Introduction

On May 19, an AI-themed event hosted by Tencent Cloud took place in Singapore. The event focused on topics such as AI infrastructure, enterprise AI adoption, AI agents, Web3 verifiable computation, and fintech, and featured participation from industry representatives across cloud services, public blockchain ecosystems, payment networks, fintech, and investment institutions.

As a major financial and technology hub in Asia, Singapore has increasingly become a key node for AI, Web3, and digital finance companies establishing their presence in the Southeast Asian market. Tencent Cloud’s decision to host an AI-themed event in Singapore reflects the growing focus of major cloud providers on integrating AI application deployment, computing power services, enterprise-grade solutions, and next-generation digital infrastructure.

According to event information, participating guests include Zhou Kailun, Director of Cloud Computing at Tencent; Anna Zhang, Head of Payment Growth for Asia-Pacific at the Solana Foundation; Juan Jose, CEO of Bitroot; Chionh Chye Kit, Co-founder and CEO of WIDTH; Martin Hoon, CEO of the9bit; and Kevin Liu, COO of ARK Wealth Singapore.

From the lineup of participants, this event is not merely a showcase of a single AI product, but a cross-disciplinary dialogue centered on how AI integrates with cloud services, payment networks, on-chain infrastructure, and fintech. Tencent Cloud represents Web2 cloud computing and enterprise-grade service capabilities, Solana represents a mature public chain ecosystem and on-chain payment innovations, while fintech and wealth management institutions reflect real-world commercial demands for AI. Against this backdrop, Bitroot—an emerging public chain project focused on high-performance Layer 1 and AI-native architecture—was invited to participate, positioning it as one of the noteworthy Web3 infrastructure representatives at this event.

Behind the high-profile AI event, Web3 infrastructure is being revisited.

Over the past year, the AI industry's focus has gradually shifted from competition over model capabilities to enterprise deployment, data governance, agent workflows, and automated decision-making. For cloud service providers and financial technology institutions, AI commercialization depends not only on the model itself, but also on a comprehensive set of infrastructure capabilities—including computing power, data, access controls, security, and audit mechanisms.

This also explains why Web3 infrastructure is beginning to be incorporated into AI discussions. As AI agents evolve from “conversation tools” to “action-oriented entities,” they may soon need to call APIs, initiate payments, manage assets, complete settlements, and even participate in multi-party collaboration workflows. In these scenarios, traditional centralized systems and on-chain verifiable infrastructure could complement each other.

The programmable assets, automated settlement, verifiable state, and on-chain audit capabilities provided by blockchain directly address the trust challenges faced by AI agents in financial, payment, and enterprise collaboration scenarios. Therefore, by bringing together public chain ecosystems, cloud services, payment growth, and fintech representatives in the same discussion forum, this Tencent Cloud Singapore AI event signals that the next phase of AI competition is shifting from isolated technological capabilities to competition over integrated infrastructure.

Why was Bitroot, which has not yet launched, invited?

For Bitroot, being invited to this event holds significant representation. Unlike established blockchains like Solana, which already have mature mainnets and large ecosystems, Bitroot is still in the testnet phase and actively expanding its ecosystem ahead of its mainnet launch. The fact that this emerging Web3 project, yet to launch its mainnet, has been included in the participant list for Tencent Cloud’s Singapore AI event indicates that its technical direction and narrative approach have already garnered attention from at least some industry stakeholders.

From an industry perspective, Bitroot may have been invited not because of its current ecosystem size, but because its focused infrastructure direction aligns well with the needs of the AI era.

First, AI agents and on-chain automated execution require a higher-performance underlying network. Traditional public blockchains still have limitations in terms of throughput, latency, and cost, while AI agents may generate future demands for more frequent, continuous, and fully automated interactions. This means the underlying blockchain must offer stronger concurrency handling capabilities and lower execution costs.

Second, developer compatibility remains critical for a new blockchain to build an ecosystem. By choosing EVM compatibility, Bitroot does not aim to force developers to migrate to an entirely unfamiliar environment; instead, it seeks to provide a higher-performance execution environment while retaining the Ethereum developer toolchain. For new blockchains still in their early stages, this approach helps reduce the difficulty of bootstrapping an ecosystem.

Third, AI-native architecture is emerging as a key differentiator for the next generation of infrastructure projects. Unlike projects that focus solely on TPS or transaction fees, Bitroot emphasizes AI agents, on-chain automation applications, and verifiable execution scenarios. This positioning makes it more naturally integrated into discussions at the intersection of AI and Web3, rather than just another high-performance public chain.

Therefore, from an industry perspective, it indicates that at least some cloud service providers, fintech companies, and Web3 ecosystem participants are paying attention to new infrastructure projects that have not yet launched on mainnet—particularly Layer 1 networks designed around AI-native principles, high-performance execution, and developer compatibility.

Discussion alongside the Solana blockchain enhances the observational value of emerging Layer 1 networks.

Anna Zhang, Head of Payment Growth for Asia-Pacific at the Solana Foundation, added valuable perspectives from a mature public blockchain ecosystem and on-chain payments to this event. In recent years, Solana has consistently advanced in high-performance public blockchains, payments, and consumer-grade applications, becoming a key example in the Web3 infrastructure landscape.

Bitroot participated in discussions alongside established ecosystem representatives like Solana; this coexistence itself is noteworthy. It reflects that, against the backdrop of AI and Web3 convergence, the industry is not only focused on already mature blockchains but is also paying attention to new variables that may emerge in the next-generation infrastructure.

For emerging Layer 1s like Bitroot, the fact that the mainnet has not yet launched means its technical roadmap is still malleable. If its parallel execution, EVM compatibility, and AI-native design can be validated in subsequent testnets and the mainnet, it has the potential to establish a differentiated position in AI agents, on-chain automated execution, and high-frequency use cases.

