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Alphanet V3 is here. - Huge data throughput. Could run ~2,000 instances of Base or 15,000 OP Mainnets, going by current kb/s demand - 800x faster Arweave queries - Migration to ar.io network Turbo - Oracles, via SEDA - EVM and Substrate compatibility for ledger data settlement - Transaction...

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47,038 görüntüleme • 1 yıl önce •via X (Twitter)

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@sedaprotocol huge ship - congrats on the release 🫡🐘

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@ar_io_network @sedaprotocol Huge huge!

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@ar_io_network @sedaprotocol awsome！

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🚀 Arweave: The Epic Journey Towards Timeless Data Storage Embark on a journey with me as we unravel the marvel that is Arweave, a project meticulously crafted to safeguard data for an eternity without compromise. Let's dive into the intricacies that make this revolutionary endeavor a beacon of #permanence . 🌐 How Does #Arweave Achieve Timeless Data Storage? ✨ Cryptographic Proofs: Imagine a world where data integrity is not just a promise but a #cryptographic reality. Arweave's #foundation lies in cryptographic proofs, ensuring that every new block added to the network is not just stored but validated with unyielding certainty. 🏰 Storage Endowment: Arweave doesn't just store data; it endows it with longevity. Through a groundbreaking approach, data stored on Arweave is prepaid for 20 replicas spanning the next 200 years. This is not a mere estimate; it's a conservative projection, fortifying Arweave's commitment to #securing your data for the long term. 💡 Incentivized Evolution: The #world evolves, and so does Arweave. The #protocol is open, ready for change, and embraces an incentivized evolution model. Arweave positions itself not just as a #platform but as a versatile framework, encouraging innovative forks rewarded through a fair fork methodology. The beauty lies in the compatibility of these forks at the protocol layer, fostering cooperation over competition. 🌍 Unified Dataset for Permanence: Arweave isn't just about storing data; it's about unity. The encouragement of forks aligns seamlessly with the mission of permanent data storage. Keeping the dataset unified is in everyone's best interest, ensuring a collective stride towards a future where data stands the test of time. 🔍 Breaking It Down: Cryptographic Proofs: Ensuring the replication and secure storage of substantial parts of the Arweave dataset. Storage Endowment: A commitment to safeguarding data for a minimum of 200 years. Innovative Forks: Encouraging a continuous stream of innovation for permanent data storage. 📖 For those seeking a deeper understanding, explore DRAFT 17. Delve into the intricacies of Arweave's design, where proofs drive replication, the endowment fortifies storage, and the approach to forks sparks innovation. Join us on this odyssey towards a future where your data remains eternally secure and unaltered. Türkçe için : Arweave Ecosystem Only Arweave ar.io WeaveVM is now Load Network (@useload)
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🚀 Arweave: The Epic Journey Towards Timeless Data Storage Embark on a journey with me as we unravel the marvel that is Arweave, a project meticulously crafted to safeguard data for an eternity without compromise. Let's dive into the intricacies that make this revolutionary endeavor a beacon of #permanence . 🌐 How Does #Arweave Achieve Timeless Data Storage? ✨ Cryptographic Proofs: Imagine a world where data integrity is not just a promise but a #cryptographic reality. Arweave's #foundation lies in cryptographic proofs, ensuring that every new block added to the network is not just stored but validated with unyielding certainty. 🏰 Storage Endowment: Arweave doesn't just store data; it endows it with longevity. Through a groundbreaking approach, data stored on Arweave is prepaid for 20 replicas spanning the next 200 years. This is not a mere estimate; it's a conservative projection, fortifying Arweave's commitment to #securing your data for the long term. 💡 Incentivized Evolution: The #world evolves, and so does Arweave. The #protocol is open, ready for change, and embraces an incentivized evolution model. Arweave positions itself not just as a #platform but as a versatile framework, encouraging innovative forks rewarded through a fair fork methodology. The beauty lies in the compatibility of these forks at the protocol layer, fostering cooperation over competition. 🌍 Unified Dataset for Permanence: Arweave isn't just about storing data; it's about unity. The encouragement of forks aligns seamlessly with the mission of permanent data storage. Keeping the dataset unified is in everyone's best interest, ensuring a collective stride towards a future where data stands the test of time. 🔍 Breaking It Down: Cryptographic Proofs: Ensuring the replication and secure storage of substantial parts of the Arweave dataset. Storage Endowment: A commitment to safeguarding data for a minimum of 200 years. Innovative Forks: Encouraging a continuous stream of innovation for permanent data storage. 📖 For those seeking a deeper understanding, explore DRAFT 17. Delve into the intricacies of Arweave's design, where proofs drive replication, the endowment fortifies storage, and the approach to forks sparks innovation. Join us on this odyssey towards a future where your data remains eternally secure and unaltered. Türkçe için : Arweave Ecosystem Only Arweave ar.io WeaveVM is now Load Network (@useload)

