.
UMA token holders resolve the dispute within 48 hours. If the disputer is correct, they receive the proposer's bond as a reward, and vice versa. Use Cases Apart from the obvious use cases for oracles in DeFi, UMA's optimistic oracles offer much more flexibility, as practically anything can be submitted as a data point. Here are some projects that utilize UMA's Optimistic Oracles: Polymarket Polymarket is a decentralized predictions market, one of the most prominent DeFi apps lately. On Polymarket, you can place your bets on pretty much anything — from the winner of the Presidential Elections in 2024 to how many tweets Elon Musk will post this month Sherlock Sherlock is a risk management platform designed for DeFi. They run extensive DeFi audit contests where many security researchers compete for a bug bounty. Cozy Cosy is an open-source insurance protocol that allows users to provide and receive protection against predefined conditions, like a loss of funds or smart contract hacks. The use cases are quite diverse already and with the upcoming RWA narrative, the amount of projects using UMA's OOs will only get bigger. RWA Tokenization RWA tokenization is one of the most promising opportunities in crypto. It has the potential to unlock multi-trillion dollar markets and onboard millions of people into DeFi. Major institutions are launching tokenized funds, and the role of Oracles in this market is as important as it's ever been. Blackrock's BUIDL fund uses Chainlink to track real-world assets like US Treasury bill prices, dollar yields, etc. It allows investors to purchase tokens representing shares in the fund with "safe" assets and offers unmatched liquidity. As the sector grows, the demand for fast and accurate Oracle infrastructure and reliable data will grow significantly. Protocols like Chainlink, UMA, and Pyth are well-positioned to capture the majority of this market share. Conclusion We brought smart contracts to the world; now, it's time to bring the world into smart contracts. Allowing smart contracts to interact with the outside world seems like the next logical step in blockchain development. While DeFi remains one of the most promising and straightforward ways to onboard the next billion users, there are many ways in which oracles can be used: they can provide real-world data for various applications, from financial products and insurance to gaming and supply chain management. Decentralized oracles ensure that this data is accurate and trustworthy without relying on a single point of failure, opening a world of new possibilities for the technology. I was inspired to write this blog post after reading a paper called " The Oracle Problem — Why Decentralising Everything is More Difficult than it Sounds" by Victor Hogrefe. The Oracle Problem As the title suggests, Victor argues that there are no good solutions for handling oracles on the blockchain. It may have been true six years ago when the paper was written, so kudos to Victor for proposing some potential ones back then. good solutions However, what struck me the most was that the author failed to consider that the oracles themselves can be decentralized. In this post, I'll explain why it's actually "not that difficult" to decentralize everything and how this issue has already been solved with the help of decentralized oracles. But first, let's take a small step back and learn what oracles are exactly. The Role Of Oracles Smart contracts are designed in a way to provide deterministic results. Their job is to take input, execute logic, and modify the state of the blockchain irreversibly. But the majority of events still happen off-chain. Allowing smart contracts to interact with these events has always been a double-edged sword. On one hand, this significantly increases the potential blockchain use cases but on the other —  poses serious security risks and trust issues. Oracles are here to help. They act as a bridge between blockchains and the external world and enable smart contracts to execute code based on real-world events and conditions. For example, to be able to bet on the outcome of a tennis match between Roger Federer and Novak Djokovic, you need a way to tell the smart contract who won. Since we don't live in the Metaverse yet, a smart contract can't know the outcome of the match — someone has to tell it who the winner is, so that the contract can payout to the winners. know The big question is: who will be the one to tell the smart contract who won? We would need to trust this person or entity to be correct and honest... But wait a minute... Trust? trust Trust? That's not how things work in Web3. We don't want to trust. We want trustless. trustless. Decentralized Oracles In the original paper I mentioned in the beginning, the author overlooks the possibility of oracles being decentralized and is rather focused on discussing different algorithmic