Foresight Ventures: Status Bus Structure — The View On Depin

Author：Yolo Shen@Foresight Ventures

Traditional computers consist of five parts: Computer, Memory, Controller, Bus, I/O. Looking at the development of the blockchain, the calculator and memory is relatively complete. If the entire distributed system is compared to a human being, then the human brain and memory system are already complete, but the perception and sensory system are still in a very primitive state. At this stage, Depin is undoubtedly the hottest buzzword, how to achieve it? The entire system needs to evolve a “trustworthy touch”, and we all know feelings and reflexes rely heavily on the spine and nervous system.

If the blockchain system is the consciousness built on the iceberg, then the Infra network of depin is the subconsciousness under the iceberg. Now the challenge is here, who is the spine and nerve of the distributed system? How do we build a spine and nerve? In this article, we will start with the small lessons from the history of IoT, to help buidler make depin world quicker.

In this article, we will start with the small lessons from the development of IoT，to help buidler clear mind and make something real happen.

TL;DR

1. Depin should not be unitized by devices, as devices do not have the capability to scale horizontally; the core of Depin is Pin, and the core of pin is the authorization code. We regard the device as a collection of sensor modules, and the pin code of each sensor module is the permit for data to go online and the authentication permit for PoPW. The device with the permission to go online, contributes the recognized device, can be called a mining machine. Therefore, the core of the entire Depin track is how to make the contribution of edge devices measurable, how to make the contribution of different devices and the same sensors have a consistent measure.

2. According to the different information transfer of traditional computers, it can be divided into three categories: Data Bus that transfers various data information; Address Bus that transfers various address information; Control Bus that transfers various control signals. The DePin bus also exists similarly: as an identity certificate for device access. (Address Bus) as a PoPW certificate for data verification. (Data Bus) as a means of device management. (Control Bus)

a. Address BUS: Dephy

b. Data BUS: Virtual Communication Layer + Sensor Network

c. Control BUS: Cellular Management Module

3. The Depin project has some RW attributes, exists in the physical world, and is related to real economic life. Therefore, more real-time management methods are needed to achieve autonomous risk control. The main implementation channels are two: one is to govern the traffic of cellular operators, once the device violates the rules, it can lose the PoPW mining right from the traffic end, which is a more Real Time management method than PoS like slash. The second is to buy out upstream resources through the miners + resource pool method. For example, a dealer has 100 units resources, when 30 are at risk, there may be a warning of revoking the license. now we can mix the 30 resources with the resources of other dealers, buy out the real resources (RWR) through the miners, and control the resources through the mixed segment method, to obtain as many resources as possible under the premise of guaranteeing the risk of upstream dealers. Liquity model can be copied to all kinds of RW resources.

Tiny lesson from IoT history

Looking back at the development of the Internet of Things(IoT) since 2015, there were two main challenges at the time: one was the single input and output of hardware devices. The second is that the product characteristics have not been enhanced after the device is connected to the network, and the device does not have Scale characteristics.

During this period, the core question was: what kind of changes will occur after the hardware device is connected to the network? the plain answer is，it make possible for hardware devices to upload and download. The next question is, why does the hardware need to upload and download? Can uploading and downloading increase product competitiveness? At that time, we saw a batch of products such as smart curtains, smart air conditioners, etc. Because the hardware has a relatively determined I/O dynamic line at the beginning of the design, the space for software development is relatively limited. Therefore, after being connected to the network, the product features only increased the feature of mobile terminal control, similar to “remote air conditioning, remote curtain pulling”, and most of the functions are remote + traditional controllers. For C-end users, this design is useless or even strange. Another core question is, does IoT devices have the ability to Scale after they are connected to the network? We mentioned earlier that hardware networking has more uploads and downloads. If the download is equivalent to the upgrade and expansion of the function, then the upload is the aggregation and integration of data. The value of the latter data lake in the early IoT era was very heavy, and there was a huge contradiction between the exponentially rising storage costs and the hard-to-explore data sales. In summary, IoT devices cannot improve product power and service dimensions in both download and upload modes.

What difference？What changes has AI brought?