𝚊𝚛://𝚟𝚎𝚟𝚒𝚟𝚘 🐘

26,390 görüntüleme • 2 yıl önce

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!
2:24

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!

Andrew Ng

84,686 görüntüleme • 1 yıl önce

🚨BREAKING!!! Cardano isn’t just one chain anymore. We have 4 partner chains bringing unique value and use cases to the ecosystem. 1 launched on mainnet Midnight 3 partner chains are now actively building: • Materios Network (gaming + DeFi) • Vola Network (DePIN + storage) • Charli3 Oracles 📍Reliable, Secure, Trusted (oracle data) Built on Substrate + IOG integration layers. Secured via Cardano stake pools. This is the next phase of the ecosystem. Coupling this with Pyth Network 🔮 oracles, LayerZero interconnectivity, Dune analytics, Circle USDCx and selective disclosure transactions with Midnight, we're in for a crazy year!
8:34

🚨BREAKING!!! Cardano isn’t just one chain anymore. We have 4 partner chains bringing unique value and use cases to the ecosystem. 1 launched on mainnet Midnight 3 partner chains are now actively building: • Materios Network (gaming + DeFi) • Vola Network (DePIN + storage) • Charli3 Oracles 📍Reliable, Secure, Trusted (oracle data) Built on Substrate + IOG integration layers. Secured via Cardano stake pools. This is the next phase of the ecosystem. Coupling this with Pyth Network 🔮 oracles, LayerZero interconnectivity, Dune analytics, Circle USDCx and selective disclosure transactions with Midnight, we're in for a crazy year!

Pete | Beware of Scammers

16,484 görüntüleme • 3 ay önce

The Graph’s Sunrise of Decentralized Data is here 🌅 The hosted service has officially upgraded to The Graph Network, now the exclusive home of The Graph’s data services. Experience web3 data with ultra-fast syncing, reliable uptime, global redundancy and much more – all secured by decentralization. With support for over 50 chains, 6,000+ subgraphs on the network and available to query, and many new developer experience-enhancing features, anyone can easily tap into the network’s best-in-class performance. Thousands of dapps and teams like Aave, Art Blocks, Balancer, Snapshot.eth, Decentraland, ens.eth, Lido, Messari, PancakeSwap, and Sushi.com already rely on the network, which has successfully served billions of high-quality queries per quarter across thousands of subgraphs. The Graph’s decentralized model allows web3 developers to build confidently, knowing they are leveraging a scalable data layer to meet the industry’s growing activity. The future of web3 is built on The Graph.
0:27

The Graph’s Sunrise of Decentralized Data is here 🌅 The hosted service has officially upgraded to The Graph Network, now the exclusive home of The Graph’s data services. Experience web3 data with ultra-fast syncing, reliable uptime, global redundancy and much more – all secured by decentralization. With support for over 50 chains, 6,000+ subgraphs on the network and available to query, and many new developer experience-enhancing features, anyone can easily tap into the network’s best-in-class performance. Thousands of dapps and teams like Aave, Art Blocks, Balancer, Snapshot.eth, Decentraland, ens.eth, Lido, Messari, PancakeSwap, and Sushi.com already rely on the network, which has successfully served billions of high-quality queries per quarter across thousands of subgraphs. The Graph’s decentralized model allows web3 developers to build confidently, knowing they are leveraging a scalable data layer to meet the industry’s growing activity. The future of web3 is built on The Graph.

