Money Frontier 2026 (https://www.moneyfrontier.info/en) will be held from July 27 to 28 at the Hong Kong Hopewell Hotel, gathering industry-leading companies, top platforms, investors, policy researchers, and frontline operators to share real observations and practical experiences from the market, products, and industry.

The summit will not discuss the macro trends of Web3 and AI but will focus more on the specific changes that have already occurred and are reshaping the industry, helping participants to see the new market structure clearly, understand how opportunities are formed, where risks lie, and establish executable judgments.

As the public market and cryptocurrency market accelerate their convergence, why are funding prices even more inconsistent? As traditional high return opportunities gradually disappear, where can investors still find opportunities with controlled risks? When the AI leaders are already difficult to participate in or overly valued, have ordinary investors really missed this round of opportunities?

Agenda Highlights Preview

Highlight 1: Latest Regulatory Policy Developments

What to Watch Next for the U.S. National Strategic Bitcoin Reserve?

The Bitcoin Policy Institute, which has long been involved in U.S. Bitcoin policy research and advocacy, will share the latest developments regarding the U.S. strategic Bitcoin reserve and related policies. This organization has been conducting Bitcoin research and public policy advocacy aimed at policymakers and continues to publish research related to strategic reserves.

What’s noteworthy is not just whether the Bitcoin bill will pass but how the strategic reserves will advance through which institutional pathway, from where the assets originate, how Congress and the executive branch will coordinate, and how these policy changes may impact institutional allocations, market liquidity, and the digital asset policies of other countries. This session will help participants penetrate the news headlines, understand the actual pace of policy advancement, key resistances, and their potential market impacts.

Members of the Hong Kong Legislative Council will also share insights on the future direction of digital assets in Hong Kong.

Highlight 2: How to Understand the New Market Structure

As DeFi and CeFi continue to develop, digital asset treasury companies (DAT), RWA, asset tokenization, and new asset issuance platforms are accelerating the connection between public markets and cryptocurrency markets.

However, this connection has not unified the market but rather amplified liquidity fragmentation. Due to differences in funding costs, access conditions, collateral rules, redemption mechanisms, trading times, and jurisdictions across platforms, the same asset may form different interest rates, prices, and liquidity on different platforms, as well as between digital assets and traditional financial markets.

The Bank for International Settlements pointed out that RWA and tokenization may exacerbate market fragmentation and raise financing costs; research from the Federal Reserve also shows that there is still cross-market pricing friction and market segmentation between digital currency markets and traditional financial markets.

Therefore, capital allocation is no longer just about choosing platforms and comparing surface returns, but about identifying the friction and boundaries between different markets, understanding the structures of different types of products, and judging whether price differences stem from market access, liquidity, credit, leverage, and subsidies, or from risks that have not yet been clearly labeled, and managing capital costs, redemptions, custody, counterparties, smart contracts, and regulatory risks accordingly.

On July 27, founders and CEOs from several leading protocols like Ethena and Spark (MakerDAO) will delve into the disassembly of their product structures, sources of returns, and platform operation mechanisms. The CEO and Chairman of Strive will also share insights on new credit products based on Bitcoin, such as STRC and SATA, discussing their product structures, return logic, and potential risks.

Senior executives from multiple traditional financial institutions and the digital asset industry will also bring frontline observations and unique judgments from different market and business perspectives.

Highlight 3: When AI Makes Everyone a Target Worth Attacking

As AI transitions from concept to reality, security issues are no longer exclusive to large institutions, trading platforms, or high-net-worth individuals.

Identity, accounts, assets, communication records, and social relationships may all become entry points for attacks. In the face of lower-cost, scalable, and highly personalized attack methods, are traditional security practices still effective?

The summit will discuss how AI changes the way attackers select targets, gather information, and implement attacks, as well as how individuals and institutions should re-evaluate identity verification, asset custody, device permissions, and internal security processes.

The core question is not just "Is AI dangerous?" but: When the cost of attacks rapidly decreases, how should we increase the costs for attackers?

Highlight 4: How to Find Opportunities and Growth Paths in the AI Wave?

Worried you’ve already missed the AI wave? Not necessarily. The best entry point for AI investments may not be before technological breakthroughs but when the technology is validated by the market, and rapid growth begins to expose industrial bottlenecks.

For most investors, opportunities may not come from guessing the next AI application in advance. Investing significant time and money to assess an unverified technology often means taking on risks in which they do not have an advantage.

A more realistic path is to wait for the technology or trend to complete market validation and enter a rapid expansion phase, then look for industrial bottlenecks exposed during the growth process. When demand rises quickly, key resources such as GPUs, memory, data centers, and electricity often cannot expand in synchronization, leading to supply-demand imbalances.

Compared to predicting who will become the next winner, these already validated by real demand, but constrained by supply capabilities, links may provide ordinary investors with clearer judgment bases and participation paths.

Which shortages are merely temporary cyclical mismatches? Which bottlenecks may persist for years? Which assets, although positioned within the AI industry chain, cannot genuinely share in industry growth? How can one identify key links with pricing power, expansion barriers, and real customer demand?

You will find the answers to these questions in the agenda on July 27.