Time always changes，Ai bring the new feature and possibilities，3 things happen：

1. Anthropomorphism of all things, independent upload and download demands. If the edge side cannot infer large models, then the terminal side needs to be independently networked to the cloud. This will transform the past radial structure with the mobile and the device into a structure with independent networking of devices.
2. Device sovereignty. From mere product sales to a dual-drive of user purchase + data sales. The device is responsible to the user not only as a product, but also as a sensor collection, responsible to the data merchant.
3. “Data is trustworthy, privacy is reliable” are the prerequisite conditions for ordinary devices to transform into mining machines. If the data is not trustworthy, then logically opening multiple virtual machines can hack the entire incentive system; if privacy is not reliable, then in the long run, the user’s interaction willingness will be suppressed.

With the development of AI, we see that Depin may have some different possibilities:

1. The emergence of AI has increased the necessity for AI hardware to connect to the internet autonomously, and the cost of device networking is likely to decrease rapidly in the next 3 years. Combined with the decline in storage and computing costs, the cost of deploying edge computing/sensors is also likely to decrease. Once many devices have been deployed, transforming them into mining machines to collect sensor data will reach a tipping point.
2. After solving the problem of devices independently connecting to the cloud, there will be more scenarios for interconnection between devices. How to use NFC and other low-cost hardware for interactive gameplay will also become a potential innovation point.
3. Making the collected perception data a bulk commodity is the core bottleneck of device mining. Setting the standard for abstract information products is a major challenge.

Depin investment themes and views:

Based on the past 5 years of IoT development experience and changes in AI new features, we believe there are three major investment themes:

• Hardware infrastructure centered on cellular modules.
• Abstract communication layer services with communication information commodities.
• General miners as a type of dealer service.

Theme 1: Depin infrastructure centered on modules

A module integrates baseband chips, memory, power amplifier devices, etc., onto a circuit board and provides a standard interface functional module. Various terminals can realize communication functions with the help of wireless modules. With the development of the entire computing network, the definition of modules is continually enriched, forming a cellular networking + computing power + end-side application ecosystem:

• Traditional Cellular IoT Modules: Basic connection modules, the main function is to implement cellular communication. These modules only contain chipsets that support this connection, without the need for additional functions.
• Intelligent Cellular IoT Modules: In addition to providing connection functionality like traditional modules, they also integrate additional computing hardware in the form of central processing units and graphics processing units (CPUs and GPUs).
• Artificial Intelligence Cellular IoT Modules: In addition to providing functions similar to intelligent cellular IoT modules, they also include dedicated chipsets for artificial intelligence acceleration, such as connection modules for neural, tensor, or parallel processing units (NPUs, TPUs, or PPUs).

Looking at the entire industry chain, upstream chip and downstream device manufacturers occupy most of the value chain. The module layer in the middle is characterized by high market concentration and low gross profit. Traditional service devices mainly include: PCs, mobile phones, POS machines. Due to its huge concentration, once a module middle layer with wide consensus is deployed, it naturally migrates various existing devices into mining machines. If traditional Web3 users are on a per-person basis, then the middle layer represented by modules will allow a large number of smart devices to enter Web3, and the Tx between these devices will generate a large amount of demand on the chain.

Looking back at the early competition between Nvidia and Intel, we gained a lot of historical experience: The early computer chip market was dominated by the Intel CPU X86 system. In some marginal markets such as graphics acceleration, there was competition between the accelerator card ecosystem led by Intel and Nvidia’s GPU; and in a broader market (areas with uncertain demand), Intel’s CPU and Nvidia’s GPU had cooperation. The two companies coexisted and prospered for a while. The turning point appeared in Crypto and AI, where a large number of computing tasks are characterized by small tasks being parallelized on a large scale, which is compatible with the computing characteristics of the GPU. When the wave came, Nvidia made several dimensions of preparation:

1. Cuda’s parallel computing instruction set. It helps developers better utilize GPU hardware.
2. Rapid iteration capability. The iterative speed beyond Moore’s Law has won it survival space.
3. The pattern of competition and cooperation with the CPU. It effectively leveraged and utilized Intel’s existing resources, and quickly seized market opportunities in some decision-sensitive areas.

Returning to the module market, there are several similarities with the competition pattern of GPUs and CPUs back then:

1. High industry concentration, and the leading group has quite strong pricing power for the entire industry.
2. Development depends on new scenarios. Communication modules + intelligent chips + standard protocols are very likely to lay a moat at the device end.
3. Rapid iteration has the opportunity to grasp new opportunities, traditional players have long decision cycles, emerging scenarios change quickly and have risks, the environment is suitable for the birth of new species.

