dapengliu25

@dapengliu25

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30 Followers

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🚀💥 Latin America’s telecom game is leveling up! 📈✨ Time to unleash the DePIN power! Let’s goooo! 🌎💪🦍 #ApeWorld #CryptoRevolution 🌟🔗 Check it out! 👀👉

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🚀💥 Latin America’s telecom game is leveling up! 📈✨ Time to unleash the DePIN power! Let’s goooo! 🌎💪🦍 #ApeWorld #CryptoRevolution 🌟🔗 Check it out! 👀👉

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https://x.com/evilcos/status/1877184891521061194

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https://x.com/lubi366/status/1877338257375244318

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https://x.com/lubi366/status/1877308414805553370

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https://x.com/lubi366/status/1877184874400145626

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https://x.com/lubi366/status/1877150262495711708

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https://x.com/bishengkegs/status/1877336535655387370

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https://x.com/bishengkegs/status/1876981900205814233

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https://www.youtube.com/watch?v=xRE4Thcs2kA

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In the weeks ahead, the Grass Network will roll out Phase 2 of the Sion upgrade, a major leap forward in scalability, efficiency, and data throughput. As a quick recap, Phase 1 delivered a breakthrough in scraping efficiency, maximizing public web data retrieval without increasing compute, driving a massive surge in network activity, and paving the way for Phase 2. Phase 2 of the upgrade horizontally scales compute, boosts network throughput by 10x, and enables real-time multimodal scraping (such as public video data) at petabyte scale.

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What is Sion? Sion is a network upgrade designed to optimize web data retrieval at scale, allowing Grass to scrape over 1 petabyte of multimodal web data per day. To put this into perspective, at this scale, Grass will be scraping enough data to fill approximately 92 football fields' worth of flash drives each day. This level of compute, bandwidth, and algorithmic efficiency makes Grass the most accessible multimodal data provider in the AI industry.

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good share. thanks

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How does Sion work? Sion fundamentally changes how the Grass Network processes large-scale data retrieval by optimizing scraping efficiency and scaling infrastructure to sustain higher throughput.

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Phase 1 - Optimizing Network Efficiency: Complete The first phase of Sion focused on improving the way public web data was scraped and processed without adding additional compute. Optimizing scraping algorithms increased efficiency, leading to a significant spike in web data retrieval. This pushed the network to its operational limits, reinforcing the need for a broader infrastructure expansion in Sion Phase 2 to sustain long-term scaling.

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Phase 2 - Scaling Infrastructure: Rolling out in the weeks ahead With the groundwork laid in Phase 1, Phase 2 is about deploying these optimizations at scale by: Horizontally scaling compute – Distributing workloads across more machines, allowing for parallel processing and higher sustained scraping speeds. Scaling multimodal data retrieval – New adaptive scraping techniques allow for processing 4K video, images, and text without bottlenecks.

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Expanding network bandwidth to beyond 1 terabit per second – Phase 2 removes throughput bottlenecks by distributing workloads across more machines, allowing sustained 10x data retrieval efficiency. A scale which makes Grass one of the most performant decentralized data scraping networks in the world.

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Why Sion? The demand for multimodal data—especially video—has surged as AI advances into generative, autonomous systems, and robotics. Multimodal models require vast, high-quality datasets to improve realism and motion accuracy. From AI-generated video to autonomous perception, these systems rely on large-scale multimodal data to function effectively.

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Yet, acquiring this data at the necessary scale remains a challenge. AI companies developing frontier models need exponentially more data to stay competitive, but the current options for sourcing it are costly, fragmented, and difficult to scale. Training the next generation of AI requires petabytes of high-quality data, yet existing solutions cannot efficiently sustain data retrieval at this magnitude.

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The Sion upgrade expands Grass’s capacity, enabling sustained, petabyte-scale multimodal data scraping on a daily basis. By horizontally scaling compute and optimizing scraping algorithms, Sion removes the bottlenecks. This expansion allows the network to process and deliver high-quality multimodal datasets at scale. With Grass, developers can now access data at a scale unmatched by traditional solutions. Grass Network Before vs. After Sion

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