IoTeX Launches Quicksilver Beta and Expands AI Infrastructure

In June 2025, IoTeX launched a beta interface for Quicksilver, a decentralized physical infrastructure network (DePIN) framework that allows AI agents to interact with data from connected devices. This interface enables developers to create and deploy AI agents, while users can query these agents through chat or API. On June 19, IoTeX implemented a significant upgrade (v2.2.0) that reduced block time from 5 seconds to 2.5 seconds, enhancing the network’s theoretical throughput to 2,000 transactions per second (TPS). Additionally, IoTeX introduced a roadmap for Realms, which aims to create domain-specific ecosystems that group AI agents and contributors to facilitate structured intelligence across various sectors such as transportation and healthcare.
Despite a decline in average daily active wallets by 26% quarter-over-quarter (QoQ) to 6,600, this figure still represents a remarkable 872% increase year-over-year (YoY). Similarly, average daily transactions dropped by 25% QoQ to 222,300 but were up 750% YoY. The protocol’s revenue also saw a significant decrease of 53% QoQ, totaling $94,800, primarily due to a 93% drop in ioID activation fees. However, the overall revenue remains up 505% YoY, indicating a robust growth trajectory despite recent fluctuations in activity.
The Quicksilver framework is designed to integrate AI agents with DePINs, enabling them to process real-world data and perform automated actions. The W3bstream layer verifies data from devices before it is utilized by AI agents. IoTeX’s ioID framework provides a decentralized identity for devices, enhancing their interaction capabilities within the network. As IoTeX continues to evolve, it aims to solidify its position in the AI and DePIN sectors, with the Realms system expected to incentivize data contributors and enhance the quality of datasets for AI applications. This strategic direction highlights IoTeX’s commitment to building a comprehensive ecosystem that leverages physical intelligence for various applications.
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