solutions, weaknesses, and potential attack vectors. What he doesn't consider is that the oracles themselves can be decentralized. Decentralized oracles, unlike the normal ones, rely on multiple independent nodes to fetch and validate information. This means there's no single point of failure, making it much harder to compromise the system. By using various mechanisms, such as multiple data sources, multiple oracles, or the need to have a stake in the system, decentralized oracles can prevent different sorts of malicious attacks, data corruption, or bribery. One such mechanism has been implemented by the UMA Protocol. UMA's Optimistic Oracles UMA is a leader in the oracles space, alongside Chainlink, which is the largest oracle protocol in the world. UMA's oracle system consists of two main components: the Optimistic Oracle and the Data Verification Mechanism (DVM). The principle is straightforward: anyone can submit an answer on-chain, and a dispute arises only if the answer is incorrect. The first layer of UMA's oracle system is the Optimistic Oracle. This layer is designed to quickly verify data optimistically, meaning that all submitted statements are true by default unless challenged. The second layer is the DVM (Data Verification Mechanism), which serves as a fallback for the Optimistic Oracle by resolving disputes if they occur. The entire system is efficient and cheap because it aims to prevent disputes in the first place. Here’s how it works: A smart contract requests a piece of data and sets a dispute period. A proposer posts a bond and submits the data. If no one disputes the data within the dispute period, the data is finalized, and the proposer gets their bond back. If a dispute arises, the disputer posts a bond equal to the proposer’s bond and escalates the dispute to the DVM. UMA token holders resolve the dispute within 48 hours. If the disputer is correct, they receive the proposer's bond as a reward, and vice versa. A smart contract requests a piece of data and sets a dispute period. A proposer posts a bond and submits the data. If no one disputes the data within the dispute period, the data is finalized, and the proposer gets their bond back. If a dispute arises, the disputer posts a bond equal to the proposer’s bond and escalates the dispute to the DVM. UMA token holders resolve the dispute within 48 hours. If the disputer is correct, they receive the proposer's bond as a reward, and vice versa. Use Cases Apart from the obvious use cases for oracles in DeFi, UMA's optimistic oracles offer much more flexibility, as practically anything can be submitted as a data point. anything Here are some projects that utilize UMA's Optimistic Oracles: Polymarket Polymarket is a decentralized predictions market, one of the most prominent DeFi apps lately. On Polymarket, you can place your bets on pretty much anything — from the winner of the Presidential Elections in 2024 to how many tweets Elon Musk will post this month Sherlock Sherlock is a risk management platform designed for DeFi. They run extensive DeFi audit contests where many security researchers compete for a bug bounty. Cozy Cosy is an open-source insurance protocol that allows users to provide and receive protection against predefined conditions, like a loss of funds or smart contract hacks. The use cases are quite diverse already and with the upcoming RWA narrative, the amount of projects using UMA's OOs will only get bigger. RWA Tokenization RWA tokenization is one of the most promising opportunities in crypto. It has the potential to unlock multi-trillion dollar markets and onboard millions of people into DeFi. Major institutions are launching tokenized funds, and the role of Oracles in this market is as important as it's ever been. Blackrock's BUIDL fund uses Chainlink to track real-world assets like US Treasury bill prices, dollar yields, etc. It allows investors to purchase tokens representing shares in the fund with " safe " assets and offers unmatched liquidity. safe As the sector grows, the demand for fast and accurate Oracle infrastructure and reliable data will grow significantly. Protocols like Chainlink, UMA, and Pyth are well-positioned to capture the majority of this market share. Conclusion We brought smart contracts to the world; now, it's time to bring the world into smart contracts. Allowing smart contracts to interact with the outside world seems like the next logical step in blockchain development. While DeFi remains one of the most promising and straightforward ways to onboard the next billion users, there are many ways in which oracles can be used: they can provide real-world data for various applications, from financial products and insurance to gaming and supply chain management. Decentralized oracles ensure that this data is accurate and trustworthy without relying on a single point of failure, opening a world of new possibilities for the technology.

