PythRoadmapand
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Learn to earn coins (complete questions and get 5.2 pyth for free) limited quantity, first come first served
First find learning to earn coins
Click to enter and then click to start learning
By simple learning, answer 10 questions correctly
You can get token rewards
Limited quantity, first come first served
!!!!!! Hope this helps everyone, move your little hands to give me some attention, the comment area can be used to exchange answers and insights.!!!!!!
Click to enter and then click to start learning
By simple learning, answer 10 questions correctly
You can get token rewards
Limited quantity, first come first served
!!!!!! Hope this helps everyone, move your little hands to give me some attention, the comment area can be used to exchange answers and insights.!!!!!!
豪94:
学习赚币先到先得
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$PYTH just announced cooperation with the U.S. Department of Commerce! The night before a surge?
$PYTH Breaking the stereotype that 'oracles are just data movers' with strength! Three core advancements prove it has outpaced several competitors:
In collaboration with the U.S. Department of Commerce
- Directly bringing core macro data like GDP and CPI onto the blockchain
- Institutional-level data sources open to the DeFi world for the first time
- The bridge between traditional finance and the crypto world has officially opened
Locked in $5.3 billion for the second quarter
- Staking demand surges, real funds vote with their feet
- Protocol revenue continuously supports ecological builders
- Coin #PythRoadmap and economics enter a positive cycle
In collaboration with the U.S. Department of Commerce
- Directly bringing core macro data like GDP and CPI onto the blockchain
- Institutional-level data sources open to the DeFi world for the first time
- The bridge between traditional finance and the crypto world has officially opened
Locked in $5.3 billion for the second quarter
- Staking demand surges, real funds vote with their feet
- Protocol revenue continuously supports ecological builders
- Coin #PythRoadmap and economics enter a positive cycle
shouruopanghu:
合作的不是人家link？
🔮 Майбутнє фінансів неможливе без якісних даних.
@Pyth Network пропонує рішення, яке поєднує інституційну якість та децентралізований підхід.
#PythRoadmapand передбачає впровадження моделей доходу та DAO для стійкого зростання.
$PYTH забезпечує участь, стимулювання та розподіл прибутку 🌐
@Pyth Network пропонує рішення, яке поєднує інституційну якість та децентралізований підхід.
#PythRoadmapand передбачає впровадження моделей доходу та DAO для стійкого зростання.
$PYTH забезпечує участь, стимулювання та розподіл прибутку 🌐
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U.S. GDP on-chain ignites market! @Pythnetwork's triple moat disrupts $500 billion market data landscape
When the U.S. Department of Commerce writes quarterly GDP data onto nine public blockchains such as Bitcoin and Ethereum through @Pythnetwork, this seemingly routine technical collaboration actually marks a paradigm shift in the decentralized oracle industry. As the first Web3 project to receive national-level economic data endorsement, Pyth Network is dismantling the monopoly of traditional data service providers with its triple moat built on institutional-grade data sources, innovative technology architecture, and self-reinforcing economic model, redefining the production and circulation rules of global market data.
1. Data Source Revolution: From "second-hand transportation" to "first-hand direct supply" paradigm leap
1. Data Source Revolution: From "second-hand transportation" to "first-hand direct supply" paradigm leap
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Not just making money from institutions! Pyth's third phase aims to be the "only source of truth for global finance".
If the second phase of Pyth is to "knock on the door of traditional finance", then the third phase is to "lay out a data network in every corner of the global financial landscape". From #PythRoadmap, it can be seen that its ambition goes far beyond making money through institutional subscriptions — the ultimate goal is to make
it the "data benchmark" recognized by all markets, whether it's on-chain DeFi, Wall Street banks, or newly emerging asset tracks, as long as price data is needed, the first thought is Pyth.
Let's first discuss how Pyth plans to "expand its plate" after the second phase.
