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Grass is a decentralized web scraping protocol that rewards users for sharing internet bandwidth — data collected is used to train AI models. On Feb. 14 touch grass hit an ATH in daily data collected – with 1M+ GB scraped 🤯 more on Grass from with MR SHIFT 🦁

Solana

4,127,960 subscribers

26,447 просмотров • 1 год назад •via X (Twitter)

Наука и технологии

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Комментарии: 18

Фото профиля Solana

Solana1 год назад

Community owned networks are the future. 13 DePIN products you can use on Solana today 🧵

Фото профиля Solana

Solana1 год назад

NATIX (@NatixNetwork) is a global mapping network offering two major products: 1️⃣ VX360 — turning Tesla dashcams into data goldmines for safer autonomous driving 2️⃣ Drive&app — where your phone gathers mapping data from daily drives — live on the Apple and Google app stores

Фото профиля Solana

Solana1 год назад

.@Gradient_HQ utilizes idle compute from edge devices, PCs, and local servers to perform real time processing tasks. Their first product — Sentry Nodes — use p2p connections to confirm liveness and measure latency between nodes. There are 1.3M active nodes as of Feb. 26th.

Фото профиля Solana

Solana1 год назад

Hivemapper is taking on big tech mapping incumbents with a community-built map — everyday drivers contribute to the network and earn with the @Hivemapper Bee dashcam. They recently started serving data to TomTom — #1 real time traffic services provider — to improve their maps.

Фото профиля Solana

Solana1 год назад

Dabba (@DabbaNetwork) is a wireless DePIN focused on expanding internet access in India — the 2nd largest telecom market in the world Set up your own hotspot to contribute to the network and earn — @dawnjohnphilip shows you how in just 2 mins

Фото профиля Solana

Solana1 год назад

Roam (@WeRoamXyz) unifies over 1M WiFi hotspots into a secure global network on Solana by rewarding users for contributing. It uses decentralized identifiers (DIDs) and verifiable credentials to keep users’ data private. Download on the app store!

Фото профиля Solana

Solana1 год назад

DeCharge (@DeCharge__) is a global EV charging network built on Solana ⚡ Their first product, DeCharge Beast, is a 7KW community charger powered by @dephynetwork that generates income for you as electric vehicles utilize it.

Фото профиля Solana

Solana1 год назад

Dawn is a decentralized broadband network built by the @andrena_wifi team. @dawninternet aims to shift internet infra into individual homes and slash consumer internet bills by around 80%. Watch @CipherResearchx explain in 3 mins.

Фото профиля Solana

Solana1 год назад

Kuzco (@Kuzco_xyz) transforms idle local GPU power into affordable cloud computing. Compute is then offered for major LLM models like Meta’s Llama with up to 90% cost savings vs. traditional providers. Start contributing at inference(dot)supply

Фото профиля Solana

Solana1 год назад

.@GEODNET_ is a network of satellite miners delivering RTK correction data for ~100x more accurate GPS positioning. Low-power stations (<2W) support robots & devices within 20-40km, correcting errors from satellite systems and space weather. 2024 recap video:

Фото профиля Solana

Solana1 год назад

.@AmbiosNetwork an environmental monitoring DePIN where individuals deploy sensors to collect real-time air quality data, earn rewards, and help orgs make informed environmental decisions. More from cofounder @luckyluca with @gizmothegizzer:

Фото профиля Solana

Solana1 год назад

Pipe (@pipenetwork) is a decentralized content delivery network (dCDN) that accelerates delivery by leveraging users’ excess storage & bandwidth. More nodes = faster delivery. More from @DavidRhodus at Breakpoint '24

Фото профиля Solana

Solana1 год назад

Get fit and earn while doing it — CUDIS (@CudisWellness) wearables track your health journey with metrics like sleep quality, heart rate and VO2 max. They recently released the CUDIS 002 Ring.

Фото профиля Solana

Solana1 год назад

These are just a few examples of DePINs powered by Solana -- nCMOs, please drop more that we missed below 🫡

Фото профиля CrispyBull

CrispyBull1 год назад

🚀 Ethereum is scaling up! With the gas limit raised beyond 30M and the Pectra update doubling Layer 2 capacity, ETH is gearing up for faster, cheaper transactions. Are we entering a new era for Ethereum? 🔥 #Ethereum #Crypto #Blockchain #ETHUpdate#DeFi

Фото профиля AJ

AJ1 год назад

@getgrass_io @Arthur_0x @KevinWSHPod Grass is the biggest of all DePINs With the largest payout!

