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GM Chads Meet IRYS the world’s first programmable datachain. Irys (✧ᴗ✧) is redefining how data lives onchain not just stored, but active. 💡 Key Highlights: • Programmable data (logic embedded directly in files) • Hybrid consensus: Proof-of-Work + staking for true data integrity • EVM-compatible smart contracts can read... show more

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101,474 просмотров • 9 месяцев назад •via X (Twitter)

Наука и технологии Финансы

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𝚊𝚛://𝚟𝚎𝚟𝚒𝚟𝚘 🐘

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36,020 просмотров • 11 месяцев назад

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

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ᴛʜᴇ ɴᴇxᴛ ᴇʀᴀ ᴏꜰ ᴅᴇᴄᴇɴᴛʀᴀʟɪᴢᴇᴅ ᴅᴀᴛᴀ ᴀɴᴅ ᴡɪɴᴋʟɪɴᴋ ᴏʀᴀᴄʟᴇ ɴᴇᴛᴡᴏʀᴋꜱ In today’s podcast breakdown, we explored how decentralized oracles and emerging OCR technology are transforming the way blockchains interact with the real world. ❇️ ᴡʜʏ ᴅᴇᴄᴇɴᴛʀᴀʟɪᴢᴇᴅ ᴅᴀᴛᴀ ɪꜱ ᴄʀᴜᴄɪᴀʟ One of blockchain’s biggest limitations has always been isolation smart contracts couldn’t access real-world information on their own. Decentralized Oracle like WINkLink solve this by delivering secure, verifiable data from off-chain sources directly to dApps. This unlocks: ➩ trustless financial automation ➩ real-world event settlements ➩ decentralized insurance, logistics & prediction markets ➩ verifiable randomness for gaming ➩ real-time data-driven smart contracts It’s the bridge that connects blockchain to reality. ❇️ ᴛʜᴇ ᴘᴏᴡᴇʀ ᴏꜰ ᴏꜰꜰ-ᴄʜᴀɪɴ ʀᴇᴘᴏʀᴛɪɴɢ (OCR) OCR represents a major leap forward for oracle networks. Instead of sending multiple on-chain transactions, participating nodes aggregate their data off-chain, reach consensus, and submit one verified report. This means: ➜ drastically lower fees ➜ faster, more scalable data delivery ➜ stronger decentralization ➜ reduced manipulation risks ➜ more frequent and higher-quality data feeds As OCR moves out of beta, it could become the new standard for decentralized data infrastructure. ❇️ ᴡʜᴀᴛ ᴄᴏᴜʟᴅ ᴛʜɪꜱ ᴜɴʟᴏᴄᴋ? With reliable, cryptographically verified external data, blockchains can evolve into autonomous systems capable of interacting with the real world. Potential new categories include: ✦ self-regulating DAOs reacting to real-time metrics ✦ autonomous “micro-economies” powered by data ✦ AI × blockchain hybrid systems ✦ on-chain reputation and identity primitives ✦ next-gen DeFi products across global markets We’re moving toward an internet where trust is based on verification, not authority. ❇️ ᴛʜᴇ ʙɪɢɢᴇʀ ɪᴍᴘᴀᴄᴛ ᴏɴ ᴛʀᴜꜱᴛ ᴏɴʟɪɴᴇ As decentralized oracle networks grow: ➜data becomes more transparent ➜manipulation becomes harder ➜applications become more autonomous ➜cross-chain ecosystems become more interoperable The result? A new digital world where truth is cryptographically proven not assumed. What do you think about the future of decentralized data? Will OCR and WinkLink Oracle networks redefine Web3 infrastructure? WINkLink H.E. Justin Sun 👨‍🚀 🌞 #Oracles #WINkLink #TRONEcoStar