First, asset categories need to "break boundaries". Currently, Pyth has covered cryptocurrencies, stocks, foreign exchange, and commodities, which seems quite a lot, but the third phase aims to go further — derivatives (such as real-time premium data for futures and options), fixed income (like yields on government bonds and corporate bonds), real estate (which may even include the tokenized prices of a specific office building or a piece of land), and those "new assets" that are not yet defined will all be pulled into its data pool. What does this mean? Previously, one could only play with crypto on-chain, but in the future, Pyth will provide real-time prices for certain private equity bonds; traditional banks wanting to engage in real estate tokenization do not need to research market prices themselves, they can simply use Pyth's data source. As the asset categories expand, Pyth's "applicable scenarios" change from the "crypto circle" to the "whole financial circle".
it the "data benchmark" recognized by all markets, whether it's on-chain DeFi, Wall Street banks, or newly emerging asset tracks, as long as price data is needed, the first thought is Pyth.
Let's first discuss how Pyth plans to "expand its plate" after the second phase.
First, asset categories need to "break boundaries". Currently, Pyth has covered cryptocurrencies, stocks, foreign exchange, and commodities, which seems quite a lot, but the third phase aims to go further — derivatives (such as real-time premium data for futures and options), fixed income (like yields on government bonds and corporate bonds), real estate (which may even include the tokenized prices of a specific office building or a piece of land), and those "new assets" that are not yet defined will all be pulled into its data pool. What does this mean? Previously, one could only play with crypto on-chain, but in the future, Pyth will provide real-time prices for certain private equity bonds; traditional banks wanting to engage in real estate tokenization do not need to research market prices themselves, they can simply use Pyth's data source. As the asset categories expand, Pyth's "applicable scenarios" change from the "crypto circle" to the "whole financial circle".
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Is the era of disrupting the Bloombergs here? What gives @Pythnetwork the right to pioneer the future of decentralized market data?
While traditional financial institutions are still paying exorbitant fees for delayed and expensive market data, @Pythnetwork is reconstructing the entire industry landscape with decentralized logic. From DeFi infrastructure to targeting a global market data track worth over $50 billion, its clear evolutionary path and underlying innovations are proving that it is far from an ordinary oracle project—rather, it aims to become the "disruptor" that defines the future rules of market data.
Vision anchor point: the leap from DeFi to a trillion-dollar market
Pyth's ambition has exceeded the positioning of "on-chain data movers" from the very beginning. Initially starting from the Solana ecosystem, it addressed the urgent need for high-frequency, accurate price data in the DeFi space, supporting over $1.6 trillion in transaction volume and validating the feasibility of a decentralized data model. But this is just the prologue; the #PythRoadmap has long been clear: to penetrate the global market data industry monopolized by giants like Bloomberg and Reuters from the vertical scenarios of the crypto circle.
Vision anchor point: the leap from DeFi to a trillion-dollar market
Pyth's ambition has exceeded the positioning of "on-chain data movers" from the very beginning. Initially starting from the Solana ecosystem, it addressed the urgent need for high-frequency, accurate price data in the DeFi space, supporting over $1.6 trillion in transaction volume and validating the feasibility of a decentralized data model. But this is just the prologue; the #PythRoadmap has long been clear: to penetrate the global market data industry monopolized by giants like Bloomberg and Reuters from the vertical scenarios of the crypto circle.
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Pyth Network: The Disruptor in the Oracle Track and Future Challenges
In the context of the explosive growth of decentralized finance (DeFi), oracles, as a key infrastructure connecting the on-chain and off-chain worlds, are experiencing unprecedented development opportunities. Pyth Network, with its innovative technical architecture and unique market positioning, stands out in fierce competition and has become the focus of industry attention. This article will comprehensively analyze the development prospects of Pyth Network from five dimensions: technical advantages, market performance, ecological layout, competitive landscape, and potential risks.
Technical innovation builds core barriers
Pyth Network's technical architecture has achieved multiple groundbreaking innovations in the oracle field, laying a solid foundation for its long-term development. Its core advantages are concentrated in three aspects: data acquisition, transmission efficiency, and cross-chain compatibility.
Technical innovation builds core barriers
Pyth Network's technical architecture has achieved multiple groundbreaking innovations in the oracle field, laying a solid foundation for its long-term development. Its core advantages are concentrated in three aspects: data acquisition, transmission efficiency, and cross-chain compatibility.