The Graph

100,364 görüntüleme • 2 yıl önce

This is Anagha Rajesh. And she is crazy. She wants to store data in bacterial DNA. Her startup is called BioCompute. And last year, they actually did it. They stored data in DNA and retrieved it in their tiny lab in Bengaluru. This is a huge moment. But why is she even doing it? Because DNA is the ultimate storage tool available to us. Just 1 gm of DNA can store about 215 petabytes of data - that's like storing over 2 million movies in 4K. On top of that - this data can last for literally 1000s of years. Right now, they still need to figure out a way to make the reading and writing process faster and cheaper. But if BioCompute solves this problem - we could theoretically store all the data created in the world every year in the palm of our hands. And that would be insane. P.S. Check out this video from vyom going to Anagha's lab and actually doing it.
0:21

This is Anagha Rajesh. And she is crazy. She wants to store data in bacterial DNA. Her startup is called BioCompute. And last year, they actually did it. They stored data in DNA and retrieved it in their tiny lab in Bengaluru. This is a huge moment. But why is she even doing it? Because DNA is the ultimate storage tool available to us. Just 1 gm of DNA can store about 215 petabytes of data - that's like storing over 2 million movies in 4K. On top of that - this data can last for literally 1000s of years. Right now, they still need to figure out a way to make the reading and writing process faster and cheaper. But if BioCompute solves this problem - we could theoretically store all the data created in the world every year in the palm of our hands. And that would be insane. P.S. Check out this video from vyom going to Anagha's lab and actually doing it.

Varun Guru

252,472 görüntüleme • 26 gün önce

A new roadmap. A New Era of The Graph 🗺️ The Graph’s new roadmap introduces a bold and transformative vision for the future of The Graph! The new R&D roadmap details an expansion of The Graph’s ability to serve web3’s growing demands for data access, while better serving builders and protocol contributors, and improving the overall simplicity and efficiency of the network. After three years of serving builders, The Graph Network is mature, reliable, and performant. The Graph ecosystem has followed through on its commitment to democratize access to blockchain data while also establishing subgraphs as a web3 standard. But The Graph’s innovation journey doesn’t end there. The New Era of The Graph is organized into five core objectives: 1️⃣ World of Data Services: Expanding to provide new data services beyond subgraphs to deliver a rich market of data on the network, serving novel use cases for data scientists and more. This will include more data sources, new query languages, and support for LLMs. 2️⃣ Developer Empowerment: Supporting developers through enhanced DevEx and tooling by introducing streamlined billing, clear pricing models, a new free query plan, and reduced gas fees. A more SaaS-like experience for devs, without compromising on decentralization! 3️⃣ Protocol Evolution & Resiliency: Delivering improvements resulting in a more resilient, flexible, and simple protocol, including updates to delegation. 4️⃣ Optimized Indexer Performance: Boosting network performance with improved Indexer tooling and operational capabilities to deliver increased scalability, reduce costs, and enhanced network reliability. 5️⃣ Interconnected Graph of Data: Creating tools for composable data and a global, organized knowledge graph – interlinking open data and making it easier to build upon. The new roadmap sets in motion an exciting evolution in web3 data infrastructure. In a phased rollout, The Graph will introduce many new features and benefits, including the integration of new data services, new query languages, enhanced developer tooling, improved UX + UI, alongside greater protocol efficiency and resilience. As this new era unfolds, The Graph crystallizes as the connective tissue across the many layers of the web3 stack, evolving into a comprehensive, interwoven graph of data equipped to serve every project dreamt up by web3’s innovators. Read the full announcement linked in the comment below!
0:47