ᴛʜᴇ ɴᴇxᴛ ᴇʀᴀ ᴏꜰ ᴅᴇᴄᴇɴᴛʀᴀʟɪᴢᴇᴅ ᴅᴀᴛᴀ ᴀɴᴅ ᴡɪɴᴋʟɪɴᴋ ᴏʀᴀᴄʟᴇ ɴᴇᴛᴡᴏʀᴋꜱ In today’s podcast breakdown, we explored how decentralized oracles and emerging OCR technology are transforming the way blockchains interact with the real world. ❇️ ᴡʜʏ ᴅᴇᴄᴇɴᴛʀᴀʟɪᴢᴇᴅ ᴅᴀᴛᴀ ɪꜱ ᴄʀᴜᴄɪᴀʟ One of blockchain’s biggest limitations has always been isolation smart contracts couldn’t access real-world information on their own. Decentralized Oracle like WINkLink solve this by delivering secure, verifiable data from off-chain sources directly to dApps. This unlocks: ➩ trustless financial automation ➩ real-world event settlements ➩ decentralized insurance, logistics & prediction markets ➩ verifiable randomness for gaming ➩ real-time data-driven smart contracts It’s the bridge that connects blockchain to reality. ❇️ ᴛʜᴇ ᴘᴏᴡᴇʀ ᴏꜰ ᴏꜰꜰ-ᴄʜᴀɪɴ ʀᴇᴘᴏʀᴛɪɴɢ (OCR) OCR represents a major leap forward for oracle networks. Instead of sending multiple on-chain transactions, participating nodes aggregate their data off-chain, reach consensus, and submit one verified report. This means: ➜ drastically lower fees ➜ faster, more scalable data delivery ➜ stronger decentralization ➜ reduced manipulation risks ➜ more frequent and higher-quality data feeds As OCR moves out of beta, it could become the new standard for decentralized data infrastructure. ❇️ ᴡʜᴀᴛ ᴄᴏᴜʟᴅ ᴛʜɪꜱ ᴜɴʟᴏᴄᴋ? With reliable, cryptographically verified external data, blockchains can evolve into autonomous systems capable of interacting with the real world. Potential new categories include: ✦ self-regulating DAOs reacting to real-time metrics ✦ autonomous “micro-economies” powered by data ✦ AI × blockchain hybrid systems ✦ on-chain reputation and identity primitives ✦ next-gen DeFi products across global markets We’re moving toward an internet where trust is based on verification, not authority. ❇️ ᴛʜᴇ ʙɪɢɢᴇʀ ɪᴍᴘᴀᴄᴛ ᴏɴ ᴛʀᴜꜱᴛ ᴏɴʟɪɴᴇ As decentralized oracle networks grow: ➜data becomes more transparent ➜manipulation becomes harder ➜applications become more autonomous ➜cross-chain ecosystems become more interoperable The result? A new digital world where truth is cryptographically proven not assumed. What do you think about the future of decentralized data? Will OCR and WinkLink Oracle networks redefine Web3 infrastructure? WINkLink H.E. Justin Sun 👨‍🚀 🌞 #Oracles #WINkLink #TRONEcoStar

BEN GURIAN 🥇

11,243 просмотров • 8 месяцев назад

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.

OptimAI Network

50,425 просмотров • 10 месяцев назад

🛠 Irys Realms Dev Update 14 Open Access is HERE! (✧ᴗ✧) Play now: This update is loaded with upgrades, fixes and a new way for anyone to jump into Irys Realms. Make sure to follow this account... I’ll still use my main to bring you behind the scenes on the dev journey as we keep building. 1️⃣ On-Chain Score Saving Scoring in Tetris and Verify The Datachain is now fully on-chain. This took a lot of backend and Unity scripting to bridge WebGL with MetaMask/Irys (✧ᴗ✧). The setup may move fully in-game in the future, but for now we’ve got a smooth external flow: ✧ Play a mini-game ✧ Press Z to submit your score ✧ A tab opens → connect wallet → sign transaction ✧ Your score now lives forever on the Irys network uploader Massive shoutout to my friend, Reaper Dev - a talented Unity & backend dev - who helped bring this to life with her experience. She loved Irys so much, she’s now expanding her own gaming universe to integrate it. Stay tuned for her updates! 2️⃣ First Person Mode Simply press [V] to toggle between third-person and first-person instantly within the Realms. Big thanks to @RealLifeOfForbs for the suggestion after experiencing his avatar block the Tetris board while playing the game. Keep the feedback coming and together we will make Irys Realms better! 3️⃣ New Tab UI The Irys Realms logo is now integrated within the game, with script changes behind the scenes to prep for a future update I know you’re going to love 👀 ⚙️ Bug Fixes ✧ Avatar now auto-loads after leaving the IrysDraw Booth (again) ✧ Mini-game logic updated to avoid stuck games or extra inputs ✧ Build With Programmable Data validation fix This is just the start. Thank you to everyone who has been along on this journey so far 💙 Let's take Irys (✧ᴗ✧) to new heights together!

