[Feature] How Can Web3 Accelerate the Productivity Revolution by Opening up the Space for Imagination?

Compiled By: Coinlive
Author: Gus Liu

Core idea：TL、DR
1.AIGC will be the most empowering technology for enhancing overall social productivity in the 21st century.
The essence of Web3 is to reform production relations and return the ownership of data assets to users, which is closely related to the AI revolution.

In the Web2 era, a large amount of data was controlled by internet giants, and users could only be consumers of data without owning it.

In the Web3 era, blockchain technology has made data a kind of encrypted, secure, and traceable asset, and the ownership of data has returned to the hands of users.

This change is very important for the AI revolution because data is the core driving force of AI, and AI models require a large amount of data for training and optimization.

Web3 allows users to own their data and better control it, and provide more diverse and comprehensive data for AI models, thus accelerating the development of AI.

2.The wave of AI tools is emerging, but it faces many pain points, while Web3 provides very good solutions.
AI tools refer to small, specialized AI applications, such as text analysis tools and image recognition tools.

With OpenAI opening up the API interface of ChatGPT, a large number of AI tools have emerged.

However, AI tools currently face many pain points, including technical problems, market, and even capitalization difficulties.

Web3 can provide solutions to these problems.

3.From an investment perspective, we are currently mainly focused on Web3 as a service protocol to empower and accelerate the productivity revolution with new native tools.
Currently, many applications or narratives in the market are still focused on:

1. Using AI to generate image NFTs with one click and continuously enrich the scene construction of the metaverse;

2. X to Earn models, such as providing correction and feedback to ChatGPT to train data and obtain corresponding tokens.

These applications are still in the early stage, but with the continuous development and popularization of technology, there are still many application scenarios to be explored and applied.

We believe that at the current stage, investing in Web3 service protocols will be more advantageous than investing in specific toC tool products, especially service protocols for new tools and revolutions, rather than inefficient vampire attacks on Web2 social networks.

4.Not only the AI revolution
Not only the AI revolution, but every productivity revolution or disruptive innovation in the future can be accelerated and empowered through Web3's native way (such as Musk's helplessness and reliance on Neuralink when facing the release of GPT-4, but theoretically, the derived applications of Neuralink can also be accelerated through Web3, as shown in the figure below).

In fact, the best approach is to see Web3 as a component, combined with the transformation of productivity and the real economy, to unleash powerful innovative forces.

In this process, Web3 no longer exists only around financial and speculative properties, but truly plays its essence of changing production relations and empowering innovation.

Introduction
With the continuous development of human society, various productive revolutions have emerged, promoting social progress and development.

In recent years, the rapid development of artificial intelligence (AI) technology has brought about an unprecedented revolution, which is a productivity revolution that covers almost all fields of human society.

The widespread application of AI technology has not only greatly improved production efficiency and quality, but also brought various innovative applications and business models. However, the AI revolution also faces many problems and challenges, one of the most important being how to quickly promote and implement these AI technologies, making them a part of productivity and bringing tangible benefits.

Therefore, we need to find a new carrier to promote the rapid application and innovation of AI technology, and Web3 technology is a very good choice.

Web3 technology not only provides a more secure and autonomous network environment, but also enables more open and decentralized applications, providing a wider range of scenarios and business models, and making AI technology better serve all aspects of human society.

Therefore, this article will focus on "How Web3 Accelerates Every Productivity Revolution? Taking the AI Tool Wave as an Example," to introduce the basic concepts and characteristics of Web3 and AI technology, analyze their interrelationships, explore how Web3 can accelerate the development of AI tools, and look forward to the future development prospects of Web3 and productivity revolution.

Previous Productivity Revolutions and Today
Previous productivity revolutions can be traced back to the Industrial Revolution in the 18th century, which was a major transformation in human history. Before that, the production methods of human society were mainly manual labor and agriculture, and the production efficiency was extremely low.

The Industrial Revolution greatly improved production efficiency and capacity through mechanized production, large-scale production, and factory organization.

This transformation completely changed the face of human society and laid the foundation for modern industrialized society.

After the Industrial Revolution, a series of productivity revolutions such as the Electrical Revolution and the Information Revolution emerged.

The Electrical Revolution mainly used the widespread application of electricity and the development of electrical equipment to further mechanize and automate the production process, and further improve production efficiency.

The Information Revolution mainly promoted information production, the popularity of the Internet, and mobile communication technology through the application of computer technology, making information acquisition and transmission more convenient and fast.

These productivity revolutions not only promoted the progress and development of human society, but also brought huge impetus to economic development and social change.

Each productivity revolution is a historic progress and brings new opportunities and challenges.

So, what is different about the AI revolution, and the possible future productivity revolutions?

The core is data-driven.

Artificial intelligence systems require a large amount of data for training and optimization, making data an important driving force for the development of AI.