The Oracle Solution: Why Decentralizing Everything Is Less Difficult Than it Sounds

ওরাকল সমাধান: কেন সবকিছুর বিকেন্দ্রীকরণ শোনার চেয়ে কম কঠিন

Die Oracle-Lösung: Warum die Dezentralisierung des Ganzen weniger schwierig ist, als es klingt

La solución de Oracle: por qué descentralizar todo es menos difícil de lo que parece

La solution Oracle : pourquoi tout décentraliser est moins difficile qu'il n'y paraît

ऑरेकल समाधान: सब कुछ विकेंद्रीकृत करना जितना लगता है उससे कम कठिन क्यों है

Oracle ソリューション: すべてを分散化することが思ったほど難しくない理由

Oracle 솔루션: 모든 것을 분산화하는 것이 생각보다 덜 어려운 이유

A solução Oracle: por que descentralizar tudo é menos difícil do que parece

Решение Oracle: почему децентрализация всего проще, чем кажется

Oracle Çözümü: Her Şeyi Merkezi Olmayan Hale Getirmek Neden Sanıldığından Daha Kolaydır?

Giải pháp của Oracle: Tại sao việc phân cấp mọi thứ lại ít khó khăn hơn bạn tưởng

预言机解决方案：为何去中心化一切并没有听起来那么困难

Supra, a leading provider of verifiable randomness services and oracle data feeds across over 80 blockchains announced its integration with ApeChain. As a result, Supra is the first protocol to use verifiable randomness and oracle price feeds on the new Layer 3 on Arbitrum. GameFi, DeFi, and other decentralised applications on ApeChain will benefit from improved real-time data accessibility, enhanced functionality, and expedited decision-making thanks to Supra's oracle price feeds protocol, the Distributed Oracle Agreement (DORA). Supra's decentralised Verifiable Random Function (dVRF) will also produce verifiable and decentralised randomness for ApeChain dApps, guaranteeing the integrity of random results in prize draws, blockchain games, and other situations where complete transparency is necessary to uphold confidence.Supra is excited to announce its integration with ApeChain. Supra is a leading provider of verifiable randomness services and oracle data feeds across over 80 blockchains. As a result, Supra is the first protocol to use verifiable randomness and oracle price feeds on the new Layer 3 on Arbitrum. Delivering Essential Data to dApps Supra's novel oracle data feeds significantly improve the possibilities of smart contracts by offering safe access to outside data that Web3 dApps require. With more than 475 active price feeds and counting, DORA is built to effectively validate and transmit real-world data to deterministic blockchain networks. Delivering comprehensive security guarantees together with high-quality price feeds is ensured by its resilience to Byzantine corruption, protection against potential node collusion, and Layer-1 grade security. Supra accommodates the various requirements of dApps by supporting both push and pull models. Supra provides robust security assurances and remarkable performance speeds for its data streams, all powered by the Supra Moonshot Consensus protocol. The Moonshot Consensus system, with 500 millisecond optimistic finality and roughly 530K transactions per second throughput, was tested extensively throughout the world. Ensuring Trust with Verifiable On-Chain Randomness Supra's dVRF protocol, which builds on DORA's advantages, uses decentralised, verifiable randomness to meet the requirement for unpredictable outcomes in dApps. For Web3 game developers, who need to ensure the integrity and unpredictable nature of random results in situations such as competition matchups and prize draws, this is essential. By enabling dApps to produce easily verifiable random outcomes, Supra's on-chain verifiable randomness generator contributes to increased community trust. ApeChain: Setting New Standards for GameFi Built on Arbitrum, ApeChain is a specialised Layer 3 solution intended to serve as the cornerstone of the Ape community and foster the expansion of ApeCoin. Located where NFTs and gaming converge, ApeChain's specialised infrastructure will support many new games and protocols inside the ApeCoin ecosystem, guaranteeing a seamless and effective gaming experience. GameFi and metaverse decentralised apps have shown a great deal of interest in ApeChain, which has raised the need for trustworthy data oracles that offer up-to-date off-chain data. To guarantee fairness, gaming apps also need verifiable on-chain randomness. Game developers using ApeChain may create more immersive experiences with improved performance by utilising Supra's dVRF and oracle data feeds. “Supra is pioneering solutions with integrations across all major ecosystems and will now empower ApeChain through Bridges, Oracles, Automation, and Randomizers. The ApeCoin DAO eagerly anticipates the innovative creations that builders will craft, leveraging Supra’s best-in-class stack for games, DeFi, and beyond!” — Hervé Larren, ApeCoin DAO Special Council and co-author of ApeChain. ApeChain wants to speed up the widespread use of GameFi by collaborating with Supra to provide more dependable data and foster trust through outcomes that are assured to be verifiably fair. What Is Supra Supra is a top vendor of verifiable randomness services and oracle price feeds across more than 80 blockchains. Supra works as an vertically integrated L1, offering robust security guarantees along with high-quality, low-latency data and randomness across Web 3. It is compatible with MoveVM chains, Bitcoin L2s, EVM L1s, L2s, and L3s dApps. With an emphasis on scalability, security, and quick transactions, Supra offers a full developer toolkit along with in-depth manuals and technical whitepapers. Accompany Supra on its journey to see its expansion, creativity, and engagement with the community. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Supra , a leading provider of verifiable randomness services and oracle data feeds across over 80 blockchains announced its integration with ApeChain. As a result, Supra is the first protocol to use verifiable randomness and oracle price feeds on the new Layer 3 on Arbitrum. Supra GameFi, DeFi, and other decentralised applications on ApeChain will benefit from improved real-time data accessibility, enhanced functionality, and expedited decision-making thanks to Supra's oracle price feeds protocol, the Distributed Oracle Agreement (DORA). Supra's decentralised Verifiable Random Function (dVRF) will also produce verifiable and decentralised randomness for ApeChain dApps, guaranteeing the integrity of random results in prize draws, blockchain games, and other situations where complete transparency is necessary to uphold confidence.Supra is excited to announce its integration with ApeChain. Supra is a leading provider of verifiable randomness services and oracle data feeds across over 80 blockchains. As a result, Supra is the first protocol to use verifiable randomness and oracle price feeds on the new Layer 3 on Arbitrum. ApeChain ApeChain Delivering Essential Data to dApps Supra's novel oracle data feeds significantly improve the possibilities of smart contracts by offering safe access to outside data that Web3 dApps require. With more than 475 active price feeds and counting, DORA is built to effectively validate and transmit real-world data to deterministic blockchain networks. Delivering comprehensive security guarantees together with high-quality price feeds is ensured by its resilience to Byzantine corruption, protection against potential node collusion, and Layer-1 grade security. Supra accommodates the various requirements of dApps by supporting both push and pull models. Supra provides robust security assurances and remarkable performance speeds for its data streams, all powered by the Supra Moonshot Consensus protocol. The Moonshot Consensus system, with 500 millisecond optimistic finality and roughly 530K transactions per second throughput, was tested extensively throughout the world. Ensuring Trust with Verifiable On-Chain Randomness Supra's dVRF protocol, which builds on DORA's advantages, uses decentralised, verifiable randomness to meet the requirement for unpredictable outcomes in dApps. For Web3 game developers, who need to ensure the integrity and unpredictable nature of random results in situations such as competition matchups and prize draws, this is essential. By enabling dApps to produce easily verifiable random outcomes, Supra's on-chain verifiable randomness generator contributes to increased community trust. ApeChain: Setting New Standards for GameFi Built on Arbitrum, ApeChain is a specialised Layer 3 solution intended to serve as the cornerstone of the Ape community and foster the expansion of ApeCoin. Located where NFTs and gaming converge, ApeChain's specialised infrastructure will support many new games and protocols inside the ApeCoin ecosystem, guaranteeing a seamless and effective gaming experience. GameFi and metaverse decentralised apps have shown a great deal of interest in ApeChain, which has raised the need for trustworthy data oracles that offer up-to-date off-chain data. To guarantee fairness, gaming apps also need verifiable on-chain randomness. Game developers using ApeChain may create more immersive experiences with improved performance by utilising Supra's dVRF and oracle data feeds. “Supra is pioneering solutions with integrations across all major ecosystems and will now empower ApeChain through Bridges, Oracles, Automation, and Randomizers. The ApeCoin DAO eagerly anticipates the innovative creations that builders will craft, leveraging Supra’s best-in-class stack for games, DeFi, and beyond!” “Supra is pioneering solutions with integrations across all major ecosystems and will now empower ApeChain through Bridges, Oracles, Automation, and Randomizers. The ApeCoin DAO eagerly anticipates the innovative creations that builders will craft, leveraging Supra’s best-in-class stack for games, DeFi, and beyond!” — Hervé Larren, ApeCoin DAO Special Council and co-author of ApeChain. ApeChain wants to speed up the widespread use of GameFi by collaborating with Supra to provide more dependable data and foster trust through outcomes that are assured to be verifiably fair. What Is Supra Supra is a top vendor of verifiable randomness services and oracle price feeds across more than 80 blockchains. Supra works as an Supra Supra vertically integrated L1, offering robust security guarantees along with high-quality, low-latency data and randomness across Web 3. It is compatible with MoveVM chains, Bitcoin L2s, EVM L1s, L2s, and L3s dApps. With an emphasis on scalability, security, and quick transactions, Supra offers a full developer toolkit along with in-depth manuals and technical whitepapers . Accompany Supra on its journey to see its expansion, creativity, and engagement with the community. in-depth manuals in-depth manuals technical whitepapers technical whitepapers Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program