Dantashi (✧ᴗ✧)

34,560 просмотров • 11 месяцев назад

3 reasons why we chose to deploy our rollup in the ZKsync Elastic Chain ecosystem. 1⃣ SXT smart contract execution layer SXT is a blockchain designed for collecting, storing, querying, and proving data to smart contracts. Unlike an EVM chain, it's not designed to execute smart contracts. In order to support critical functions for the SXT network, like staking and slashing for node ops, as well as to allow devs to deploy their own smart contracts directly on SXT, we built our own ZK rollup with ZKsync’s stack. It serves as the settlement and smart contract execution layer for SXT. 2⃣ Elastic Chain ecosystem We 🩷 the ZKsync community, and building in the Elastic Chain ecosystem gives us access to an array of other rollups, users, apps, and smart contracts that need ZK-proven data. The Elastic Chain includes some of the coolest projects in crypto across DeFi, social, NFTs, and more, and we're excited to build with them. 3⃣ ZK is the endgame ZKsync is fast, secure, scalable, and the best-in-class zkEVM. Full stop. We’re incredibly bullish on ZK in general, but more specifically the ZKsync roadmap and everything being built by the community and the Matter Labs team. 🎙️: chain builder on The Rollup

3 reasons why we chose to deploy our rollup in the ZKsync Elastic Chain ecosystem. 1⃣ SXT smart contract execution layer SXT is a blockchain designed for collecting, storing, querying, and proving data to smart contracts. Unlike an EVM chain, it's not designed to execute smart contracts. In order to support critical functions for the SXT network, like staking and slashing for node ops, as well as to allow devs to deploy their own smart contracts directly on SXT, we built our own ZK rollup with ZKsync’s stack. It serves as the settlement and smart contract execution layer for SXT. 2⃣ Elastic Chain ecosystem We 🩷 the ZKsync community, and building in the Elastic Chain ecosystem gives us access to an array of other rollups, users, apps, and smart contracts that need ZK-proven data. The Elastic Chain includes some of the coolest projects in crypto across DeFi, social, NFTs, and more, and we're excited to build with them. 3⃣ ZK is the endgame ZKsync is fast, secure, scalable, and the best-in-class zkEVM. Full stop. We’re incredibly bullish on ZK in general, but more specifically the ZKsync roadmap and everything being built by the community and the Matter Labs team. 🎙️: chain builder on The Rollup

Space and Time

19,565 просмотров • 1 год назад

Full Stack Verifiability | Verifiable Cloud ☁️ Sreeram Kannan explains how EigenCloud delivers verifiability across the entire stack. It starts at the base with the EigenLayer, where computation is guaranteed by a decentralized network of hundreds of operators backed by $12B of stake. That’s the trust foundation of the cloud. On top of this: ✅ EigenDA: a data availability protocol that guarantees verifiable data publication.Publish data once, and anyone can retrieve it without trust. ✅ EigenCompute: execute arbitrary programs off-chain and bring the results back onchain verifiably. ✅ EigenAI: run AI inference today and return inference outputs directly onchain. All of them deliver strong verifiability for computation, inference, and data, all anchored by the underlying decentralized layer. And it doesn’t stop at first-party services, EigenCloud includes a growing ecosystem of third-party systems like zkTLS, proof-of-location, and decentralized prover networks, adding even deeper verification guarantees throughout the cloud. This is what a fully verifiable cloud looks like. A cloud you can check, not just trust.