Compared with previous productivity revolutions, the AI revolution focuses more on the collection, processing, and analysis of data, which can be strongly combined with the properties of Web3.

Web3 and AI: The Combination of Two Revolutionary Forces
Web3, also known as the distributed web, uses blockchain and decentralized technologies to distribute data and applications across multiple nodes, creating a more secure, transparent, and decentralized network. The mission of Web3 is to bring a fairer and more open internet, empowering users with more control over their data and asset value.

Gus, a researcher at the Tsinghua University Blockchain Association, believes that as a disruptive innovation, AI has liberated productivity, while Web3 has reformed production relations, returning ownership of data assets to users and transforming production relations. Therefore, the combination of the two has great potential.

From a top-level perspective, firstly, AI can help Web3 better achieve decentralization and autonomy. For example, AI can be used for the automation of contract and DAO execution and decision-making, improving the efficiency and reliability of Web3. At the same time, Web3 technology can provide AI with a more secure, transparent, and decentralized infrastructure, making AI learning and decision-making more fair and trustworthy.

Secondly, the combination of Web3 and AI can bring users more intelligent and personalized applications and services. For example, a decentralized identity management system based on Web3 can provide AI with more accurate and secure data and provide users with more convenient and secure identity authentication services. At the same time, AI can provide users with personalized recommendations and services based on their preferences and behavior patterns.

Finally, regarding the specific scenarios for the combination of Web3 and AI, the market consensus is generally focused on using AI's generative ability to empower the metaverse scene. For example, using an AI-generated small image tool (connected to midjourney or stable diffusion, etc.) to generate NFT images, text, videos, and task images with one click, which can then be placed in games and metaverse scenes for customized production. Alternatively, using AI to automatically generate questions can prevent cheating robots/witch attacks. For example, readon uses chatgpt to automatically generate small quizzes to prevent users from cheating.

These logics are essentially based on the perspective of AI tools looking for use cases in the metaverse or Web3, but undoubtedly, the use cases of AI tools themselves are limited under this mindset. Therefore, the more critical question should be another perspective, that is, how Web3 can empower the wave of AI tools, even to the point of using Web3 services to accelerate every future productivity revolution. We believe that Web3 can help accelerate every productivity revolution, including AI. By decentralizing, de-trusting, and autonomizing, innovation and development of tools can be promoted, and the problems of cold start and capitalization can be solved, thereby promoting the process of productivity revolution. This is also the focus of this article.

Market Perspective: Pain Points of AI Tools
We have seen that recently (early March 2023), with the opening of the latest ChatGPT interface by OpenAI, there has been a surge of AI tools in the market. According to Gus's incomplete statistics from the Tsinghua University Blockchain Association, in the week following the release of the latest ChatGPT interface by OpenAI, there were more than 1,200 AI tools emerging in the market, covering various workflows, including but not limited to: programming-related training models and code development; text processing tools, such as translation assistance, PDF summaries (chatpdt), and automatic excel generation (chatexcel); and many other interesting tools, such as a little red book copywriting generator, weekly and daily report generators, etc.

With OpenAI officially opening GPT-4 in mid-March 2023, further improving productivity (see attached image), we anticipate a continuous surge of entrepreneurial waves in the field of AI tools, accompanied by the emergence of multimodal and cross-domain characteristics. Multimodality refers to AI tools' ability to handle multiple types of data simultaneously, such as text, images, sound, etc., thereby achieving more comprehensive and accurate analysis and applications. Cross-domain refers to AI tools' ability to be applied in multiple fields, such as healthcare, finance, education, etc., thereby achieving a broader range of application scenarios.

There is no doubt that based on the existing LLM model, these AI tools can help us improve work efficiency, reduce costs, optimize decision-making, and even improve our quality of life.

However, the development of these tools still faces many challenges, particularly from a market perspective. The business models of these tools are often relatively simple and rely mainly on subscription or sales revenue. According to survey results on AI tool business models, the mainstream model is a $5/month subscription fee (such as ChatPDF).

The advantage of this model is that the price is relatively low and easy for users to accept, while also providing stable revenue for developers. However, this model also has some issues.

Firstly, the subscription model has become very common in the market, leading to intense competition.

Developers need to continually optimize their pricing and features to attract more users. This can also result in some tools only offering basic functions and being unable to provide more advanced services, making it difficult to stand out from the competition.

Secondly, marketing AI tools presents a challenge. Developers often rely too heavily on their personal influence on social media, lacking a proper marketing strategy, resulting in increasingly high customer acquisition costs.

In such a fiercely competitive market, relying solely on personal influence is not enough to attract more users.

Finally, AI tools lack compelling narratives and attractive brand images, making it difficult for users to identify with them and causing weak brand effects in the market, making it difficult to expand market share.

In summary, AI tools face challenges in their business models, marketing, and brand building. Due to the abundance of similar products in the market, competition is fierce.

These tools also face difficulties in GTM (go-to-market), which refers to how to promote and gain user acceptance of the product.