A new roadmap. A New Era of The Graph 🗺️ The Graph’s new roadmap introduces a bold and transformative vision for the future of The Graph! The new R&D roadmap details an expansion of The Graph’s ability to serve web3’s growing demands for data access, while better serving builders and protocol contributors, and improving the overall simplicity and efficiency of the network. After three years of serving builders, The Graph Network is mature, reliable, and performant. The Graph ecosystem has followed through on its commitment to democratize access to blockchain data while also establishing subgraphs as a web3 standard. But The Graph’s innovation journey doesn’t end there. The New Era of The Graph is organized into five core objectives: 1️⃣ World of Data Services: Expanding to provide new data services beyond subgraphs to deliver a rich market of data on the network, serving novel use cases for data scientists and more. This will include more data sources, new query languages, and support for LLMs. 2️⃣ Developer Empowerment: Supporting developers through enhanced DevEx and tooling by introducing streamlined billing, clear pricing models, a new free query plan, and reduced gas fees. A more SaaS-like experience for devs, without compromising on decentralization! 3️⃣ Protocol Evolution & Resiliency: Delivering improvements resulting in a more resilient, flexible, and simple protocol, including updates to delegation. 4️⃣ Optimized Indexer Performance: Boosting network performance with improved Indexer tooling and operational capabilities to deliver increased scalability, reduce costs, and enhanced network reliability. 5️⃣ Interconnected Graph of Data: Creating tools for composable data and a global, organized knowledge graph – interlinking open data and making it easier to build upon. The new roadmap sets in motion an exciting evolution in web3 data infrastructure. In a phased rollout, The Graph will introduce many new features and benefits, including the integration of new data services, new query languages, enhanced developer tooling, improved UX + UI, alongside greater protocol efficiency and resilience. As this new era unfolds, The Graph crystallizes as the connective tissue across the many layers of the web3 stack, evolving into a comprehensive, interwoven graph of data equipped to serve every project dreamt up by web3’s innovators. Read the full announcement linked in the comment below!

The Graph

425,326 görüntüleme • 2 yıl önce

The $KLED Enterprise Portal Full Demo – Search and License Any Data in Seconds: For the last 6 weeks, we've had thousands of users sign up for the first data marketplace. We've paid out over $200,000 to them for uploading their camera rolls, homework, dashcam footage, etc. We've now amassed petabytes and petabytes of data from these users and large enterprises, and tagged it all with rich metadata. Now OpenAI, xAI, Google AI, or any other large lab can easily search and license that data using our newly completed enterprise portal. If you're a large lab, send me a DM and get access to the largest, never-before-seen consumer dataset on the planet. This is the biggest update for Kled since launch.
4:40

The $KLED Enterprise Portal Full Demo – Search and License Any Data in Seconds: For the last 6 weeks, we've had thousands of users sign up for the first data marketplace. We've paid out over $200,000 to them for uploading their camera rolls, homework, dashcam footage, etc. We've now amassed petabytes and petabytes of data from these users and large enterprises, and tagged it all with rich metadata. Now OpenAI, xAI, Google AI, or any other large lab can easily search and license that data using our newly completed enterprise portal. If you're a large lab, send me a DM and get access to the largest, never-before-seen consumer dataset on the planet. This is the biggest update for Kled since launch.