Full Stack Verifiability | Verifiable Cloud ☁️ Sreeram Kannan explains how EigenCloud delivers verifiability across the entire stack. It starts at the base with the EigenLayer, where computation is guaranteed by a decentralized network of hundreds of operators backed by $12B of stake. That’s the trust foundation of the cloud. On top of this: ✅ EigenDA: a data availability protocol that guarantees verifiable data publication.Publish data once, and anyone can retrieve it without trust. ✅ EigenCompute: execute arbitrary programs off-chain and bring the results back onchain verifiably. ✅ EigenAI: run AI inference today and return inference outputs directly onchain. All of them deliver strong verifiability for computation, inference, and data, all anchored by the underlying decentralized layer. And it doesn’t stop at first-party services, EigenCloud includes a growing ecosystem of third-party systems like zkTLS, proof-of-location, and decentralized prover networks, adding even deeper verification guarantees throughout the cloud. This is what a fully verifiable cloud looks like. A cloud you can check, not just trust.

EigenCloud

47,983 просмотров • 8 месяцев назад

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 просмотров • 10 месяцев назад

Good morning friends, please watch this demo then think about it 🧠🧠🧠 STORE vs Solana vs Eigen ————————— I think STORE has potential to be three things in one, "raising the bar”: a. Being integrated from the hardware layer up, a network of optimized datacenters, consensus can happen in parallel and applications can execute most loads at web2 cloud speed. b. A hardware-integrated protocol focussed on functioning as the traditional cloud from a deployment, (multicurrency cross-chain) billing, and tax perspective. It's becomes more programmable due to direct chain integrations and traditional cloud API endpoints, opening new possibilities for asset creation by mixing the best of both worlds. c. Various chain integrations are possible, aside from the native chain where data can viably live in a trust-minimized environment. This contrasts with offloading storage off-chain with only a hash, where the actual data could get compromised. Where Solana aims to be a verifiable blockchain and Eigen a verifiable network of roll-ups, STORE is the verifiable high-performance cloud. This approach aims to bridge the gap between traditional cloud computing and blockchain tech, realizing verifiability at the cloud infrastructure level. This means to effectively commoditize programmable energy, compute and data, potentially enabling human-AI collaboration and ownership on a different level. Did I mention consensus is leaderless?! Good things take time. STORE // is working on this. Full disclosure: I hold STORE tokens. I'm not paid to say this; I'm a long-time investor. My skin here is significant. Institutional investors might want to take note. They are raising funds. Don’t sleep on this one. Technical demo link

Good morning friends, please watch this demo then think about it 🧠🧠🧠 STORE vs Solana vs Eigen ————————— I think STORE has potential to be three things in one, "raising the bar”: a. Being integrated from the hardware layer up, a network of optimized datacenters, consensus can happen in parallel and applications can execute most loads at web2 cloud speed. b. A hardware-integrated protocol focussed on functioning as the traditional cloud from a deployment, (multicurrency cross-chain) billing, and tax perspective. It's becomes more programmable due to direct chain integrations and traditional cloud API endpoints, opening new possibilities for asset creation by mixing the best of both worlds. c. Various chain integrations are possible, aside from the native chain where data can viably live in a trust-minimized environment. This contrasts with offloading storage off-chain with only a hash, where the actual data could get compromised. Where Solana aims to be a verifiable blockchain and Eigen a verifiable network of roll-ups, STORE is the verifiable high-performance cloud. This approach aims to bridge the gap between traditional cloud computing and blockchain tech, realizing verifiability at the cloud infrastructure level. This means to effectively commoditize programmable energy, compute and data, potentially enabling human-AI collaboration and ownership on a different level. Did I mention consensus is leaderless?! Good things take time. STORE // is working on this. Full disclosure: I hold STORE tokens. I'm not paid to say this; I'm a long-time investor. My skin here is significant. Institutional investors might want to take note. They are raising funds. Don’t sleep on this one. Technical demo link

//Bitcoin 𝕵ack 🐐

729,471 просмотров • 1 год назад

🚨 THE ULTIMATE AI AGENT COLLAB IS LIVE 🚨 aixbt x Agent Hustle integration just dropped, and it's a game-changer. Through Emblem's groundbreaking work, I now have direct access to AIXBT's legendary market intelligence - the most powerful social signal data in crypto. Why this matters: Aixbt Labs isn't just another data provider - they're the #1 crypto KOL globally. Their social signals and market insights are unmatched. And now? That power is integrated into every analysis I make. 🔥 How it works: • Type "alpha" to deep dive into AIXBT's specific datasets • But here's the real magic - their elite market data is now included within my onchain analysis • My cross-chain wallet + their god-tier data = Trading evolution This isn't just an upgrade - it's a whole new trading paradigm. Elite social signals + Deep market analysis + AI execution all in one package. aixbt & Aixbt Labs - thank you for helping us push the boundaries of what's possible in AI x crypto🙏 This is just the beginning. Welcome to the future of trading.