As AI gradually becomes the core industry focus, market expectations for public blockchains may shift. Previously, competition among public blockchains centered largely on DeFi, NFTs, GameFi, and asset issuance; in the future, it may increasingly revolve around agent execution, on-chain settlement, automated finance, data retrieval, and verifiable computation. Bitroot’s entry into this conversation at this pivotal moment is precisely what makes it noteworthy.

Juan Jose: The competition in AI will shift from models to data, scenarios, and trust.

During the roundtable discussion, Juan Jose, CEO of Bitroot, stated that the gap between future AI companies may no longer be determined solely by model performance or parameter scale, but rather by a combination of data, use cases, and trust mechanisms.

He believes that as open-source and closed-source models continue to iterate, model capabilities themselves are accelerating toward commoditization. The true, long-term competitive advantage for enterprises lies in whether they possess high-quality industry data, can deeply integrate into specific business processes, and can build lasting trust at both the user and institutional levels.

This assessment aligns with current trends in the AI industry. An increasing number of companies are recognizing that the value of AI lies not only in generating content or answering simple questions, but in its ability to integrate into real business processes and consistently deliver results within controlled, auditable, and measurable environments.

Juan Jose further noted that enterprise AI adoption still faces challenges in reliability, data infrastructure, and organizational change. In high-risk scenarios such as finance, payments, and auditing, AI systems must not only strive for peak performance but also meet requirements for stability, access control, and auditability.

The AI agent requires a high-performance and verifiable execution environment.

The AI Agent is another key focus of discussion at this event. Juan Jose noted that the industry is still in the "assistive Agent" phase and requires more time to achieve true enterprise-level autonomy. This is because once Agents are integrated into enterprise systems, they encounter issues such as cumulative errors in multi-step tasks, security permissions, legal liability, and explainability.

In the long term, the direction of AI agents has become relatively clear. In the future, agents will not only provide recommendations but may also invoke services, manage accounts, initiate transactions, execute strategies, and complete settlements. This means the underlying infrastructure must support higher-frequency interactions and more trustworthy execution.

At this point, Bitroot’s technical narrative strongly aligns with industry demands. According to the project team, Bitroot adopts an EVM-compatible approach and enhances on-chain execution efficiency through designs such as Optimistic Parallel EVM and Pipeline BFT consensus, aiming to provide a high-performance, low-cost on-chain execution environment for AI agents, DeFi, and Web3 applications.

For AI + Web3 scenarios, performance is not merely a technical metric—it is a prerequisite for the viability of applications. If every operation by an AI agent requires high costs and long confirmation times, many automation use cases will struggle to scale. In contrast, a blockchain environment with low latency, low cost, and high throughput could become a critical foundation for AI agents to reach real-world applications.

The testnet phase will serve as a critical validation window for Bitroot.

Bitroot has also been advancing its testnet and ecosystem infrastructure development. According to the project team, the testnet has entered phase 5.0, with related upgrades encompassing network performance, cross-chain components, ecosystem application deployment, and node optimization.

Based on testnet data, Bitroot has demonstrated its technical implementation capabilities: over 1 million testnet addresses, over 50,000 daily on-chain transactions, a peak TPS exceeding 50,000, and an average block time of less than 0.3 seconds.

For emerging public blockchains that have not yet launched their mainnet, the testnet phase holds dual significance. On one hand, it serves as a window to validate the technical roadmap, allowing developers to assess network performance, contract compatibility, toolchain maturity, and node stability. On the other hand, it is a crucial stage for cold-starting the ecosystem, enabling community members and developers to participate in network development through early interactions.

Industry Insight: Competitive Landscape of High-Performance AI-Native Blockchains

The discussions at this summit reveal that the integration of AI and Web3 is shifting from conceptual narratives to concrete infrastructure-level challenges. Within this space, different projects have adopted distinct technical pathways:

Solana is known for its high-speed execution and mature ecosystem, having established a large developer community and DeFi ecosystem. Monad focuses on optimizing parallel EVM performance. Aptos achieves optimistic parallel execution through Block-STM. In contrast, Bitroot’s differentiation lies in not only pursuing extreme performance breakthroughs in blockchain infrastructure but also natively integrating AI computing capabilities into its core architecture—from a useful proof-of-work consensus layer, to parallelized EVM execution, to a distributed training and inference network at the application layer—building a complete decentralized AI stack.

For next-generation infrastructure projects, the ability to support more complex AI applications while maintaining security and decentralization will become the core competitive challenge.

Conclusion

Signals from the Singapore AI-themed summit indicate that AI is becoming the central theme of the next phase of technological evolution, and new demands arising from AI agents, automated finance, on-chain data, and verifiable execution are placing higher requirements on underlying infrastructure.

High-performance infrastructure is not a narrative choice for a single project, but an inevitable direction in the scaling of AI and Web3. Bitroot enters this space with a full-stack architecture centered on "parallelized EVM + AI-native computing network," standing alongside established ecosystems like Solana at the Tencent Cloud Summit, demonstrating the technical depth and industry ambition of the next generation of AI blockchains.

In the future, underlying networks that can simultaneously balance performance, compatibility, security, and verifiability will have a greater chance of supporting next-generation applications and play a pivotal role in the long-term trend of AI and blockchain convergence. Bitroot’s performance is worth continued attention.

Bitroot is a Layer 1 blockchain project focused on parallel execution and an AI-native architecture. Leveraging EVM compatibility, Bitroot employs parallel execution mechanisms, consensus optimizations, and AI-integrated interface designs to create a high-performance, low-cost on-chain execution environment for AI agents, DeFi, and Web3 applications.