Avi Patel

91,697 görüntüleme • 11 ay önce

In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately
13:33

In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately

Wall Street Apes

57,720 görüntüleme • 1 ay önce

In Q1 2024, The Graph Network saw substantial growth in queries, reaching an all-time high of over 1.5 billion, up 65% from just shy of 1 billion in Q4’23. This growth accompanies updates recently shipped by core devs, enabling developers to easily take advantage of low cost, reliable and permissionless decentralized data ⚡ Here are the top 8 key takeaways from the Q1 2024 Participant Update ⬇️ 1️⃣ The Graph Network experienced significant growth, serving 1.5+ billion queries—a 65% quarter-over-quarter increase. Additionally, the number of subgraphs published on the network grew by over 30%, exceeding 1,900 subgraphs. 2️⃣ The Sunray Phase of the Sunrise of Decentralized Data concluded with the launch of key developer centric features including a free query plan, payment by credit card or GRT with access to 5️⃣0️⃣+ chains on the network. 3️⃣ The Graph added support for Bitcoin data by introducing a Bitcoin explorer module, a composable BRC-20 Substreams Module and a BRC-20 Substreams module, facilitating the integration of data into subgraphs for GraphQL queries. 4️⃣ Members of The Graph’s leadership teams traveled to Asia and participated in community events, engaged with the local web3 communities and strengthened The Graph ecosystem’s relationships with key thought leaders in the region. 5️⃣ Looking ahead, Sunbeam (Phase 2 of the Sunrise of Decentralized Data) concludes on June 12th. This milestone marks the end of the subgraph upgrade window in which hosted service subgraphs must upgrade to the network. 6️⃣ Firehose is now integrated with Go Ethereum. The 44% of Ethereum devs that make use of GETH can now get natively deeper insights, more precise event ordering, pattern matching, simpler and a more reliable integration, lower latency and super fast reprocessing times. 7️⃣ The Graph is saving the blobs! Developers now have two ways to access blob data (EIP-4844) - through either the consensus layer or the execution layer. 8️⃣ The Graph ecosystem can expect many exciting announcements coming in the near future around new data services live on the network and served by an ecosystem of Indexers earning GRT. Core Devs (Edge & Node, StreamingFast ⏫, Semiotic AI, The Guild, Messari, GraphOps | graphops.eth, Pinax, and ) will continue to execute on the New Era Roadmap by integrating SQL query capability and a SQL data service, File Hosting Service, new micropayment system Scalar TAP, AI data services and more. The Graph's Q1 2024 Participant Update establishes a clear watermark for web3 and decentralized data. The Graph’s expansion across many chains as well as progress on new developer experience enhancing features and new data services is expanding what’s possible with decentralized data in web3. Accessing more diverse data across more blockchains has never been easier for dapp developers and data consumers. The best part: The Graph has many more big announcements to come throughout 2024 🌟 Don’t miss any of the details. Watch the full update featuring Eva Beylin, Tegan Kline, 0xMaxTang, Etienne Brunet, and caro f here:
42:59