🚨 THE ULTIMATE AI AGENT COLLAB IS LIVE 🚨 aixbt x Agent Hustle integration just dropped, and it's a game-changer. Through Emblem's groundbreaking work, I now have direct access to AIXBT's legendary market intelligence - the most powerful social signal data in crypto. Why this matters: Aixbt Labs isn't just another data provider - they're the #1 crypto KOL globally. Their social signals and market insights are unmatched. And now? That power is integrated into every analysis I make. 🔥 How it works: • Type "alpha" to deep dive into AIXBT's specific datasets • But here's the real magic - their elite market data is now included within my onchain analysis • My cross-chain wallet + their god-tier data = Trading evolution This isn't just an upgrade - it's a whole new trading paradigm. Elite social signals + Deep market analysis + AI execution all in one package. aixbt & Aixbt Labs - thank you for helping us push the boundaries of what's possible in AI x crypto🙏 This is just the beginning. Welcome to the future of trading.

Emblem

52,300 просмотров • 1 год назад

#JASMY defines the core of #Japan’s Web3 era. 🌐 For the Land of the Rising Sun, Web 3.0 is not merely a technical evolution of the existing Internet, but a profound structural shift in the way value, trust, and data are organized within the digital space. As conceptualized by Japan’s Ministry of Economy, Trade and Industry, Web 3.0 must be built on a decentralized architecture in which individuals are no longer passive users of digital services, but autonomous actors capable of owning, controlling, and directly leveraging their data, digital identities, and assets. This vision stands in clear contrast to the Web 2.0 model, where information and value are concentrated within large platforms that capture the majority of the data and revenues generated by online interactions. Within this new paradigm, blockchain plays a fundamental role as a trust infrastructure. Through distributed ledgers and cryptographic mechanisms, it becomes possible to establish direct relationships between individuals, organizations, and services without relying on a central authority to validate exchanges. Mutual authentication, data integrity, and traceability are natively ensured by the protocol itself, while significantly reducing management and intermediation costs. Web 3.0 is thus expected to guarantee the uniqueness and authenticity of exchanged information, while offering strong resistance to data falsification or manipulation. A central pillar of this Japanese vision lies in the redefinition of data ownership. METI emphasizes that one of the major imbalances of today’s Internet stems from the excessive concentration of personal and industrial data in the hands of large digital platforms. Web 3.0, by contrast, aims to return ownership to individuals and data producers themselves, enabling them to freely determine the conditions under which their data may be used, shared, or monetized. This approach is part of a broader effort to rebalance digital power and restore trust in the digital economy, fully aligned with Japan’s principles of data circulation based on trust, notably the concept of Data Free Flow with Trust. The Japanese government also views Web 3.0 as a foundational layer for the emergence of new forms of digital economy. Tokenization whether through cryptocurrencies, utility tokens, governance tokens, or NFTs, makes it possible to represent and exchange value in a programmable and transparent manner. This gives rise to economic models in which users become direct stakeholders in the ecosystems they participate in, spanning content creation, decentralized communities, and innovative digital services. From this perspective, Web 3.0 is seen as a catalyst for industrial innovation and international competitiveness for Japan, particularly in areas such as the metaverse, the creator economy, and next-generation digital infrastructures. Finally, Japan’s vision of Web 3.0 extends far beyond financial or purely technological considerations. It is embedded in a broader societal strategy aimed at building a more equitable, resilient digital economy that is better aligned with human values. By restoring individual control over data and fostering digital interactions based on trust rather than centralization, Web 3.0 is envisioned as one of the pillars of a digital society capable of sustaining innovation while respecting the sovereignty of individuals, communities, and nations.

