Addressing Digital Resource Exploitation

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This chapter focuses on the motivations behind a project designed to combat resource exploitation in the digital realm, particularly for contributors to public web data. It details the architecture of the GRASS network, which efficiently acquires data using a decentralized approach, and emphasizes challenges such as data poisoning and the need for better accountability in AI systems. The discussion also contrasts GRAS's ethical web scraping capabilities with traditional methods used by major tech companies, highlighting its advantages in providing timely access to information.

In this episode, we dive deep into GRASS, a revolutionary decentralized network for web scraping and data collection. Andrej, from GRASS, explains how their platform is democratizing access to web data for AI development. We explore the technical aspects of the GRASS network, its innovative approach to data collection, and its potential impact on the AI industry. The conversation covers topics ranging from data poisoning prevention to the intersection of crypto and AI, concluding with insights into GRASS's future plans and expansion into mobile platforms.

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Timestamps

(0:00) Introduction

(2:11) Global Web Resource Problem

(16:50) Permissionless III Ad

(18:04) Polygon Ad

(18:55) Live Context Retrieval

(25:15) Data Labeling & RLHF Program

(32:59) Crypto & AI Intersection

(39:43) Why Solana & Business Future

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