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From DeFi Infrastructure to Global Data Giant: The Rise of Pyth Network
In the blockchain oracle track, the development trajectory of Pyth Network can be described as a revolutionary movement that disrupts the traditional data distribution model. From its conceptual prototype in 2021 to now targeting a $50 billion market as an industry challenger, each step in its evolution has profoundly impacted the data interaction rules between decentralized finance and traditional finance.
Seed Stage: Laying the Infrastructure (2021-2023)
The story of Pyth Network began in April 2021, when the cryptocurrency market was facing industry pain points of oracle data delays, high costs, and insufficient reliability. The founding team keenly realized that the traditional push model of oracles, which continuously broadcasts data, not only wastes network resources but also struggles to meet the demands of high-frequency trading scenarios. Based on this insight, the team established the core design philosophy of 'fetching data on demand,' laying the groundwork for the later Pull model.
Seed Stage: Laying the Infrastructure (2021-2023)
The story of Pyth Network began in April 2021, when the cryptocurrency market was facing industry pain points of oracle data delays, high costs, and insufficient reliability. The founding team keenly realized that the traditional push model of oracles, which continuously broadcasts data, not only wastes network resources but also struggles to meet the demands of high-frequency trading scenarios. Based on this insight, the team established the core design philosophy of 'fetching data on demand,' laying the groundwork for the later Pull model.
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Not just an oracle! Pyth Network supports the backbone of the next generation of finance with 'precise data'
While decentralized finance is still troubled by whether 'data is accurate and transmitted quickly', Pyth Network has long since jumped out of the 'single oracle' positioning - it relies on real-time reliable market data to connect scattered assets like digital currencies, stocks, and commodities, and has also bridged the gap between traditional finance and blockchain, slowly growing into the 'data backbone' of the global financial system.
To support this backbone, Pyth's core strength lies in its 'broad and reliable data coverage'. It does not engage in minor skirmishes but directly connects with over 120 leading data providers, capturing everything from real-time cryptocurrency prices, to fluctuations in tokenized stocks, to commodities like gold and oil, and even exchange rates for currency pairs, all in real time. Moreover, this data is not limited to a specific chain; over 50 blockchains can utilize its price feeds - whether you are lending on Ethereum or trading derivatives on Solana, you can obtain unified and accurate price data without worrying about the 'inconsistency of on-chain and off-chain data'. For traders, this means less risk of misjudgment; for developers, it eliminates the need to connect with multiple data sources, saving significant adaptation costs.
To support this backbone, Pyth's core strength lies in its 'broad and reliable data coverage'. It does not engage in minor skirmishes but directly connects with over 120 leading data providers, capturing everything from real-time cryptocurrency prices, to fluctuations in tokenized stocks, to commodities like gold and oil, and even exchange rates for currency pairs, all in real time. Moreover, this data is not limited to a specific chain; over 50 blockchains can utilize its price feeds - whether you are lending on Ethereum or trading derivatives on Solana, you can obtain unified and accurate price data without worrying about the 'inconsistency of on-chain and off-chain data'. For traders, this means less risk of misjudgment; for developers, it eliminates the need to connect with multiple data sources, saving significant adaptation costs.
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The Disruptor of the Oracle Track: Pyth Network's Triple Growth Engine and Concerns
In the competition for decentralized financial infrastructure, oracles, as key hubs connecting the on-chain and off-chain worlds, are迎来新一轮变革浪潮. Pyth Network, with its unique first-party data model and high-frequency trading adaptability, has rapidly emerged as an industry dark horse in just two years. The current project is at a critical stage of transitioning from DeFi to TradFi, with development prospects that hold the enormous potential to disrupt a $50 billion data market, while also facing the dual challenges of industry competition and regulatory environment. This article will analyze Pyth Network's core competitiveness and future challenges from three dimensions: technical barriers, market expansion, and commercial monetization.
