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NEW You can now automatically replay historical data with LaserStream for the last 24 hours (previously was 3,000 slots or ~20 minutes) The longer replay window and 60 blocks/s catch up speed means more time to recover, faster repairs, and better data integrity Enjoy

Helius

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14,017 просмотров • 8 месяцев назад •via X (Twitter)

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Introducing Grayscale Space and Time Trust $SXT 🪐 , backed by M12 - Microsoft's Venture Fund and integrated with Microsoft Fabric*, connects the power of decentralized blockchains with the speed and flexibility of traditional databases through: 🏢 Enterprise-Readiness: Backed by Microsoft and integrated into Microsoft Fabric*, allowing developers to easily access data from networks like #Bitcoin, Sui, and #Ethereum. 🖊️ Proof of SQL: Verifies queries on tamperproof data using zero-knowledge proofs without needing to rerun or reveal underlying data. ⏳ Decentralized + Scalable: Blends blockchain security with traditional database speed and accessibility for reliable, real-time data access. ✅ Verifiable Data: As we enter the new age of AI, transparency is paramount. Space and Time enables verifiable data, helping ensure we can trust the datasets that power AI systems and smart contract applications. See important disclosures and learn more about the Grayscale Space and Time Trust: *Source: Space and Time press release, May 20, 2025.

Introducing Grayscale Space and Time Trust $SXT 🪐 , backed by M12 - Microsoft's Venture Fund and integrated with Microsoft Fabric, connects the power of decentralized blockchains with the speed and flexibility of traditional databases through: 🏢 Enterprise-Readiness: Backed by Microsoft and integrated into Microsoft Fabric, allowing developers to easily access data from networks like #Bitcoin, Sui, and #Ethereum. 🖊️ Proof of SQL: Verifies queries on tamperproof data using zero-knowledge proofs without needing to rerun or reveal underlying data. ⏳ Decentralized + Scalable: Blends blockchain security with traditional database speed and accessibility for reliable, real-time data access. ✅ Verifiable Data: As we enter the new age of AI, transparency is paramount. Space and Time enables verifiable data, helping ensure we can trust the datasets that power AI systems and smart contract applications. See important disclosures and learn more about the Grayscale Space and Time Trust: *Source: Space and Time press release, May 20, 2025.

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We’ve stored every tick from decades ago up to the present. You can backtest in bar by bar mode, or replay real market scenarios tick by tick for any symbol and timeframe. Set the speed to real 1H, 1M and it behaves exactly as if you actually went back in time!

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First try with Vercel's new Postgres database! Was so quick to set up 🤯 here I've got a collaborative form built with Liveblocks, and I'm having it automatically sync data to the database. More info 🧵

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OpenAI's Deep Research is getting a run for its money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!

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BSCN

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Introducing my new OSS framework: OhSnap provides really simple way to record and reproduce the data your users saw when encountering an issue (bug/crash), integration in your project should take a few minutes at most. Majority of bugs are related to data you have to deal with and often times we have to work with frequently changing data via network API's. Even if you have access to multiple environments (prod/staging/dev) it's still going to be PITA to reproduce a lot of bugs your user saw, since we often get to them a long time after the bug occured... OhSnap allows you to easily record any data your app downloads, pack it and put it on server so that you can replay it on your device later on, while connected to debugger and save hours of development time trying to figure out what exactly they experienced! Here's a demo of 2 app instances running, and me manipulating what server reply I'll be getting, there is 1 line of code needed to record and reply this data (outside of just setting up your framework). I built this so that I can show dev tool building process for the members of which I encourage you to join if you want to put your engineering efficiency at a different level😉

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