In Q1 2024, The Graph Network saw substantial growth in queries, reaching an all-time high of over 1.5 billion, up 65% from just shy of 1 billion in Q4’23. This growth accompanies updates recently shipped by core devs, enabling developers to easily take advantage of low cost, reliable and permissionless decentralized data ⚡ Here are the top 8 key takeaways from the Q1 2024 Participant Update ⬇️ 1️⃣ The Graph Network experienced significant growth, serving 1.5+ billion queries—a 65% quarter-over-quarter increase. Additionally, the number of subgraphs published on the network grew by over 30%, exceeding 1,900 subgraphs. 2️⃣ The Sunray Phase of the Sunrise of Decentralized Data concluded with the launch of key developer centric features including a free query plan, payment by credit card or GRT with access to 5️⃣0️⃣+ chains on the network. 3️⃣ The Graph added support for Bitcoin data by introducing a Bitcoin explorer module, a composable BRC-20 Substreams Module and a BRC-20 Substreams module, facilitating the integration of data into subgraphs for GraphQL queries. 4️⃣ Members of The Graph’s leadership teams traveled to Asia and participated in community events, engaged with the local web3 communities and strengthened The Graph ecosystem’s relationships with key thought leaders in the region. 5️⃣ Looking ahead, Sunbeam (Phase 2 of the Sunrise of Decentralized Data) concludes on June 12th. This milestone marks the end of the subgraph upgrade window in which hosted service subgraphs must upgrade to the network. 6️⃣ Firehose is now integrated with Go Ethereum. The 44% of Ethereum devs that make use of GETH can now get natively deeper insights, more precise event ordering, pattern matching, simpler and a more reliable integration, lower latency and super fast reprocessing times. 7️⃣ The Graph is saving the blobs! Developers now have two ways to access blob data (EIP-4844) - through either the consensus layer or the execution layer. 8️⃣ The Graph ecosystem can expect many exciting announcements coming in the near future around new data services live on the network and served by an ecosystem of Indexers earning GRT. Core Devs (Edge & Node, StreamingFast ⏫, Semiotic AI, The Guild, Messari, GraphOps | graphops.eth, Pinax, and ) will continue to execute on the New Era Roadmap by integrating SQL query capability and a SQL data service, File Hosting Service, new micropayment system Scalar TAP, AI data services and more. The Graph's Q1 2024 Participant Update establishes a clear watermark for web3 and decentralized data. The Graph’s expansion across many chains as well as progress on new developer experience enhancing features and new data services is expanding what’s possible with decentralized data in web3. Accessing more diverse data across more blockchains has never been easier for dapp developers and data consumers. The best part: The Graph has many more big announcements to come throughout 2024 🌟 Don’t miss any of the details. Watch the full update featuring Eva Beylin, Tegan Kline, 0xMaxTang, Etienne Brunet, and caro f here:

The Graph

27,400 görüntüleme • 2 yıl önce

AthenaX Roundtable EP.2 is LIVE! ——— Metis🌿 isn’t just an Ethereum L2 anymore. It wants to become the first AI-native blockchain economy. In this episode, we sit down with Tom Ngo, CEO of Metis, advisor to LazAI Network, to talk about how the project is moving from a typical Ethereum Layer 2 toward an AI-native blockchain ecosystem and what it really means beyond buzzwords. Here’s what we unpack together: Why Metis says “we’re not just an L2” and how their AI pivot has actually been in the works for over 18 months What an AI-native blockchain looks like in real life, not just in theory Why verified data is the core of AI on-chain and how concepts like Lazbubu are making data something you can actually own and interact with How AI agents could make blockchain invisible for users What it takes to lead a team through a major shift while staying true to the original vision ——— Timestamps 00:00 Introduction to Metis and Its Vision 03:55 Transitioning to AI: The New Frontier 06:56 Personal Journey into Blockchain and Metis 09:48 The Importance of Data in AI and Blockchain 13:00 Navigating Market Pressures and User Expectations 16:04 The Unified Experience of Andromeda and Hyperion 19:09 The Future of AI in Blockchain 22:12 LazBubu: Making Data Playable 24:47 Innovation and the Path Forward 27:56 Defining Success in the Blockchain Space ——— Resources Tom Ngo Rea Follow AthenaX on: X: Spotify: TikTok: Instagram: Apple Podcast:
30:47

