Questioner: Mia, ChainCatcher

Answerer: Arthur Meng, Co-founder and CEO of Hemera

Recently, W3W.ai announced a rebranding as Hemera, providing a public infrastructure protocol for high-performance AI and data, introducing a unique new competitor in the Web3 AI and data track - Hemera.

In fact, with the rise of Sora under OpenAI, the AI field has once again sparked a technological wave AI+Crypto=?, which has become a hot topic in the current innovative technology field. In a16z's "2024 Outlook List," "AI+Crypto" is included, emphasizing that encryption technology can create a multilateral, global, permissionless market, allowing anyone to contribute computation or new datasets to the network and receive corresponding compensation. This sharing and utilization of resources not only reduces the cost of AI but also makes data more accessible.

At the same time, Vitalik Buterin also envisioned the potential of "AI+Crypto" in his article, believing that encryption technology can find a balance between the centralization and transparency of AI, further optimizing the storage of AI data.

Hemera is steadfast in exploring the potential of Crypto + AI, empowering the crypto industry with the latest AI revolution, creating an AI-native operating system for the entire industry through a high-performance data indexing network and Web3 deeply optimized large models. According to Hemera co-founder Arthur Meng, the Hemera Protocol will be built as a public infrastructure for the entire industry, using AI capabilities to redefine the interaction between users and blockchain in the Web3.0 era.

Arthur Meng, co-founder and CEO of Hemera, holds a Ph.D. in physics from Stanford University and has co-authored papers with several Nobel Prize winners in journals such as "Nature" and "Nature Communications."

Hemera is committed to providing real-time, high-performance data infrastructure services for the global blockchain industry. Its new ecosystem has flourished and has built a series of commercial products and services for developers based on the Hemera protocol, such as the SocialScan blockchain browser, airdrops, and community quality audits, and the SocialScan Agent Store, meeting various data needs of the industry.

Hemera has completed a $2.6 million seed round of financing, with investors including Nomad Capital, LIF, SNZ, Chainlink, ZetaChain, Sending Labs, founders of Ultiverse, co-founder of Wish Danny Zhang, and Microsoft's Senior Vice President and AI expert Shen Xiangyang, among other angel investors. Currently, its official website has been completely revamped and launched, and the website domain and official X account have also been migrated and renamed.

Recently, ChainCatcher interviewed CEO Arthur Meng, unveiling the mystery of Hemera.

Founder's Academic and Entrepreneurial Journey: From AI Exploration to Web3

ChainCatcher: You previously pursued a Ph.D. in physics at Stanford. What prompted you to enter the AI field as an entrepreneur and then lead the team into the Web3 domain?

Arthur Meng: Many people in the venture capital circle do not understand "pursuing a Ph.D.," and some even, under the influence of Silicon Valley tycoon Peter Thiel, carry some interesting "prejudices" and believe that the earlier you "drop out," the better. I have the right to speak from the other side of the mountain on this matter: in fact, pursuing a top Ph.D. degree is very similar to entrepreneurship - first of all, just like entrepreneurship, pursuing a Ph.D. is not necessarily suitable for everyone; at the same time, the project direction you choose must achieve the greatest results with limited time and resources. If the direction is too broad and distant, it may be impossible to achieve under current conditions. If the direction is too small and ordinary, it may not be possible to publish work in top journals or even graduate smoothly. During my time at Stanford, I had a strong interest in AI and data, participated in many AI projects, and successfully integrated AI into physics research, achieving very good results. Some of the results were successfully published in the main issue of "Nature" magazine (impact factor 65).

After graduating from Stanford, I joined an artificial intelligence company, responsible for algorithm development, engineering, and architecture, turning the company's unique machine learning and deep learning algorithms into enterprise service software, sold to large enterprises for user behavior analysis. At that time, the main clients included Pinterest, Yelp, Alipay, American Express, Funplus, and others, helping them detect large-scale registration attacks and predict whale customers, among other tasks. This experience has greatly inspired our current work at Hemera Protocol.

ChainCatcher: W3W announced in March that it rebranded as Hemera Protocol, providing AI and data infrastructure services. What prompted the team to shift to the AI field?

Arthur Meng: In fact, since we first entered Web3, we have been exploring the potential applications and scenarios of AI in Web3. At that time, when Web3 and AI were mentioned, most people felt very resistant or unreasonable. But from day one, we believed that the massive on-chain data of Web3 has enormous potential, and the industry is still in a very early stage. Whoever can effectively solve the use of on-chain data will gain an advantage in the future large-scale application of AI in Web3.

As mentioned earlier, our entry into Web3 is very relevant to the business of the previous entrepreneurial company. So how to use community members' on-chain information and evidence to build Web3 identities to help community growth and operations is the first scenario we thought about. We quickly found that answering this question is not easy: to answer this question, a very high-quality and high-precision account-level granular data capability is needed. The transaction forms of Web3 users are diverse, and there are many asset categories. At the same time, with the maturity of Ethereum's scaling solutions, modular blockchain technology stacks have become mainstream, and the organization and use of user interaction information across multiple blockchains and contracts is very cumbersome. On the other hand, almost all the communities we cooperate with, including NFT, gaming, social, and even wallets, need this type of solution. At the same time, we quickly found that the existing data infrastructure within the industry cannot effectively support the scenarios we want to address. The majority of them are centralized B2B SaaS model data companies, which are limited by cost control issues and cannot quickly support hundreds or thousands of application chains (appchains). Another type of infrastructure, such as the Graph, caught our attention: The Graph provides decentralized data indexing capabilities, which can effectively address the granularity of data at the smart contract level, but it is powerless in the granularity of data at the "account level" that we are concerned about.