In this competition, the Crypto Stack is undoubtedly the best technology stack for building protocols and ecosystems, and the migration of existing devices to cash flow mining machines will generate β-level opportunities. Among them, DePhy is an important player, by building an integrated module + Ledger + identity layer, to realize the distribution and management responsibilities for the entire Depin network.

Theme 2: Sensors+SE

What exactly is a mining machine? We believe any hardware/software that can generate specific information resources and intends to acquire token resources can be called a mining machine. In this understanding, there are several standards for mining machines:

1. Does it generate specific information resources?
2. Can it receive tokens? is that a real need？

Therefore, in the whole process, whether the device generates trustworthy specific information resources PoPW (proof of physical work) becomes very important. Therefore, we believe that every sensor capable of producing PoPW needs a trustworthy (TEE/SE) to ensure the credibility of edge data collection. In the field of sensors, many horizontally scalable networks can be generated. For example, the video resources collected by cameras of different devices will be measured uniformly in a network. Compared with independent collection by different devices, horizontally extended sensors + trustworthy modules can construct a larger PoPW resource market. The video materials collected can be better priced according to unified standards, which is more conducive to the formation of a large-scale market for information resources. This is not available in Device-Focus.

Theme 3: Virtual Communication Layer

Since some Depin devices exist in the physical world and are related to traditional commercial society, and the Crypto world is characterized by PermissionLess, how to manage all kinds of participants in real-time without KYC becomes particularly important. We believe that the whole web3 world needs a communication abstraction layer that integrates cellular networks and public IP networks. Users/devices only need to pay Crypto currency to get the corresponding network services. Specific direction tracks include:

1. Integration of traffic. Connect the traffic resources of global operators, turn traffic into a kind of information bulk commodity, and price it with tokens.
2. Integration of number segments. Connect the number segment resources of the world, make numbers a kind of identity layer, trade and price with tokens, and use Blockchain as a governance system.
3. Integration of IP resources. Connect public IP resources, integrate public IP pools into a resource, make public IP a resource pool, support arbitrary access and jump, trade and price with tokens, and use Blockchain as a governance system.

Conclusion

1. Depin should not take devices as units, devices do not have horizontal scale capability; the core of Depin is Pin, and the core of Pin is the authorization code. We regard the device as a collection of sensor modules, and the pin code of each sensor module is the permission for data to enter the network and the authentication permission for PoPW. Devices with network access rights and contributions that are recognized can be called mining machines. Therefore, the core of the whole Depin track lies in how to make the contribution of edge devices quantifiable, and how to make the contributions of different devices with the same sensors have a consistent measurement standard.
2. According to the different ways of transmitting information in traditional computers, there are three categories: Data Bus for transmitting various data information; Address Bus for transmitting various address information; Control Bus for transmitting various control signals. Similarly, DePin bus also exists: As an identity certificate for device access (Address Bus), as a PoPW certificate for data verification (Data Bus), as a means of device management (Control Bus).
3. Depin project, due to its partial RWA properties, exists in the physical world and is related to real economic life. Therefore, more real-time management methods are needed to realize autonomous risk control. There are mainly two implementation channels: one is through the governance of cellular operator traffic. Once a device violation occurs, the device can lose the right to PoPW mining from the traffic end, which is a more real-time management method compared to Slash. The other is to buy up upstream resources through miners + resource pools. For example, a dealer has 100 number segment resources. When 30 are at risk, there may be warnings of penalties and license suspensions. Today, we mix the 30 resources with the resources of other dealers. Through miners buying up real resources (RWR) and mixing number segments to control the risk of resources, we can obtain as many resources as possible while ensuring the risk of upstream dealers. Replicate the Liquity model to all kinds of RW resources.

REF

1. 《The rise of smart and AI-capable cellular IoT modules: Evolution and market outlook》，iot-analytics https://iot-analytics.com/rise-of-smart-ai-capable-cellular-iot-modules/
2. 《Depin Investment MEME 202505 Yolo》https://docs.google.com/presentation/d/1Zf-QbhuH_gYYc8adQ7ZQ8yGHWC62uDTvHVZ2GVLF8cQ/edit#slide=id.g2e09513e47b_0_137