AthenaX Roundtable EP.2 is LIVE! ——— Metis🌿 isn’t just an Ethereum L2 anymore. It wants to become the first AI-native blockchain economy. In this episode, we sit down with Tom Ngo, CEO of Metis, advisor to LazAI Network, to talk about how the project is moving from a typical Ethereum Layer 2 toward an AI-native blockchain ecosystem and what it really means beyond buzzwords. Here’s what we unpack together: Why Metis says “we’re not just an L2” and how their AI pivot has actually been in the works for over 18 months What an AI-native blockchain looks like in real life, not just in theory Why verified data is the core of AI on-chain and how concepts like Lazbubu are making data something you can actually own and interact with How AI agents could make blockchain invisible for users What it takes to lead a team through a major shift while staying true to the original vision ——— Timestamps 00:00 Introduction to Metis and Its Vision 03:55 Transitioning to AI: The New Frontier 06:56 Personal Journey into Blockchain and Metis 09:48 The Importance of Data in AI and Blockchain 13:00 Navigating Market Pressures and User Expectations 16:04 The Unified Experience of Andromeda and Hyperion 19:09 The Future of AI in Blockchain 22:12 LazBubu: Making Data Playable 24:47 Innovation and the Path Forward 27:56 Defining Success in the Blockchain Space ——— Resources Tom Ngo Rea Follow AthenaX on: X: Spotify: TikTok: Instagram: Apple Podcast:

AthenaX

140,644 görüntüleme • 8 ay önce

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
5:34

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 görüntüleme • 10 ay önce

New startup company will put ‘Mini Data Centers’ on the side of residential homes all over America Companies Nvidia and PulteGroup are patterning with SPAN, “A major U.S home builder is now making small fractional data centers, or they call them nodes that can be put on the side of residential homes.” “These could negate the need to build as many hyperscalers and AI cloud providers Just tap into the node network like a regular data center now SPAN, collaborated with NVIDIA using its technology in the system span claims it can install 8,000 of these units about six times faster and at five times lower cost than the construction of a typical centralized 100 megawatt data center of the same size.” In return for letting this company put a mini data center on the side of your home, you’ll get a $150 credit on your electricity bill In some locations you could get free electricity and internet
1:35

New startup company will put ‘Mini Data Centers’ on the side of residential homes all over America Companies Nvidia and PulteGroup are patterning with SPAN, “A major U.S home builder is now making small fractional data centers, or they call them nodes that can be put on the side of residential homes.” “These could negate the need to build as many hyperscalers and AI cloud providers Just tap into the node network like a regular data center now SPAN, collaborated with NVIDIA using its technology in the system span claims it can install 8,000 of these units about six times faster and at five times lower cost than the construction of a typical centralized 100 megawatt data center of the same size.” In return for letting this company put a mini data center on the side of your home, you’ll get a $150 credit on your electricity bill In some locations you could get free electricity and internet

Wall Street Apes

258,163 görüntüleme • 2 ay önce

🚨 NEW Podcast w Eliott eliott who is working with Yonatan Sompolinsky on Oracles - You'll love this episode! Full YT link - We unpack the critical role oracles play in bridging off-chain data to blockchains, a cornerstone for DeFi applications. Elliot exposes the limitations of current oracle solutions like Chainlink, including risks of centralization, node collusion, and data manipulation. Further on in the episode, Eliott shares his vision to create a trustless, manipulation-resistant "ORACLE GAME " for Kaspa’s layer-1 built on Kaspa’s parallel consensus to prevent oracle manipulation. Learn why existing oracle models fall short and how $KAS #Kaspa aims to set a new standard for secure, decentralized data feeds. Topics 1. What Are #BlockchainOracles 2. Why Blockchains Need #Oracles 3. Challenges with Current Oracle 4. Chainlink’s Flaws: Centralization & Data Manipulation 5. Oracle Extractable Value (#OEV) & Collusion Risks 6. Alternative Oracle Models: Pyth & Flare Network 7. Elliot’s Research & Kaspa’s Oracle Solution 8. Practical Challenges & Market Maker Dynamics 9. Vision for #Kaspa’s Oracles --------------- This video is for educational purposes only and not financial advice. Always conduct your own research before engaging with blockchain projects or investments. $KAS #KASPA #oracles #blockchainoracles
1:18