Notable investors such as Xingkong will share their investment experiences and judgment frameworks in the primary markets of frontier technology; Xiandao will also continue to present the "Second Life Practical Handbook," sharing how to translate judgments on new trends into executable personal choices and practices.

Day Two: From GPUs to Power, Disassembling the AI Computing Infrastructure Full Industry Chain

Highlight 1: Domestic Chips Accelerate Entry into Smart Computing Centers, Opening New Industrial Windows

As large model inference and industry AI applications accelerate their rollout, the competition for domestic computing power is no longer limited to a single technological route. How can domestic general-purpose GPUs further enter smart computing centers and real business scenarios? How can China leverage its industrial chain advantages to overtake overseas GPU giants? Can ASICs optimized for specific AI tasks achieve breakthroughs in performance, energy efficiency, cost, and scalable deployment? The summit will invite representatives from Moore Threads and Dr. Yang Zuoxing, founder of Yanji Electronics, which has long been devoted to domestic AI ASIC research and has launched its own "Shen Miao" brand, to share the research progress, practical implementations, and industrialization directions of domestic smart computing chips from different technological paths, jointly observing new opportunities that the local computing power ecosystem is opening up.

Highlight 2: Domestic Open Source Large Models Lower Innovation Barriers, Agents Head Towards Real Applications

With the advent of high-performance open-source large models like ChatGLM 5.2 and Kimi K3, more and more companies can directly access capabilities close to the cutting-edge level. Models are no longer exclusive resources of a few leading companies, and the competitive focus of the AI industry has begun to shift from "who can train larger models" to "who can build truly usable products and systems based on models."

This also brings new development windows for Agents. When model capabilities become foundational capabilities that can be invoked, how can companies further connect data, tools, and business processes? Which Agents have moved beyond conceptual demonstrations into real production scenarios? Which applications have sustained demand, payment abilities, and replicability at scale? How can a closed loop be formed between model capabilities, computing cost, and business models?

The summit will invite guests from Tencent Cloud, BytePlus Hong Kong, KUAI.CLOUD, and AI startups and investment institutions to share practical cases and development directions of Agents through topics such as "Agent Wave: A Comprehensive Reshaping from Technological Evolution to a New Industrial Era" and "From Models to Agents: The Path to AI Native Application Realization, Computing Power, and Capitalization," observing the new generation of AI application ecosystems that domestic open-source models are fostering from different dimensions such as technology evolution, product implementation, computing power support, and commercialization paths.

Highlight 3: From Data Center Overseas to AI Factory, Engineering Capability Becomes Core Barrier

AI data centers do not simply add GPUs in traditional computer rooms. As the power density of single racks continues to increase, power distribution, cooling, network interconnection, device deployment, and operational systems need to be redesigned. Whether the ability to organize land, electricity, equipment, and operational capabilities into a stable, efficient, and sustainably expandable system is becoming the true engineering barrier of the computing power industry.

Data center overseas also entails more complex real-world issues: how to choose regions and power conditions suitable for AI loads? How to control construction cycles and delivery costs? What differences exist in infrastructure, supply chains, and operating environments among different markets? What upgrades do traditional data centers need to undergo to truly evolve into "AI Factories" aimed at AI training and inference?

Regarding discussions such as "Data Center Overseas" and "Beyond Traditional Data Centers: The Rise of AI Factories and Intelligent Computing Power," companies like Canaan, Xiaoke Intelligent, Skyward Digital, JDK Capital, Goodvision AI, and guests including heads of specialized working groups from the Korean Presidential Artificial Intelligence National Strategy Committee will merge frontline project experiences to dissect key pathways in the planning, construction, overseas expansion, and operation of data centers, discussing which experiences can be replicated and which technologies and construction risks are most easily overlooked. The agenda will also focus on core aspects such as power supply reliability, rack power density, cooling systems, network interconnections, and operational capabilities.

Highlight 4: From POW to AI, the Value Boundaries of Power Resources Are Being Redefined

If GPUs determine computing power performance, and data centers determine how computing power is supported, then electricity constitutes the fundamental resource constraint of the entire computing power system. As AI computing demand continues to increase, AI data centers and POW are competing for the same scarce resources—stable and cost-effective electricity, space suitable for deploying high-density equipment, and electricity contracts that can lock in long-term costs.

In this context, electricity is no longer just an operational cost of data centers; it may also become a strategic asset that needs to be independently configured, operated, and re-evaluated. Can different types of computing loads switch flexibly according to market demand? Can existing POW infrastructure further support AI computing? How can the computing power value generated per megawatt of electricity be enhanced? What new asset forms and business models may emerge around electricity, parks, and load scheduling?

The summit will address questions like "From POW to AI" and "What Problems Did POW Solve? What Is the Next Problem?" to further extend discussions from existing computing power industry experiences to the resource allocation efficiency, yield elasticity, and future opportunities of electricity resources. It remains to be seen whether existing AI computing services or Token distribution mechanisms can achieve efficient, transparent, and scalable resource organization, similar to mining pools allocating computing power. KuPool will also delve into the issues that POW has already addressed and explore the new propositions that the computing power industry needs to face in the next stage: as chips and models continue to iterate, the true boundaries of industry expansion may not only depend on the electricity resources themselves but also on the ability to organize, schedule, and transact computing power.

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For participation and cooperation inquiries, please contact the summit staff.