In addition, some tools are limited by their functionality and storytelling capabilities, making it difficult to expand into wider markets, resulting in a low TAM (Total Addressable Market) and insufficient capital value.

How Web3 Accelerates the Productivity Revolution
From a market perspective, Web3 can accelerate the GTM, cold start, and even capitalization of these small tools and products for the AIGC revolution. Developers can help small companies and individual developers quickly raise funds through decentralized exchanges and crowdfunding platforms, reducing the funding threshold and accelerating product launches.

In addition, users can enjoy most of the value of their data assets in the productivity revolution through Web3.

Web3 uses a decentralized model to achieve decentralized storage of data assets and ownership through blockchain technology.

This allows users to own their data, rather than having it controlled by large technology companies as in the Web2 era.

At the same time, users can propose their own needs or vote for their favorite small tools using DAO and snapshot voting mechanisms, quantifying their demands.

These mechanisms enable users to actively participate in the development and improvement of products, increasing user satisfaction and stickiness.

From a technical perspective, Web3's decentralized and distributed features provide better support for AI tools.

In the Web3 ecosystem, all data and applications are stored on a decentralized blockchain network, and this data is public, transparent, and tamper-proof. This data architecture makes it easier for AI tools to access, share, and manage data, while ensuring data security and privacy.

In addition, Web3's smart contract function can provide more flexible and efficient transaction, collaboration, and governance mechanisms for AI tools, making the application and management of AI tools more convenient and effective.

These features can help improve the performance and reliability of AI tools. Web3 uses distributed computing, storage, and communication technologies to provide more efficient, reliable, and secure computing and communication environments for AI tools.

For example, Web3's IPFS distributed file system can provide faster, more reliable, and decentralized data storage and sharing services for AI tools, reducing data latency and loss. Web3's P2P communication protocol can also provide faster, more reliable, and decentralized communication services for AI tools, supporting real-time interaction and collaboration between AI tools.

Similarly, this is also a rare opportunity for Web3
From the perspective of first principles, the focus of Web3's narrative is TVL, so the influx of new users brought by the explosive wave of AI tools will greatly increase the speed of achieving this North Star indicator.

Currently, Web3 has few application scenarios and often reuses existing stories from Web2, such as money laundering, financial speculation, and social networking.

However, these scenarios have been occupied by Web2, and it is difficult to obtain sufficient ROI by trying to seize these scenarios.

Therefore, we need to find new cakes and new increments. The new tools and application scenarios brought by disruptive innovations such as AIGC are the new opportunities we need to seize. These new small tools can bring new users, new traffic, and new sources of revenue to the Web3 platform.

By combining with AI tools, Web3 can create more useful application scenarios, providing users with better experiences and services.

Typical Applications of Web3 Accelerating Productivity Revolution
As mentioned earlier, we have found that most applications or narratives in the current market are still at a preliminary stage, such as using AI to generate NFT images with one click and continuously enriching the scene construction of the metaverse, and the X to Earn model, such as providing corrections and feedback to ChatGPT to train data and earn corresponding tokens.

These applications are still in their infancy, but with the continuous development and popularization of technology, there will be many more application scenarios to be explored and applied in the future.

We believe that at this stage, investing in Web3 service protocols will be more advantageous than investing in specific toC tool products, especially for new tools and new revolutions. This means focusing on service protocols rather than inefficiently attacking Web2 social networks.

We briefly introduce Tie Protocol, a product of a joint team from Tsinghua and MIT, which is a Web3 service protocol oriented towards disruptive innovative technologies such as AI. Its positioning is to explore new Web3 native application scenarios, rather than simply occupying the scenes that have already been occupied by Web2, in order to provide higher ROI and value. In a sense, Tie Protocol's positioning can be seen as the "Apple Store or WeChat Mini Program Mall" of Web3 native applications.

As a bridge, its vision is to link and accelerate every productivity revolution with Web3. Taking the AIGC revolution as an example, Tie Protocol's solution to the pain points of the large number of AI tools in the market mentioned in this article is:

Firstly, it provides developers with services for one-click deployment of NFT matrices, AI SDKs and other basic components to help them develop and deploy AI tools and products more quickly and easily, thereby accelerating their GTM and capitalization processes.

Secondly, Tie Protocol's decentralized architecture ensures the privacy and ownership of user data, allowing users to fully control their data and enjoy most of the value in their productivity revolution. Users can obtain, manage, exchange their data assets through the Tie Protocol platform, and can participate in voting, interaction, and governance through community DAO, making their participation deeper and more interesting.

In addition, Tie Protocol also provides functions such as smart contracts, on-chain governance, and decentralized markets, which provide comprehensive support and guarantees for the development, deployment, transaction, and management of AI tools and products. Through these functions, Tie Protocol can help developers and users better utilize Web3 technology to accelerate the process of the AIGC revolution and create more business and social value.