So after nearly a year of research and effort, we created the first version of the Hemera Protocol - a decentralized account-level real-time data indexing protocol. It can effectively meet the industry's developers' needs for user account-level asset information, social community information, and on-chain reputation in Web3, while supporting a range of essential services for the public chain ecosystem, such as blockchain browsers and data APIs. In this process, we quickly realized that in the context of the AI revolution sweeping the entire internet, the Hemera Protocol should also keep pace with the times and evolve into the next generation of AI-native data infrastructure: on top of the first-generation Hemera's access to data through traditional methods such as SQL and GraphQL, we proposed for the first time to incorporate the use of finely tuned large models using on-chain data, allowing ordinary users to access on-chain information in English and integrating the service form of Agent-as-a-service, enabling developers of various Web3 applications, protocols, and public chains to easily customize their own AI Agent, providing AI capabilities to the entire industry, and comprehensively upgrading the interaction experience between Web3 users and Web3.

SocialScan Explorer is a blockchain browser built on the Hemera Protocol as an infrastructure application for the public chain ecosystem, providing high-performance blockchain browsers for major Layer 1, Layer 2 public chains, and application chains. Currently, we have established partnerships with several well-known collaborators and clients, including public chain ecosystems such as Polygon, Linea, Manta Network, Taiko, Mantle Network, Celestia, Xion, Story Protocol, Merlin, and others. At the same time, we have established good strategic partnerships with leading RaaS projects in the infrastructure field, such as Caldera, Altlayer, Conduit, to jointly serve app clients under the Ethereum scaling and rollup trends.

In the community interface of SocialScan, we provide an entry to the Hemera AI Agent Store for Web3 end users, allowing both experienced Web3 users and new users entering Web3 to efficiently track and trade assets using AI Agent's real-time on-chain data. Since the closed beta launch in early March, it has attracted over 500,000 registered users and generated around 600,000 on-chain interactions.

The Birth of the Hemera Protocol

ChainCatcher: What is the significance of the name Hemera Protocol, and what services will it provide to blockchain users?

Arthur Meng: Hemera comes from the Greek mythology "Goddess of Daylight," coincidentally related to the relationship between Ether and Hemera. We also hope that the Hemera Protocol can shine on a massive amount of on-chain data like sunlight, making it easy for everyone to discover and utilize truly valuable signals.

The Hemera Protocol aims to become a public infrastructure serving the entire industry, providing real-time and efficient data services and AI capabilities for the entire Web3 domain. Similar to water and electricity in real life, the data and AI capabilities of the future Web3 world will become more valuable and efficient under the influence of Hemera. On-chain data contains enormous opportunities but also faces problems such as information fragmentation and difficulty in information filtering. Therefore, Hemera will use artificial intelligence and other technologies to filter out truly valuable signals from massive on-chain data, providing powerful decision support for developers, investors, and traders. Hemera aims to become the data middle platform of the Web3 domain, allowing the entire industry to easily access and process on-chain data through AI.

Achieving Interoperability of On-Chain Data

Regardless of the chain's data, as long as it goes through the Hemera Protocol, it can be easily accessed and shared, greatly reducing the cost of data acquisition and processing and improving the operational efficiency of the entire industry.

Mining and Analysis of On-Chain Data Using Large Language Models

The Hemera Protocol uses artificial intelligence technology to deeply mine and analyze on-chain data. By training large language models or AI algorithms, we can help users filter out information that meets their needs and provide personalized data services. This way, both developers and investors and traders can more conveniently access the data they need, improving decision-making accuracy and efficiency.

Open Applications

As a public infrastructure, Hemera is open-source and will also work closely with partners, developer communities, and others to provide strong data support for the development of the Web3 domain.

Application Scenarios of Hemera

ChainCatcher: How does Hemera use large language models to bring value to the Web3 industry? What are the specific application scenarios of Hemera?

Arthur Meng: The Hemera Protocol's technical architecture incorporates large language models, changing the way users interact with data, achieving active user demand iteration from passive, and fully leveraging the advantages of data interoperability in the Web3 industry. Through large language models, Hemera can actively capture and meet user needs, completely breaking the limitations of users passively receiving information in traditional applications. At the same time, the data interoperability of Web3 provides a broad stage for the innovation of the Hemera Protocol, allowing us to fully utilize data across the network to provide more accurate and comprehensive services to users.

Given that the Web3 industry is still in its early stages, with users mainly focusing on asset management and discovering new projects, our first practical scenario is to develop a cross-chain, fully interconnected AI agent to help users filter out projects worth paying attention to within the Ethereum ecosystem. This involves screening based on factors such as high gas fees, community quality, and investor behavior to improve user investment decision-making efficiency.