Supra Integrates First Ever Oracle Data Feed and Verifiable Randomness on ApeChain

ApeChain-এ সুপ্রা প্রথম ওরাকল ডেটা ফিড এবং যাচাইযোগ্য এলোমেলোতা একীভূত করে

Supra integriert den ersten Oracle-Datenfeed und verifizierbare Zufälligkeit auf ApeChain

Supra integra la primera fuente de datos de Oracle y aleatoriedad verificable en ApeChain

Supra intègre le tout premier flux de données Oracle et le caractère aléatoire vérifiable sur ApeChain

सुप्रा ने एपचेन पर पहली बार ऑरेकल डेटा फीड और सत्यापन योग्य रैंडमनेस को एकीकृत किया

Supra、ApeChainで初のOracleデータフィードと検証可能なランダム性を統合

Supra는 ApeChain에 최초의 Oracle 데이터 피드와 검증 가능한 무작위성을 통합합니다.

Supra integra o primeiro feed de dados Oracle e aleatoriedade verificável no ApeChain

Supra интегрирует первый в мире поток данных Oracle и проверяемую случайность в ApeChain

Supra, ApeChain'e İlk Oracle Veri Beslemesini ve Doğrulanabilir Rastgeleliği Entegre Ediyor

Supra tích hợp nguồn cấp dữ liệu Oracle đầu tiên và tính ngẫu nhiên có thể xác minh được trên ApeChain

Supra 在 ApeChain 上集成首个 Oracle 数据源和可验证随机性

This is the second part of the trilogy focusing on performance evaluation infrastructure for conversational AI agents. Part 1 - Metrics: Swallow the Red Pill
Part 2 - Metrics Reloaded: The Oracle
Part 3 - The Metrics Revolution: Scaling Quick Recap In case you have not read the first part of this trilogy, we focused on some high level questions of what and why about metrics needed to ensure end user performance for an AI agent. Here is a summary: User Perceived Metrics and User Reported Metrics form the foundation for a highly reliable conversational assistant.


Reliability and Latency are two different aspects to evaluate end user performance for conversational agents.


Never fully trust a metric - always question negative and positive movement in a metric.


It is crucial to identify these metrics from early development stage to objectively measure the performance of an AI agent. In this article, we will focus on how to obtain these metrics in a manner that is easy to use, accurate and actionable. The Oracle We hope there was a “oracle” which could provide highly accurate end user performance metrics. Guess what? There is! We as humans are extremely good at doing this. However this comes as a cost of efficiency. The amount of data points are less but highly confident. We will discuss some ways to mitigate this gap. Human Testing: This can be the QA team or developers or PMs or executives testing the product. It is important to realize the value for this data - is truly the “golden dataset” for metrics. This also shows that there is no replacement for testing your product manually.


Automated Lab Testing: There can be test benches setup where a different software analyzes automated testing via audio and visual processing. This helps us increase coverage for the “golden dataset” metrics. There should be infrastructure in place to analyze these data points and referred to as the “ground truth”. The Next Best Thing While ground truth provides highly confident set of metrics, it cannot replicate all the conditions that might be occur for a real user in production. Note that this might have lower confidence but is needed to uncover unanticipated issues. Hence, there is a need to invest in ensuring we have logging signals in place for production metrics. There are few things to be cautious of for production logging. Privacy and security implications must be kept in mind This is pretty much self-explanatory but all production logs should be aggregated and anonymized to protect against any privacy and security issues. Log only what is needed On the second point, it is important to note that success metrics need to be decided beforehand and then the corresponding logs need to be identified from that. It is easy to just add a lot of logging and then determine the metrics we can derive. This actually ends up polluting the metrics making it less objective and only ends up measuring the metrics we can based on available logs. The other drawback for logging a lot is that it can end up affecting user behavior, causing performance degradation. Keep Logging simple It is important to note that while metrics should drive what logs are needed, logs should not try to derive metrics. In other words, logging should just capture what event happened and when. The derivation should happen on the metric processing side and not during the user interaction. This helps to keep logging and metric derivation orthogonal - single responsibility :) Keeping logging simple also helps with reducing unnecessary complexity in production code which can result in unexpected errors and lead to performance degradation. Putting everything together The two types of metric collection processes we discussed here are complementary to each other. Production metrics have high coverage but lower confidence.