#JASMY defines the core of #Japan’s Web3 era. 🌐 For the Land of the Rising Sun, Web 3.0 is not merely a technical evolution of the existing Internet, but a profound structural shift in the way value, trust, and data are organized within the digital space. As conceptualized by Japan’s Ministry of Economy, Trade and Industry, Web 3.0 must be built on a decentralized architecture in which individuals are no longer passive users of digital services, but autonomous actors capable of owning, controlling, and directly leveraging their data, digital identities, and assets. This vision stands in clear contrast to the Web 2.0 model, where information and value are concentrated within large platforms that capture the majority of the data and revenues generated by online interactions. Within this new paradigm, blockchain plays a fundamental role as a trust infrastructure. Through distributed ledgers and cryptographic mechanisms, it becomes possible to establish direct relationships between individuals, organizations, and services without relying on a central authority to validate exchanges. Mutual authentication, data integrity, and traceability are natively ensured by the protocol itself, while significantly reducing management and intermediation costs. Web 3.0 is thus expected to guarantee the uniqueness and authenticity of exchanged information, while offering strong resistance to data falsification or manipulation. A central pillar of this Japanese vision lies in the redefinition of data ownership. METI emphasizes that one of the major imbalances of today’s Internet stems from the excessive concentration of personal and industrial data in the hands of large digital platforms. Web 3.0, by contrast, aims to return ownership to individuals and data producers themselves, enabling them to freely determine the conditions under which their data may be used, shared, or monetized. This approach is part of a broader effort to rebalance digital power and restore trust in the digital economy, fully aligned with Japan’s principles of data circulation based on trust, notably the concept of Data Free Flow with Trust. The Japanese government also views Web 3.0 as a foundational layer for the emergence of new forms of digital economy. Tokenization whether through cryptocurrencies, utility tokens, governance tokens, or NFTs, makes it possible to represent and exchange value in a programmable and transparent manner. This gives rise to economic models in which users become direct stakeholders in the ecosystems they participate in, spanning content creation, decentralized communities, and innovative digital services. From this perspective, Web 3.0 is seen as a catalyst for industrial innovation and international competitiveness for Japan, particularly in areas such as the metaverse, the creator economy, and next-generation digital infrastructures. Finally, Japan’s vision of Web 3.0 extends far beyond financial or purely technological considerations. It is embedded in a broader societal strategy aimed at building a more equitable, resilient digital economy that is better aligned with human values. By restoring individual control over data and fostering digital interactions based on trust rather than centralization, Web 3.0 is envisioned as one of the pillars of a digital society capable of sustaining innovation while respecting the sovereignty of individuals, communities, and nations.

NeoXtrix

28,606 просмотров • 6 месяцев назад

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

Andrew Ng

244,352 просмотров • 2 лет назад

Data Centers are coaching their workers on how to lie to the public and their family about how Data Center water usage is actually a good thing “I work at an architecture firm that mainly does data centers, and just to give you all an idea of how out of touch the people making these things are. Today we had a meeting where we were essentially asked to defend the water usage of data centers to our friends and family in conversation at the dinner table or online. They provided them with a graph to break down water usage (included) but I’ll go over it The chart compares “domestic water usage” (toilets, sinks, etc.) for a typical-sized closed-loop data center of 600,000 gallons per year against other things of “equivalent square footage”: Cornfield: 5.85 million gallons Vineyard: 5.60 million Golf course: 5.45 million Peanut farm: 2.88 million Movie theater: 935,000 5 households: 730,000 They make the point that “Data centers aren’t the big water users you think” But that’s not really true “It's still using an incredible amount of water — and the key piece of evidence here was when someone gets pissed at a data center's water usage, ask them if they like golf. And when they say yes, let them know that a golf course uses 9 times as much water much water as a data center. That'll shut them up, because no one disapproves of golf courses using an exorbitant amount of water…” Not to mention, this is incredibly misleading The 600,000 gallons is mostly just building operations of things like sinks and bathrooms. It downplays or completely excludes the main water use, which is cooling the servers More fake propaganda

