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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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Load Network

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47,038 Aufrufe • vor 1 Jahr •via X (Twitter)

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ar.io networkvor 1 Jahr

@sedaprotocol huge ship - congrats on the release 🫡🐘

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mousevor 1 Jahr

@ar_io_network @sedaprotocol Huge huge!

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Kvor 1 Jahr

@ar_io_network @sedaprotocol 🔥

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Arweave Oasisvor 1 Jahr

@ar_io_network @sedaprotocol awsome！

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Gondal Gandul 🆓🐐vor 1 Jahr

@ar_io_network @sedaprotocol @Brianeedsleep ini apa bang?

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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 by Blockworks, 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:

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A new HUGE data center campus called Project Open Sky is being planned in Oklahoma. The land will be over a square mile with 6 Data Centers One American family all built houses together on a compound, and the data center campus is planned less than 300 feet away from their homes The residents say they already have a water pressure issue and this is going to mean there won’t be enough water to farm or even for their homes The data center campus could use as 27.4 million gallons per year “They literally have an entire square mile and are pushing to get more — Cloverleaf Infrastructure is the company behind Project Open Sky, which is in talks to build a 633-acre campus with as many as 6 data centers on it” This is going to destroy the lives of the residents in this town
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A new HUGE data center campus called Project Open Sky is being planned in Oklahoma. The land will be over a square mile with 6 Data Centers One American family all built houses together on a compound, and the data center campus is planned less than 300 feet away from their homes The residents say they already have a water pressure issue and this is going to mean there won’t be enough water to farm or even for their homes The data center campus could use as 27.4 million gallons per year “They literally have an entire square mile and are pushing to get more — Cloverleaf Infrastructure is the company behind Project Open Sky, which is in talks to build a 633-acre campus with as many as 6 data centers on it” This is going to destroy the lives of the residents in this town

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66,687 Aufrufe • vor 9 Tagen

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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

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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 Aufrufe • vor 10 Monaten

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

258,581 Aufrufe • vor 4 Monaten

🚨 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 Aufrufe • vor 11 Monaten

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

640,176 Aufrufe • vor 3 Jahren

A model is only as good as its data, and we’ve long since exhausted the internet. From here on out, model progress is gated by data production. ’s Brendan (can/do) joined us at our Sovereign AI event to talk about how RL environments get built, and why your data might be your real moat: 00:00 Introduction 00:47 A short history of the data market: crowdsourcing to agentic data 02:29 What an RL environment is: worlds, apps, tasks 03:57 Why only humans can measure the frontier 05:35 Building verifiers is the hard part 06:44 Walkthrough: a real legal RL environment 08:18 Leaderboards — and what open weights change 09:45 Post-training results on Apex Agents 11:17 Three ways companies buy data 12:49 Q&A: How do you price data? 14:17 Q&A: What "data quality" actually means 16:42 Q&A: The misunderstanding about synthetic data 18:17 Q&A: Why RL environments now — and what comes after 21:20 Q&A: Can you scale rubric generation with models? 23:00 Q&A: RL environments for cyber defense 25:33 Q&A: Build data in-house or partner?
26:21

A model is only as good as its data, and we’ve long since exhausted the internet. From here on out, model progress is gated by data production. ’s Brendan (can/do) joined us at our Sovereign AI event to talk about how RL environments get built, and why your data might be your real moat: 00:00 Introduction 00:47 A short history of the data market: crowdsourcing to agentic data 02:29 What an RL environment is: worlds, apps, tasks 03:57 Why only humans can measure the frontier 05:35 Building verifiers is the hard part 06:44 Walkthrough: a real legal RL environment 08:18 Leaderboards — and what open weights change 09:45 Post-training results on Apex Agents 11:17 Three ways companies buy data 12:49 Q&A: How do you price data? 14:17 Q&A: What "data quality" actually means 16:42 Q&A: The misunderstanding about synthetic data 18:17 Q&A: Why RL environments now — and what comes after 21:20 Q&A: Can you scale rubric generation with models? 23:00 Q&A: RL environments for cyber defense 25:33 Q&A: Build data in-house or partner?

Pat Grady

65,994 Aufrufe • vor 23 Tagen

🚨 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 Aufrufe • vor 3 Monaten

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

50,043 Aufrufe • vor 1 Jahr

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

30,046 Aufrufe • vor 2 Monaten