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PYTH Coin (PYTH) is the native token of the Pyth Network oracle, a project known as a "blockchain information relay station," which aims to penetrate the global market data industry worth over $50 billion, leveraging advantages accumulated from DeFi (decentralized finance) to create a "data infrastructure" that connects on-chain and reality. First, let's understand its starting point: in the DeFi field, PYTH has long been a "necessary tool." The blockchain itself cannot directly obtain real-world price data, while DeFi's lending and derivatives trading rely on accurate data—such as lending platforms needing to calculate the value of collateral in real time, and derivatives platforms needing to keep up with asset price fluctuations. Pyth Network precisely addresses this issue: it does not seek intermediaries, directly obtaining "first-hand data" from over 90 top exchanges and market makers like Binance and Jane Street, and then aggregates trustworthy prices through a unique algorithm, updating every 400 milliseconds, which is much faster than traditional oracles. Platforms like Drift Protocol for derivatives and Solend for lending on Solana rely on its high-frequency data to ensure transactions and settlements are error-free. The PYTH token acts as the "lubricant" for this ecosystem: data providers can use it as rewards, users pay data fees with it, and holders can vote to decide the development direction of the protocol, supporting the operation of DeFi scenarios.
However, Pyth's ambition extends beyond DeFi. The global market data industry is worth over $50 billion but has many pain points: traditional service providers have high data latency, expensive fees, and are easily manipulated by centralized institutions. Pyth aims to reconstruct this market using the "decentralized magic" of blockchain—its "pull model" updates data only when users need it, saving a significant amount of costs; the transparency of blockchain can ensure data is immutable, solving the industry's most pressing trust issues.
Now, this expansion has already made substantial progress. In the traditional financial sector, it has partnered with the digital bank Revolut, which has 45 million users, to integrate the latter's price data into the on-chain ecosystem; it has also teamed up with Swiss crypto bank Amina to provide real-time pricing services, and has even caught the attention of tech giants like Sony to collaborate on data services for blockchain test networks. These partnerships are no longer limited to crypto assets,
@PythNetwork #PythRoadmapand
$PYTH
However, Pyth's ambition extends beyond DeFi. The global market data industry is worth over $50 billion but has many pain points: traditional service providers have high data latency, expensive fees, and are easily manipulated by centralized institutions. Pyth aims to reconstruct this market using the "decentralized magic" of blockchain—its "pull model" updates data only when users need it, saving a significant amount of costs; the transparency of blockchain can ensure data is immutable, solving the industry's most pressing trust issues.
Now, this expansion has already made substantial progress. In the traditional financial sector, it has partnered with the digital bank Revolut, which has 45 million users, to integrate the latter's price data into the on-chain ecosystem; it has also teamed up with Swiss crypto bank Amina to provide real-time pricing services, and has even caught the attention of tech giants like Sony to collaborate on data services for blockchain test networks. These partnerships are no longer limited to crypto assets,
@PythNetwork #PythRoadmapand
$PYTH
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$50 billion market disruptor: Pyth Network's ambitions and layout in the second phase
When traditional financial data giants are still relying on regional barriers and price monopolies to harvest institutions, Pyth Network has quietly knocked on the door of reconstructing the $50 billion market data track with a second-phase expansion blueprint. Unlike the first phase of building infrastructure in the DeFi field, this time Pyth is targeting the ecological gap between TradFi and Web3, attempting to rewrite the power landscape of financial data with a combination of 'institution-grade products + token economic upgrades'.
Core Objective: To tackle the tough nut of TradFi
The core ambition of Pyth's second phase is to break the monopoly barriers of traditional market data providers. Currently, the global market data industry has an annual scale exceeding $50 billion, yet it is firmly controlled by a few giants—who have raised prices by over 50% in three years, with pricing differences for the same product reaching up to five times, and artificially splitting data access paths by region and asset class. What Pyth aims to do is to tear open a gap in this closed market using the advantages of a decentralized network.
Core Objective: To tackle the tough nut of TradFi
The core ambition of Pyth's second phase is to break the monopoly barriers of traditional market data providers. Currently, the global market data industry has an annual scale exceeding $50 billion, yet it is firmly controlled by a few giants—who have raised prices by over 50% in three years, with pricing differences for the same product reaching up to five times, and artificially splitting data access paths by region and asset class. What Pyth aims to do is to tear open a gap in this closed market using the advantages of a decentralized network.
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Today, I would like to introduce Pythnetwork, a highly promising token.
The Pyth network handles an enormous amount of data daily, covering over 60 chains and serving more than 400 applications, responding to billions of requests every day. In such a vast system, the PYTH token incentive becomes key to ensuring data quality and network stability.