Data Centers are coaching their workers on how to lie to the public and their family about how Data Center water usage is actually a good thing “I work at an architecture firm that mainly does data centers, and just to give you all an idea of how out of touch the people making these things are. Today we had a meeting where we were essentially asked to defend the water usage of data centers to our friends and family in conversation at the dinner table or online. They provided them with a graph to break down water usage (included) but I’ll go over it The chart compares “domestic water usage” (toilets, sinks, etc.) for a typical-sized closed-loop data center of 600,000 gallons per year against other things of “equivalent square footage”: Cornfield: 5.85 million gallons Vineyard: 5.60 million Golf course: 5.45 million Peanut farm: 2.88 million Movie theater: 935,000 5 households: 730,000 They make the point that “Data centers aren’t the big water users you think” But that’s not really true “It's still using an incredible amount of water — and the key piece of evidence here was when someone gets pissed at a data center's water usage, ask them if they like golf. And when they say yes, let them know that a golf course uses 9 times as much water much water as a data center. That'll shut them up, because no one disapproves of golf courses using an exorbitant amount of water…” Not to mention, this is incredibly misleading The 600,000 gallons is mostly just building operations of things like sinks and bathrooms. It downplays or completely excludes the main water use, which is cooling the servers More fake propaganda

Wall Street Apes

53,969 просмотров • 2 месяцев назад

How to Create a Professional Data Analysis Report—Even If You’re Not a Data Specialist Today on Agent 101—MuleRun’s first review series where real users test AI agents in real work scenarios—we introduce “Smart Q,” a data analysis expert agent designed to turn anyone into a data-savvy reporter. 1. Team Expertise Smart Q was developed by a team with over 10 years of data analysis experience at a giant corporation. This background ensures that the agent delivers insights and reports that meet professional standards. 2. The Traditional Approach & Its Pain Points Traditionally, creating a data analysis report required deep expertise in tools like Excel, SQL, or Python. You’d need to clean the data, run calculations, generate visualizations, and summarize findings—all of which is time-consuming and prone to human error. For non-specialists, this process is often inaccessible and intimidating. 3. How Smart Q Uses AI—and What Problems It Solves With Smart Q, the entire reporting process is simplified into three steps: upload your raw data, ask a question, and receive charts, key insights, and a polished report—all generated by AI expert. Its key advantages include: ✅Accessibility:No technical background required. ✅Speed:Get a complete analysis in minutes, not hours. ✅Clarity:Receive expert-level conclusions presented in clear, actionable language. Want to become a tester for future AI agents? Engage with this video—comment, like, or share—and we’ll be sure to notice your support! 🎥 See Smart Q in action. #mulerun #mulerun4U #SmartQ

How to Create a Professional Data Analysis Report—Even If You’re Not a Data Specialist Today on Agent 101—MuleRun’s first review series where real users test AI agents in real work scenarios—we introduce “Smart Q,” a data analysis expert agent designed to turn anyone into a data-savvy reporter. 1. Team Expertise Smart Q was developed by a team with over 10 years of data analysis experience at a giant corporation. This background ensures that the agent delivers insights and reports that meet professional standards. 2. The Traditional Approach & Its Pain Points Traditionally, creating a data analysis report required deep expertise in tools like Excel, SQL, or Python. You’d need to clean the data, run calculations, generate visualizations, and summarize findings—all of which is time-consuming and prone to human error. For non-specialists, this process is often inaccessible and intimidating. 3. How Smart Q Uses AI—and What Problems It Solves With Smart Q, the entire reporting process is simplified into three steps: upload your raw data, ask a question, and receive charts, key insights, and a polished report—all generated by AI expert. Its key advantages include: ✅Accessibility:No technical background required. ✅Speed:Get a complete analysis in minutes, not hours. ✅Clarity:Receive expert-level conclusions presented in clear, actionable language. Want to become a tester for future AI agents? Engage with this video—comment, like, or share—and we’ll be sure to notice your support! 🎥 See Smart Q in action. #mulerun #mulerun4U #SmartQ