🚨 NEW Podcast w Eliott eliott who is working with Yonatan Sompolinsky on Oracles - You'll love this episode! Full YT link - We unpack the critical role oracles play in bridging off-chain data to blockchains, a cornerstone for DeFi applications. Elliot exposes the limitations of current oracle solutions like Chainlink, including risks of centralization, node collusion, and data manipulation. Further on in the episode, Eliott shares his vision to create a trustless, manipulation-resistant "ORACLE GAME " for Kaspa’s layer-1 built on Kaspa’s parallel consensus to prevent oracle manipulation. Learn why existing oracle models fall short and how $KAS #Kaspa aims to set a new standard for secure, decentralized data feeds. Topics 1. What Are #BlockchainOracles 2. Why Blockchains Need #Oracles 3. Challenges with Current Oracle 4. Chainlink’s Flaws: Centralization & Data Manipulation 5. Oracle Extractable Value (#OEV) & Collusion Risks 6. Alternative Oracle Models: Pyth & Flare Network 7. Elliot’s Research & Kaspa’s Oracle Solution 8. Practical Challenges & Market Maker Dynamics 9. Vision for #Kaspa’s Oracles --------------- This video is for educational purposes only and not financial advice. Always conduct your own research before engaging with blockchain projects or investments. $KAS #KASPA #oracles #blockchainoracles

XXIM - Decentralise Capitalism

15,872 görüntüleme • 9 ay önce

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?
12:54

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

steve

640,114 görüntüleme • 3 yıl önce

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast
1:29

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

AI Evolution

15,565 görüntüleme • 1 ay önce

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!
5:42

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

Alex Ratner

49,924 görüntüleme • 1 yıl önce

GeoLibre v1.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python
1:12

GeoLibre v1.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

Qiusheng Wu

29,386 görüntüleme • 28 gün önce

🚨 Georgia Power is forcing a family off their farm with eminent domain for a Data Center “I'm fighting for survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This data center project affects over 330 private properties. Georgia Power says it will negotiate purchases and easements and use eminent domain Georgia Power claims its to strengthen the grid for the growing energy demand in Georgia (due to many new data centers) The lines are widely linked to Project Sail This isn’t a small operation. Project Sail is a $17 billion hyperscale data center campus by Prologis, Atlas that includes 9 massive buildings totaling up to 4.34 million square feet on 829 acres. It will demand hundreds of megawatts of continuous power equivalent to what a small city uses We cannon allow data centers to take priority over farmers
2:00

🚨 Georgia Power is forcing a family off their farm with eminent domain for a Data Center “I'm fighting for survival of my cattle farm. I'm here because a massive data center was approved just a couple of miles from my land — and I'm being hounded by Georgia Power for an easement to build transmission lines through my property for the data center” “I'm a local farmer, not an industrial developer. These 500-kV lines aren't for me. They are for the data centers that the boards and surrounding counties continue to approve. I have mail from lawyers stacking up on my kitchen table wanting to take my case because they know my land is being targeted for eminent domain — These easements are permanent. They affect my ability to graze my cattle, they lower my property value, and they destroy the rural character of this county forever. This board makes decisions to approve these massive, massive projects, but it's residents like me, young people trying to build a life here, who pay the price. You're voting to turn our farms into a network of high-voltage wires and noisy industrial buildings. I'm asking you to realize the real-world impacts of your votes. Every time you say yes to a data center, you're saying no to a local farmer. We aren't just numbers on a map. We are the future of the county, and right now you're making that future impossible.“ This data center project affects over 330 private properties. Georgia Power says it will negotiate purchases and easements and use eminent domain Georgia Power claims its to strengthen the grid for the growing energy demand in Georgia (due to many new data centers) The lines are widely linked to Project Sail This isn’t a small operation. Project Sail is a $17 billion hyperscale data center campus by Prologis, Atlas that includes 9 massive buildings totaling up to 4.34 million square feet on 829 acres. It will demand hundreds of megawatts of continuous power equivalent to what a small city uses We cannon allow data centers to take priority over farmers

Wall Street Apes

434,530 görüntüleme • 2 ay önce

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”
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Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”

David Fields

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