Ground truth metrics have low coverage but high confidence. As a result, both of these should be used together to create a highly reliable and fast conversational agent. For any new changes (user facing or not), both the metric systems should be used to verify if there is any degradation in end user performance. The metric collection processes should aim to improve each other: Production metrics should be validated against “ground truth” metrics. A lot of deviation suggests issues with production logging or metric instrumentation pipeline. Issues captured by production metrics that have not been flagged by “ground truth” metrics reveal gaps in human or semi-automated metric pipeline. These can be used to add new manual or semi-automated tests to improve the coverage for “ground truth” metrics. High Level Takeaways Ground truth and production metrics complement each others for ensuring performance.

These two metric pipeline should be used to improve each other.



Metric collection from production should not affect degrading performance.

Metrics should dictate what logs needed to be added.
Logs should be harmless and simple.
Metrics derivation and logs should be orthogonal. What’s Next? As our conversation AI agent scales across different devices - phones, tablets, cars, earphones - it is becomes vital that the performance evaluation infrastructure can also scale seamlessly. We discuss more details on scaling performance metrics infrastructure in the final part of the trilogy - stay tuned! This is the second part of the trilogy focusing on performance evaluation infrastructure for conversational AI agents. Part 1 - Metrics: Swallow the Red Pill Part 2 - Metrics Reloaded: The Oracle Part 3 - The Metrics Revolution: Scaling Part 1 - Metrics: Swallow the Red Pill Metrics: Swallow the Red Pill Part 2 - Metrics Reloaded: The Oracle Metrics Reloaded: The Oracle Part 3 - The Metrics Revolution: Scaling The Metrics Revolution: Scaling Quick Recap In case you have not read the first part of this trilogy, we focused on some high level questions of what and why about metrics needed to ensure end user performance for an AI agent. what and why what and why Here is a summary: User Perceived Metrics and User Reported Metrics form the foundation for a highly reliable conversational assistant. Reliability and Latency are two different aspects to evaluate end user performance for conversational agents. Never fully trust a metric - always question negative and positive movement in a metric. It is crucial to identify these metrics from early development stage to objectively measure the performance of an AI agent. User Perceived Metrics and User Reported Metrics form the foundation for a highly reliable conversational assistant. User Perceived Metrics and User Reported Metrics form the foundation for a highly reliable conversational assistant. User Perceived Metrics User Perceived Metrics User Reported Metrics User Reported Metrics Reliability and Latency are two different aspects to evaluate end user performance for conversational agents. Reliability and Latency are two different aspects to evaluate end user performance for conversational agents. Reliability and Latency Reliability and Latency Never fully trust a metric - always question negative and positive movement in a metric. Never fully trust a metric - always question negative and positive movement in a metric. Never fully trust a metric Never fully trust a metric It is crucial to identify these metrics from early development stage to objectively measure the performance of an AI agent. It is crucial to identify these metrics from early development stage to objectively measure the performance of an AI agent. In this article, we will focus on how to obtain these metrics in a manner that is easy to use, accurate and actionable. how to obtain these metrics in a manner that is easy to use, accurate and actionable. how to obtain these metrics in a manner that is easy to use, accurate and actionable. The Oracle We hope there was a “oracle” which could provide highly accurate end user performance metrics. Guess what? There is! We as humans are extremely good at doing this. However this comes as a cost of efficiency . The amount of data points are less but highly confident . We will discuss some ways to mitigate this gap. a cost of efficiency data points are less but highly confident data points are less but highly confident Human Testing: This can be the QA team or developers or PMs or executives testing the product. It is important to realize the value for this data - is truly the “golden dataset” for metrics. This also shows that there is no replacement for testing your product manually. Automated Lab Testing: There can be test benches setup where a different software analyzes automated testing via audio and visual processing. This helps us increase coverage for the “golden dataset” metrics. Human Testing: This can be the QA team or developers or PMs or executives testing the product. It is important to realize the value for this data - is truly the “golden dataset” for metrics. This also shows that there is no replacement for testing your product manually. Human Testing: This can be the QA team or developers or PMs or executives testing the product. It is important to realize the value for this data - is truly the “golden dataset” for metrics. This also shows that there is no replacement for testing your product manually. Human Testing: Automated Lab Testing: There can be test benches setup where a different software analyzes automated testing via audio and visual processing. This helps us increase coverage for the “golden dataset” metrics. Automated Lab Testing: There can be test benches setup where a different software analyzes automated testing via audio