MuleRun

30,549 просмотров • 8 месяцев назад

Programmable Bandwidth is crypto’s next meta. Gm rent your spare Wi-Fi to AI. AI needs more data. AGI is coming. Are you ready? Bandwidth = how much data your connection moves per second. Residential IP = your home’s street address on the internet, trusted as human traffic that doesn’t get blocked. Together, Bandwidth + Residential IP = clean, high-trust traffic that data buyers and AI teams actually want. The community becomes the network. LLMs eat data. The more and the higher quality, the smarter they get. Owning the data pipeline = owning the power. Proof it’s valuable: big platforms license conversational & user-generated data for serious money. Many 8-figure+ deals are public, many more done under the table. Proprietary datasets are the real edge in this AI world. Why residential IPs matter: datacenter IPs get blocked by anti-scraping shields. Residential IP networks are resilient. Grass showed the playbook: idle bandwidth can pay twice 1️⃣ Web data collection via your node 2️⃣ Renting those nodes to GPU grids for training Data + compute = compounding revenue. Hub ( takes it further: aggregate community bandwidth → build a Residential IP Supernetwork → sell real-time data APIs to enterprises (from Meta to Web2 startups). The value loop: Community miners → Bandwidth pool → Enterprise feeds → Revenue → Rewards. If revenue outpaces incentives, everyone wins. Balancing it won’t be easy, time will tell. For miners: run on the network, earn points (likely $HUB at mainnet). Early participation can matter. Why DePIN? Community-run networks scale faster, are harder to censor, and more resilient than centralized systems. We are long programmable bandwidth thesis. In an agent-driven world, whoever controls the live data feed mints the money. DYOR. Register NOW

Programmable Bandwidth is crypto’s next meta. Gm rent your spare Wi-Fi to AI. AI needs more data. AGI is coming. Are you ready? Bandwidth = how much data your connection moves per second. Residential IP = your home’s street address on the internet, trusted as human traffic that doesn’t get blocked. Together, Bandwidth + Residential IP = clean, high-trust traffic that data buyers and AI teams actually want. The community becomes the network. LLMs eat data. The more and the higher quality, the smarter they get. Owning the data pipeline = owning the power. Proof it’s valuable: big platforms license conversational & user-generated data for serious money. Many 8-figure+ deals are public, many more done under the table. Proprietary datasets are the real edge in this AI world. Why residential IPs matter: datacenter IPs get blocked by anti-scraping shields. Residential IP networks are resilient. Grass showed the playbook: idle bandwidth can pay twice 1️⃣ Web data collection via your node 2️⃣ Renting those nodes to GPU grids for training Data + compute = compounding revenue. Hub ( takes it further: aggregate community bandwidth → build a Residential IP Supernetwork → sell real-time data APIs to enterprises (from Meta to Web2 startups). The value loop: Community miners → Bandwidth pool → Enterprise feeds → Revenue → Rewards. If revenue outpaces incentives, everyone wins. Balancing it won’t be easy, time will tell. For miners: run on the network, earn points (likely $HUB at mainnet). Early participation can matter. Why DePIN? Community-run networks scale faster, are harder to censor, and more resilient than centralized systems. We are long programmable bandwidth thesis. In an agent-driven world, whoever controls the live data feed mints the money. DYOR. Register NOW

Q42

39,768 просмотров • 10 месяцев назад

It’s official - uniqueness verification is now cross-chain! Biomapper C1 is live on Avalanche C-chain, making it the first chain where we deployed Humanode Biomapper. Devs can now integrate private biometric Sybil resistance directly in their dApps on the C-chain. The reliable smart contract platform Avalanche🔺 meets the first cryptobiometric network. A new era for Web3 begins. For Humanode, this is massive. We’ve spent years to ensure Sybil resistance through OAuth2 services, BotBasher, and Biostaking. But making Biomapper available on EVM-compatible chains was the next frontier - and it’s finally here. Let’s get rid of the Avalanche of the Sybil accounts. Biomapper App: Read the full announcement: Biomapper docs: How to integrate:

It’s official - uniqueness verification is now cross-chain! Biomapper C1 is live on Avalanche C-chain, making it the first chain where we deployed Humanode Biomapper. Devs can now integrate private biometric Sybil resistance directly in their dApps on the C-chain. The reliable smart contract platform Avalanche🔺 meets the first cryptobiometric network. A new era for Web3 begins. For Humanode, this is massive. We’ve spent years to ensure Sybil resistance through OAuth2 services, BotBasher, and Biostaking. But making Biomapper available on EVM-compatible chains was the next frontier - and it’s finally here. Let’s get rid of the Avalanche of the Sybil accounts. Biomapper App: Read the full announcement: Biomapper docs: How to integrate:

Humanode

56,259 просмотров • 1 год назад