HomeBlockchain & Crypto"Rookie" DePIN projects are preparing for the next busy months of 2024

“Rookie” DePIN projects are preparing for the next busy months of 2024

DePIN is regarded as one of the most robust narratives in the year 2024, primarily owing to its profound association with real-world applications, captivating the attention of conventional players. Besides big names like Filecoin, Render, Akash and Helium, there are numerous promising new projects currently launching and diligently building their communities and products, preparing for a forthcoming era characterized by an influx of positive news regarding advancements in the domain of physical network innovation.

I. So, what is DePIN?

DePIN is a term coined by Messari, which stands for Decentralised Physical Infrastructure Network, introducing an innovative token allocation methodology, complemented by a consensus mechanism called PoPW (Proof of Physical Work).

It is well recognized that one of the most formidable characteristics of crypto-economic protocols is their inherent ability to establish incentive structures that foster worldwide participation in collective objectives, free from the need for authorization. These incentive structures can be thoughtfully crafted to facilitate comprehensive coordination, driving the attainment of specific aims. 

DePIN serves to fortify the fundamental tenets of sharing economics by harnessing surplus and untapped hardware resources possessed by decentralized individuals and collectives. DePIN addresses issues of centralized physical infrastructure networks such as the risk of attacks, decentralized information, and high access costs.

II. Rising DePIN “rookies”

The competition within the DePIN sector remains intense with the ongoing introduction of new initiatives. Here are a few distinguished entrants.

1. Grass

On March 13th, Grass announced a new development direction, becoming the first Layer 2 Data Rollup. The system is built on Solana and is a research and development project by Wynd Network.

Grass aims to become the AI Oracle by providing datasets through Web Scraping – an automated process of extracting information from websites using programming tools and techniques. By leveraging Grass, individuals have the opportunity to contribute their unused internet resources, which AI laboratories can then employ to access public websites and extract AI data for training purposes.

The primary objective of Grass is to establish a decentralized and impartial alternative to conventional approaches to data provisioning, thereby promoting greater transparency in data provenance.

Currently, the Grass community is also actively engaging in network connectivity and accumulating points, expecting an upcoming airdrop.

Project links

2. Aethir

Aethir defines themselves as an enterprise-focused, distributed GPU cloud provider with the largest GPU network and highest committed revenue within the DePIN sector.

Aethir addresses the growing demand for computational resources. By consolidating and efficiently reallocating both new and underutilized enterprise-grade GPUs (from enterprises, datacenters, miners and consumers), Aethir facilitates the expansion of industries dependent on GPUs, such as Artificial Intelligence and gaming, on a substantial scale. Participants benefit from an almost limitless global compute network of enterprise grade GPUs with flexible, superior unit economics. 

Aethir recently launched its public node sale on March 20th, achieving the anticipated success with notable traction.

Project links

3. ionet

Io.net is a DePIN project built on Solana, aggregating GPU resources and providing computing power for AI and ML companies. The project aims to deliver computing power at low cost and faster processing times, as opposed to centralized services such as Google, AWS, or Azure. 

More precisely, io.net is a recently developed cloud system designed to facilitate the accessibility of ML engineers to decentralized cloud services in a convenient and economically viable manner. The project has implemented a parallel execution model to enhance performance and broaden the range of ML models.

Project links


The information provided in this article is for reference only and should not be taken as investment advice. All investment decisions should be based on thorough research and personal evaluation.

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