and visual processing. This helps us increase coverage for the “golden dataset” metrics. Automated Lab Testing: There should be infrastructure in place to analyze these data points and referred to as the “ground truth”. There should be infrastructure in place to analyze these data points and referred to as the “ground truth”. There should be infrastructure in place to analyze these data points and referred to as the “ground truth”. “ground truth”. The Next Best Thing While ground truth provides highly confident set of metrics, it cannot replicate all the conditions that might be occur for a real user in production. Note that this might have lower confidence but is needed to uncover unanticipated issues. Hence, there is a need to invest in ensuring we have logging signals in place for production metrics. There are few things to be cautious of for production logging. Privacy and security implications must be kept in mind This is pretty much self-explanatory but all production logs should be aggregated and anonymized to protect against any privacy and security issues. Log only what is needed On the second point, it is important to note that success metrics need to be decided beforehand and then the corresponding logs need to be identified from that . It is easy to just add a lot of logging and then determine the metrics we can derive. This actually ends up polluting the metrics making it less objective and only ends up measuring the metrics we can based on available logs. metrics need to be decided beforehand and then the corresponding logs need to be identified from that The other drawback for logging a lot is that it can end up affecting user behavior, causing performance degradation. Keep Logging simple It is important to note that while metrics should drive what logs are needed, logs should not try to derive metrics. In other words, logging should just capture what event happened and when. The derivation should happen on the metric processing side and not during the user interaction. This helps to keep logging and metric derivation orthogonal - single responsibility :) logs should not try to derive metrics. This helps to keep logging and metric derivation orthogonal - single responsibility Keeping logging simple also helps with reducing unnecessary complexity in production code which can result in unexpected errors and lead to performance degradation. Putting everything together The two types of metric collection processes we discussed here are complementary to each other. Production metrics have high coverage but lower confidence. Ground truth metrics have low coverage but high confidence. Production metrics have high coverage but lower confidence. Production metrics have high coverage but lower confidence. Ground truth metrics have low coverage but high confidence. Ground truth metrics have low coverage but high confidence. As a result, both of these should be used together to create a highly reliable and fast conversational agent. For any new changes (user facing or not), both the metric systems should be used to verify if there is any degradation in end user performance. The metric collection processes should aim to improve each other: Production metrics should be validated against “ground truth” metrics. A lot of deviation suggests issues with production logging or metric instrumentation pipeline. Production metrics should be validated against “ground truth” metrics. A lot of deviation suggests issues with production logging or metric instrumentation pipeline. “ground truth” “ground truth” Issues captured by production metrics that have not been flagged by “ground truth” metrics reveal gaps in human or semi-automated metric pipeline. These can be used to add new manual or semi-automated tests to improve the coverage for “ground truth” metrics. Issues captured by production metrics that have not been flagged by “ground truth” metrics reveal gaps in human or semi-automated metric pipeline. These can be used to add new manual or semi-automated tests to improve the coverage for “ground truth” metrics. “ground truth” “ground truth” High Level Takeaways Ground truth and production metrics complement each others for ensuring performance.

These two metric pipeline should be used to improve each other. Metric collection from production should not affect degrading performance.

Metrics should dictate what logs needed to be added.
Logs should be harmless and simple.
Metrics derivation and logs should be orthogonal. Ground truth and production metrics complement each others for ensuring performance. These two metric pipeline should be used to improve each other. Ground truth and production metrics complement each others for ensuring performance. These two metric pipeline should be used to improve each other. These two metric pipeline should be used to improve each other. Metric collection from production should not affect degrading performance. Metrics should dictate what logs needed to be added.
Logs should be harmless and simple.
Metrics derivation and logs should be orthogonal. Metric collection from production should not affect degrading performance. Metrics should dictate what logs needed to be added. Logs should be harmless and simple. Metrics derivation and logs should be orthogonal. Metrics should dictate what logs needed to be added. Logs should be harmless and simple. Metrics derivation and logs should be orthogonal. What’s Next? As our conversation AI agent scales across different devices - phones, tablets, cars, earphones - it is becomes vital that the performance evaluation infrastructure can also scale seamlessly. We discuss more details on scaling performance metrics infrastructure in the final part of the trilogy - stay tuned!

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