Every price update and data verification triggers on-chain token settlement. Data providers are rewarded for submitting accurate data, and governance participants can also participate in decision-making through tokens, creating positive feedback. This is akin to an automatically operating "quality control system"; as long as there are token incentives, nodes are motivated to continuously provide highly trustworthy, low-latency data.
When a data source is abnormal, verification nodes will quickly intervene to correct it, and rewards will also tilt towards high-quality data. Institutional users pay for data subscriptions with $PYTH , further driving token demand and circulation, enhancing ecological vitality.
This mechanism not only reduces network risk but also builds a symbiotic relationship where "the higher the data credibility, the more stable the token value." In the long run, token incentives promote continuous network expansion and create a closed-loop ecosystem with stronger risk resistance.
In summary, $PYTH incentives tightly integrate economic behavior with technical operations, allowing Pyth to maintain high reliability in cross-chain applications, DeFi, and institutional services, achieving the dual goals of data stability and ecological efficiency.
@Pyth Network #PythRoadmapand
$PYTH
The Pyth network handles an enormous amount of data daily, covering over 60 chains and serving more than 400 applications, responding to billions of requests every day. In such a vast system, the PYTH token incentive becomes key to ensuring data quality and network stability.
Every price update and data verification triggers on-chain token settlement. Data providers are rewarded for submitting accurate data, and governance participants can also participate in decision-making through tokens, creating positive feedback. This is akin to an automatically operating "quality control system"; as long as there are token incentives, nodes are motivated to continuously provide highly trustworthy, low-latency data.
When a data source is abnormal, verification nodes will quickly intervene to correct it, and rewards will also tilt towards high-quality data. Institutional users pay for data subscriptions with $PYTH , further driving token demand and circulation, enhancing ecological vitality.
This mechanism not only reduces network risk but also builds a symbiotic relationship where "the higher the data credibility, the more stable the token value." In the long run, token incentives promote continuous network expansion and create a closed-loop ecosystem with stronger risk resistance.
In summary, $PYTH incentives tightly integrate economic behavior with technical operations, allowing Pyth to maintain high reliability in cross-chain applications, DeFi, and institutional services, achieving the dual goals of data stability and ecological efficiency.
@Pyth Network #PythRoadmapand
$PYTH
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Pyth Token Incentives: Driving Stable and Efficient Core Ecosystem Data
The Pyth network processes a massive amount of data daily, covering over 60 chains and serving more than 400 applications, responding to billions of requests every day. In such a large system, the $PYTH token incentives have become key to ensuring data quality and network stability.
Each price update and data verification triggers on-chain token settlements. Data providers are rewarded for submitting accurate data, and governance participants can also participate in decision-making through tokens, creating positive feedback. This is akin to an automatically running "quality control system"; as long as there are token incentives, nodes are motivated to continuously provide highly reliable, low-latency data.
When a data source is abnormal, validation nodes will quickly intervene to correct it, and rewards will lean towards high-quality data. Institutional users pay for data subscriptions with PYTH, further driving demand and circulation of tokens, enhancing ecosystem vitality.
This mechanism not only reduces network risks but also builds a symbiotic relationship where "the higher the data credibility, the more stable the token value". In the long run, token incentives promote continuous expansion of the network and form a closed-loop ecosystem with stronger risk resistance.
In summary, the $PYTH incentives tightly integrate economic behavior and technical operations, allowing Pyth to maintain high reliability in cross-chain applications, DeFi, and institutional services, achieving the dual goals of stable data and efficient ecosystem.
@Pyth Network #PythRoadmapand $PYTH
The Pyth network processes a massive amount of data daily, covering over 60 chains and serving more than 400 applications, responding to billions of requests every day. In such a large system, the $PYTH token incentives have become key to ensuring data quality and network stability.
Each price update and data verification triggers on-chain token settlements. Data providers are rewarded for submitting accurate data, and governance participants can also participate in decision-making through tokens, creating positive feedback. This is akin to an automatically running "quality control system"; as long as there are token incentives, nodes are motivated to continuously provide highly reliable, low-latency data.