We plan to initially provide real-time on-chain data to users through web-based push notifications, Telegram, Discord, or email. Additionally, one of Hemera's innovations is to use AI and data capabilities to provide adapted agents for various infrastructure, protocols, and applications to better serve their clients. Through artificial intelligence, we will help creators and IP in the ecosystem to push to the Web3 community in a more high-quality manner. We plan to place agents from different fields in the Hemera agent store to meet diverse user needs.

Interoperability

ChainCatcher: How does Hemera build and develop its ecosystem, and what are the selection criteria for partners?

Arthur Meng: Hemera is committed to achieving unlimited interoperability, as the team deeply understands that in the Web3 era, both large enterprises and startups are more or less involved in on-chain data. The diversity of chains and the prosperity of the ecosystem are extremely beneficial to our project's development. Therefore, the team has collaborated with multiple public chains and well-known projects to expand the influence and application scope of Hemera, meeting the needs of more ecosystems and applications. Currently, Hemera has integrated with numerous public chains, including the Ethereum mainnet and its well-known L2 solutions, as well as other L1 public chains and the Cosmos ecosystem.

Our strategy is to closely collaborate with public chains, infrastructure, and application ecosystems that share a similar vision to jointly drive industry development. Only through collaboration can we achieve true win-win outcomes, and for this reason, the team has been seeking more partners to empower applications in this industry.

First Ecosystem Application: SocialScan

ChainCatcher: What are the product features and positioning of SocialScan? Why develop an application product?

Arthur Meng: SocialScan is positioned as the next-generation Web3 interaction interface. We have divided this interaction interface into two different parts for developers and end users. SocialScan Explorer is a blockchain browser for developers, powered by the Hemera Protocol data infrastructure, providing empowerment for the modular blockchain ecosystem and data capabilities for Hemera AI Agents. The end-user interface of SocialScan is positioned as the Hemera agent store, similar to the GPT store of Web2. Through this application, users can access and connect with numerous Web3 protocols, infrastructure, and applications, and interact with them through AI. SocialScan is not only a window to showcase our data capabilities but also a platform for users to directly interact with AI agents from our partners. Through this platform, users can easily find infrastructure protocols and applications from various chains and ecosystems and interact with them. Currently, over 500,000 users have registered on SocialScan, generating nearly 600,000 on-chain interaction records.

In addition to collaboration and community building, the team also places great emphasis on product iteration and optimization. We understand that the emergence of large language models has disrupted the way users interact with the server-side in the past. Therefore, the team hopes that through the SocialScan application, users can directly interact with our AI, accelerating the iteration speed of the Hemera Protocol.

Community Incentive Program

ChainCatcher: How will the project incentivize users participating in the construction of Hemera's big data algorithms?

Note: The original question was not included in the provided text.

Arthur Meng: Currently, Hemera Protocol mainly attracts several types of users: C-end community users, algorithm construction users, and computing power network participants. For C-end users, Hemera showcases AI capabilities and provides data labeling functions, attracting their participation through point rewards, which will be converted into tokens in the future.

For algorithm construction users, Hemera aims to attract AI and data experts from both Web2 and Web3 to contribute algorithms to enhance the project's value. We have drawn inspiration from similar projects but have undergone in-depth iteration and updates at the technical and business levels. In the future, we will establish a developer community to encourage data scientists and AI experts to provide algorithms to improve the Web3 user experience.

Computing power network providers will also have the opportunity to participate in Hemera's decentralized data indexing protocol and receive rewards through computing power. Additionally, we will continue to drive community development and reward community users through token airdrops and growth plans.

Team Expansion

ChainCatcher: Regarding the development roadmap, what are Hemera's future plans?

Arthur Meng: The Hemera team has been accelerating its development, especially in Q1 of this year, with a significant expansion in team size and a substantial increase in community users. In today's AI and crypto industries, both of which are in very early blue ocean markets, we plan to accelerate financing and product commercialization.

In my opinion, AI has the potential to greatly drive the future development of the Web3 industry. As a team that has been working in the AI and data fields for many years, Hemera began contemplating this issue a year ago. Vertical data in Web3, especially full-chain data, holds special significance for the development of AI. Although there are many challenges in using on-chain data for AI, we believe it is a direction worth exploring.

From a business model perspective, AI is largely a business-oriented field. However, in the Web2 environment, due to the monopoly and resource advantages of large enterprises, small companies face significant challenges in the development of AI. In contrast, Web3 provides a massive liquidity and incremental market, offering a broader space for the application and development of AI. Most of Web3 belongs to the computing power network and has not yet entered the realm of AI application infrastructure algorithms, so I think this area holds promise for the future.

Infinite interoperability is the core competitive advantage of Hemera. We look forward to all applications and infrastructure being able to have their own agents on our platform, collectively driving industry development. We strongly encourage builders and AI experts to actively join and create exclusive agents. In the future, Hemera will continue to increase investment and research and development efforts, driving the rapid development of the project and bringing more value to users and the community.

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