DEPIN: Decentralized Physical Infrastructure

Grayscale released a research report on Depin at the beginning of the year. The report shows the most valuable DEPIN projects on the market and their market value.

Author: jiawei @iosg

Grayscale released a research report on Depin at the beginning of the year. The report shows the most valuable DEPIN projects on the market and their market value. Since 2022, Depin and AI have been considered two new directions for crypto investment. However, there seems to be a lack of iconic projects in the Depin field. (Helium is considered a top project, but its concept is even predated by Depin; while the bittensor, rendering, and akash in the table are more like AI track projects.)

Depin seems to lack a strong enough leading project to drive its growth. Over the next 1 to 3 years, there may still be potential investment opportunities in the Depin track.

This article attempts to summarize Depin's investment logic from scratch, including why Depin deserves our attention, and proposes a simple analysis framework. Since Depin is a comprehensive concept covering many different suborbitals, this article will explain this concept from a more abstract perspective, while also providing some concrete examples.

Why focus on Depin investment?

Depin is not a buzzword

First, it should be clear that decentralizing the infrastructure of the physical world is not a strange idea, nor is it a simple "narrative game", but it can be achieved. In Depin, in some cases, decentralization can indeed "enable" or "optimize" something.

Here are two simple examples:

In the telecommunications field, taking the United States as an example, traditional communications operators such as AT&T and T-Mobile often need to invest billions of dollars in spectrum license auctions and base station deployments, and then pay for deployment costs of $200,000 to $500,000 per acoustic base station, covering 1 to 3 kilometers per acoustic base station. In 2022, when the Federal Communications Commission (FCC) auctioned 5G spectrum in the 3.45GHz band, AT&T invested $9 billion, becoming the highest-invested operator. This centralized infrastructure model leads to high prices for communication services.

Helium phones share this early cost to each user through community crowdsourcing. Individuals can access the network and become a "micro operator" by simply buying hotspot equipment for $249 or $499. Through token incentives, communities can spontaneously build networks, thereby reducing overall investment. The cost of deploying an acous base station for Verizon is about $200,000, while helium can achieve similar coverage by deploying about 100 hotspot devices (total cost of about $50,000), reducing the cost by about 75%.

In addition, in the field of AI data, traditional AI companies need to pay up to $300 million in API fees to platforms such as Reddit and Twitter every year to obtain training data and crawl data through Bright Data (residential agent) and Oxylabs (data center agent). Not only that, they also face increasing copyright and technical restrictions, and the compliance and diversity of data sources are difficult to guarantee.

Grass solves this problem through distributed network crawling, allowing users to share idle bandwidth through downloading browser extensions, thereby helping to crawl public web page data and obtain token rewards. This model greatly reduces the data acquisition costs of AI companies, while achieving data diversity and geographical distribution. According to Grass statistics, 109,755,404 IP addresses from 190 countries currently participate in the network, contributing an average of 1,000 TB of Internet data per day.

In short, the basic starting point for investing in Depin is that decentralized physical infrastructure has the opportunity to do better than traditional physical infrastructure, and can even do things that traditional methods cannot do.

As the intersection of mid-range and consumers

As two main lines of crypto investment, both mid-range and consumers are facing some problems.

Mid-range projects usually have two characteristics: First, they are very technical. For example, technologies such as ZK, FHE and MPC have a high barrier to entry, and there is a certain disconnection in market perception. Secondly, except for the familiar projects that can directly cover end users, such as Layer1/2, cross-chain bridges, commitments, etc., most mid-range projects are actually for enterprises. For example, developer tools, data availability layers, shells, coprocessors, etc. are relatively far from users.

These two aspects make it difficult for mid-range projects to promote the transformation and dissemination of user thinking. Although high-quality mid-range projects have a certain PMF and revenue and can be self-sufficient throughout the cycle, the lack of mind share in the markets that are focused makes it difficult for them to stand out on the subsequent list.

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