When a data source is abnormal, validation nodes will quickly intervene to correct it, and rewards will lean towards high-quality data. Institutional users pay for data subscriptions with PYTH, further driving demand and circulation of tokens, enhancing ecosystem vitality.
This mechanism not only reduces network risks but also builds a symbiotic relationship where "the higher the data credibility, the more stable the token value". In the long run, token incentives promote continuous expansion of the network and form a closed-loop ecosystem with stronger risk resistance.
In summary, the $PYTH incentives tightly integrate economic behavior and technical operations, allowing Pyth to maintain high reliability in cross-chain applications, DeFi, and institutional services, achieving the dual goals of stable data and efficient ecosystem.
@Pyth Network #PythRoadmapand $PYTH
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The Secret to Wealth of Pyth Network Revealed! From Being Overlooked to Controlling a $5.3 Billion Data Empire
2019-2021: The Unnoticed Infrastructure Revolution
While everyone was chasing DeFi mining profits, a few geeks from Wall Street discovered the industry's biggest pain point: blockchain is like a sports car without GPS, full of performance but lacking direction. They made a bold decision - to give up high-paying jobs and build an oracle network specifically designed for high-frequency trading.
In the early stages, financing was repeatedly rejected, and investors bluntly stated, "Building the underlying data is too painful and slow." The team gritted their teeth and persisted, leveraging the institutional resources accumulated at Jump Trading, successfully bringing in the first batch of 25 market makers as data sources. The first deployment on Solana in 2021 allowed the entire industry to witness the power of "second-level updates" for the first time.
While everyone was chasing DeFi mining profits, a few geeks from Wall Street discovered the industry's biggest pain point: blockchain is like a sports car without GPS, full of performance but lacking direction. They made a bold decision - to give up high-paying jobs and build an oracle network specifically designed for high-frequency trading.
In the early stages, financing was repeatedly rejected, and investors bluntly stated, "Building the underlying data is too painful and slow." The team gritted their teeth and persisted, leveraging the institutional resources accumulated at Jump Trading, successfully bringing in the first batch of 25 market makers as data sources. The first deployment on Solana in 2021 allowed the entire industry to witness the power of "second-level updates" for the first time.
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Biting into a $50 billion data cake! Pyth Network's second phase aims at TradFi, not just oracles.
When mentioning oracles, don't just think of DeFi——
The focus has long been on a larger battlefield. This new generation of oracle projects is moving from establishing a foothold in DeFi to the global market data arena worth $50 billion, and it has just reached the most critical second phase, ambition that can't be hidden.
Pyth's expansion path is steady, taking three steps, each step hitting the mark.
The first step has been successfully completed: establishing a solid root in the DeFi circle. It did not follow the traditional oracle path, but rather implemented an 'on-demand pull' update model—price data does not need to be pushed onto the chain continuously; users can call it when they need it, saving gas fees and achieving an update speed of once per second, faster than many blockchain block times. With this efficient infrastructure, it has securely handled over $1.6 trillion in on-chain transaction volume, becoming the most trusted 'data backbone' for DeFi projects. Whether it's calculating collateral ratios for lending protocols or determining liquidation prices for perpetual contracts, they are willing to use Pyth's data sources, establishing a solid foothold in DeFi.
The focus has long been on a larger battlefield. This new generation of oracle projects is moving from establishing a foothold in DeFi to the global market data arena worth $50 billion, and it has just reached the most critical second phase, ambition that can't be hidden.
Pyth's expansion path is steady, taking three steps, each step hitting the mark.
The first step has been successfully completed: establishing a solid root in the DeFi circle. It did not follow the traditional oracle path, but rather implemented an 'on-demand pull' update model—price data does not need to be pushed onto the chain continuously; users can call it when they need it, saving gas fees and achieving an update speed of once per second, faster than many blockchain block times. With this efficient infrastructure, it has securely handled over $1.6 trillion in on-chain transaction volume, becoming the most trusted 'data backbone' for DeFi projects. Whether it's calculating collateral ratios for lending protocols or determining liquidation prices for perpetual contracts, they are willing to use Pyth's data sources, establishing a solid foothold in DeFi.