Фото профиля Connan

Connan1 год назад

@getgrass_io @Arthur_0x @KevinWSHPod Touch grass

Фото профиля Mhayo

Mhayo1 год назад

@getgrass_io @Arthur_0x @KevinWSHPod AI + blockchain = future. $WAM knows this, now Grass knows it too

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In the second episode of Scenius Studio's mini-series "The Use-Case", I sit down with Andrej Co-Founder of touch grass. Grass gives users the ability to earn ownership in the Grass network by supplying the protocol with their unused internet bandwidth for data scraping purposes (something that is already happening to most of us and we don’t get paid!). The grass protocol packages this scraped web data and sells it to AI companies who have insufficient data to further develop their models. With over 3 millions users and millions of annualized revenue, Grass is a real commercial business with a roadmap that makes it one of the most exciting projects at the intersection of crypto x AI and data. In this episode we discuss: ➔ Andrej’s background in physics, finance, and sports betting ➔ Big companies using your IP address without your knowledge or permission ➔ How the Grass protocol puts a toll booth on your internet bandwidth highway ➔ Packaging web scraped data and selling it to AI companies building Multi-Modal models ➔ Dynamics between the Grass Protocol and the labs entity developing Grass’ IP ➔ Protocol design decisions to ensure that all tokenholders (VCs, team, and community) are aligned ➔ Why Grass needed to be built on crypto rails to maximize its potential ➔ The future of LLMs and how they will search for context and information Hope you enjoy this episode of Scenius Studio's "The Use-Case". Links to listen in bio or below👇

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When AI gives bad advice, it can have real consequences. Grass is improving the way AI interacts with information by providing tools that enable access to accurate, verifiable web data. Join millions of users and download Grass today.

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You can now scrape any website with AI in two clicks. Thunderbit is a zero-setup web scraper that extracts data from any site instantly, it even allows you subpage scraping. Here’s how to try free:

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🎉 Season 2 of the Sahara AI Data Services Platform is live! With 2M+ on our waitlist, we’ve onboarded 100K new contributors to build a more equitable, collaborative AI economy. More Users. More Tasks. More Rewards. Let's dive into what's new 👇

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Training robot foundation models faces two key hurdles: how to get enough data to train an effective model, and how to make sure that new skills can be acquired quickly. The team at Rhoda AI believes that the answer is training Direct Video Action models from web data. Web data is plentiful, to the point where Rhoda can train their base model on hundreds of years of video data. And then, with the addition of robot data, they can quickly adapt it to new tasks with as little as 20 hours of in-domain data, performing complex, multi-step manipulation tasks with their purpose-built video foundation model. Tongzhou Mu 🤖🦾🦿 Eric Chan and Changan Chen joined us to talk more about their approach. Watch Episode #79 of RoboPapers, with Michael Cho - Rbt/Acc, Chris Paxton, and Jiafei Duan, to learn more!

Training robot foundation models faces two key hurdles: how to get enough data to train an effective model, and how to make sure that new skills can be acquired quickly. The team at Rhoda AI believes that the answer is training Direct Video Action models from web data. Web data is plentiful, to the point where Rhoda can train their base model on hundreds of years of video data. And then, with the addition of robot data, they can quickly adapt it to new tasks with as little as 20 hours of in-domain data, performing complex, multi-step manipulation tasks with their purpose-built video foundation model. Tongzhou Mu 🤖🦾🦿 Eric Chan and Changan Chen joined us to talk more about their approach. Watch Episode #79 of RoboPapers, with Michael Cho - Rbt/Acc, Chris Paxton, and Jiafei Duan, to learn more!

RoboPapers

24,677 просмотров • 4 месяцев назад

$ORCL founder Larry Ellison says next phase of AI will come from combining public models with proprietary enterprise data. These 5 names own some of the deepest proprietary data moats for that transition: 1. $PLTR sits inside some of most sensitive enterprise & government datasets in the world operationalizing AI across classified defense data, regulated healthcare data & Fortune 500 workflows that public models will never train on. 2. $META owns the world’s largest proprietary social graph with 3.5B+ daily active users generating text, image, video & voice data at a scale no competitor can replicate. 3. $GOOGL owns one of deepest consumer data stacks in world with 8.5B+ daily Search queries, 2.7B+ YouTube monthly users, 2B+ Maps users, 1.8B+ Gmail users & 3B+ Android devices feeding Gemini with proprietary data competitors cannot replicate. 4. $RDDT owns one of largest archives of human conversation, opinion & consumer behavior online with 20+ years of proprietary discussion data now being licensed to frontier labs like OpenAI with data licensing revenue could reach $400M+ annually by 2027. 5. $TEM owns one of largest clinical-grade oncology datasets in the world with 45M+ de-identified patient records across genomics, imaging & clinical data that healthcare AI structurally needs.

$ORCL founder Larry Ellison says next phase of AI will come from combining public models with proprietary enterprise data. These 5 names own some of the deepest proprietary data moats for that transition: 1. $PLTR sits inside some of most sensitive enterprise & government datasets in the world operationalizing AI across classified defense data, regulated healthcare data & Fortune 500 workflows that public models will never train on. 2. $META owns the world’s largest proprietary social graph with 3.5B+ daily active users generating text, image, video & voice data at a scale no competitor can replicate. 3. $GOOGL owns one of deepest consumer data stacks in world with 8.5B+ daily Search queries, 2.7B+ YouTube monthly users, 2B+ Maps users, 1.8B+ Gmail users & 3B+ Android devices feeding Gemini with proprietary data competitors cannot replicate. 4. $RDDT owns one of largest archives of human conversation, opinion & consumer behavior online with 20+ years of proprietary discussion data now being licensed to frontier labs like OpenAI with data licensing revenue could reach $400M+ annually by 2027. 5. $TEM owns one of largest clinical-grade oncology datasets in the world with 45M+ de-identified patient records across genomics, imaging & clinical data that healthcare AI structurally needs.

Shay Boloor

265,610 просмотров • 3 месяцев назад