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Pyth Network: From DeFi oracle to a trillion-level data market disruptor
@PythNetwork
If the first generation of oracle solved the problem of 'whether there is data', then Pyth is answering the next key question: **how to make on-chain data better, more efficient, and more inclusive than traditional financial data?** Its development path is astonishingly clear.
### 🚀 Short-term goal: to become the 'data cornerstone' of full-chain finance.
- Cross-chain expansion: has covered over 50 mainstream blockchains, from Solana to Sui, Aptos, achieving 'one release, all-chain synchronization'.
- Data upgrade: expanded from single price feedback to institutional-level indicators such as volatility, cross-asset correlation.
If the first generation of oracle solved the problem of 'whether there is data', then Pyth is answering the next key question: **how to make on-chain data better, more efficient, and more inclusive than traditional financial data?** Its development path is astonishingly clear.
### 🚀 Short-term goal: to become the 'data cornerstone' of full-chain finance.
- Cross-chain expansion: has covered over 50 mainstream blockchains, from Solana to Sui, Aptos, achieving 'one release, all-chain synchronization'.
- Data upgrade: expanded from single price feedback to institutional-level indicators such as volatility, cross-asset correlation.
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Pyth Pro: When Crypto Data Knocks on Wall Street's Door
Yesterday, when Pyth announced the launch of Pyth Pro, many ordinary investors might not have realized what this meant. But in the world of institutional trading, this undoubtedly dropped a deep-water bomb—data services in the crypto world have, for the first time, truly possessed the power to knock on the doors of traditional financial institutions.
Breaking the Data Babel Tower
In the traditional financial sector, the data market has always been a fragmented world. Stocks, foreign exchange, commodities, cryptocurrencies... each market has its own data providers, and each institution needs to maintain complex data interfaces. Traders' desks are always piled high with different terminals, much like a data Babel Tower.
Breaking the Data Babel Tower
In the traditional financial sector, the data market has always been a fragmented world. Stocks, foreign exchange, commodities, cryptocurrencies... each market has its own data providers, and each institution needs to maintain complex data interfaces. Traders' desks are always piled high with different terminals, much like a data Babel Tower.
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The Alchemy of Data: How Pyth Turns Raw Data into Your 'Money Tree'?
In the traditional financial world, top institutions spend billions of dollars annually purchasing market data—this is 'privileged information' that ordinary people can never access. Pyth is breaking down this wall with blockchain technology, allowing everyone to access institutional-level data gifts.
The transformation journey from 'data raw materials' to 'Alpha gold mine'
Imagine that a Goldman Sachs trader and an ordinary retail investor see the same data at the same time—this is nearly impossible in traditional finance. But Pyth makes this a reality through three key steps:
1. Selected data sources - directly obtaining raw data from exchanges, market makers, and trading institutions, eliminating the pollution of second-hand information.
The transformation journey from 'data raw materials' to 'Alpha gold mine'
Imagine that a Goldman Sachs trader and an ordinary retail investor see the same data at the same time—this is nearly impossible in traditional finance. But Pyth makes this a reality through three key steps:
1. Selected data sources - directly obtaining raw data from exchanges, market makers, and trading institutions, eliminating the pollution of second-hand information.
杨双桃8888:
朋友👫下午好，祝幸福快乐！
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It's not 'binding', it's 'symbiosis': The kingly path of Pyth and Solana, neither can do without the other
The blockchain community loves to discuss the grand story of 'cross-chain interoperability', but what really gets done are often those deep partnerships where 'what you lack, I just happen to have, and what I want, you just happen to give'. Just like today’s oracle giant Pyth Network, which covers 55 chains; who would have thought it started as a project experimenting in the 'performance test field' of Solana? And Solana's ability to firmly hold its position as a high-performance public chain owes much to Pyth's pricing data.
The relationship between these two is not simply 'cooperation', but more like a pair of 'soul partners': Solana provided Pyth with the grounding confidence, and Pyth helped Solana support the ecological framework. Understanding their mutual achievements is essential to grasping the success logic in the world of high-performance blockchains.
The relationship between these two is not simply 'cooperation', but more like a pair of 'soul partners': Solana provided Pyth with the grounding confidence, and Pyth helped Solana support the ecological framework. Understanding their mutual achievements is essential to grasping the success logic in the world of high-performance blockchains.
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