bottleneck

According to Forbes, although the trading volume of stablecoins has exceeded $1 trillion in the past year, most activities are still concentrated in the crypto-native space (trading, arbitrage, and inter-protocol settlement), with limited applications in everyday commercial payments. WasabiCard CEO Ray Yang pointed out that the transfer of funds is no longer the core issue; licensing, compliance, risk management, and banking capabilities are the key foundations for achieving widespread adoption.Forbes noted that while stablecoin settlement can significantly enhance cross-border payment efficiency, each market has different compliance standards, licensing requirements, and banking relationships, making the construction of localized compliance in each market both slow and expensive, which contradicts the instant global settlement that stablecoins advocate. Currently, the stablecoin market has surpassed $320 billion, and industry discussions are shifting from whether stablecoins can replace existing networks to how they can be integrated into existing networks.Forbes believes that the challenge of the last decade was to get funds flowing, while the challenge of this decade is to ensure that global payments operate in compliance and at scale within a fragmented regulatory environment.

At the "Crypto 2026: From Cryptocurrency to Smart Economy" themed forum held in Hong Kong, guests including KiteAI's Asia Pacific head Laughing, Sentient's Asia Pacific head Anita, Brevis content director Nic Tang, Mentis product head Jerry, and Predict.fun's Asia Pacific BD head Ah Huang Ricardo engaged in a roundtable discussion on the theme "AI × Crypto --- The Foundation of the Next Generation Digital Economy."Regarding whether the outbreak of open-source AI Agents (such as "raising lobsters") is a short-term sentiment or a long-term trend, Laughing believes this marks a paradigm shift of AI from "conversational" to "executive," signaling the beginning of a long-term trend. However, Agents lack a physical identity, making it difficult for merchants to trust their trading behavior, and issues of data leakage and uncontrollability remain obstacles that must be overcome for scaling. Jerry pointed out, based on his own usage experience, that current Agents face security risks such as memory fuzziness, token consumption in dead loops, and accidental file deletion. Although newly emerged Agents have improvements, they still have shortcomings. Ah Huang Ricardo stated that behind the short-term sentiment is real user demand, but truly reproducible profitable trading Agents are still very rare, and there is a long way to go.Addressing core bottlenecks such as trust, security, and verifiability, Nic Tang emphasized that the current execution process of Agents is like a black box, where users cannot verify whether their decisions are executed as promised. Zero-knowledge proof technology can mathematically prove the source of an Agent's output and compliance with behavior, while not exposing privacy. Anita added that Sentient is committed to building an open and collaborative AI agent network, promoting the deep integration of AI and blockchain in identity, data, and incentive layers, providing foundational support for the next generation digital economy.Regarding the application scenarios that are likely to scale first, the guests generally believe that the programming field is relatively mature, and Agents in prediction markets perform better than humans in specific tracks due to their rationality and lack of emotions. In the short term, they are optimistic about API Marketplace and cross-platform consumer shopping Agents, while in the medium term, they are optimistic about content creation AI (such as AI influencers). Agent-to-Agent interaction and the Agent/Skill Marketplace are seen as important future trends.

At the "Crypto 2026: From Cryptocurrency to Smart Economy" themed forum held in Hong Kong, Tencent Cloud's industry architect Alan Nie delivered a keynote speech titled "Cloud + AI Dual Engine: Tencent Cloud Empowers New Growth in Web3."Alan Nie pointed out that Web3 enterprises face three major bottlenecks in global infrastructure, R&D efficiency, and business intelligence. Tencent Cloud deeply integrates the "Cloud + AI" dual engine to provide low-latency infrastructure covering the globe. Among them, the Singapore data center is the only cloud provider in the world that offers four availability zones, and the self-developed TDSQL-C database can achieve elastic scaling in seconds, with Redis single-node performance reaching over 300,000.In terms of AI empowerment, Tencent Cloud launched CodeBuddy (AI Pair Programmer) and WorkBuddy (Personal AI Assistant), which can automatically generate code, batch process office documents, organize meeting minutes, and support multi-agent parallel execution of complex tasks. In financial scenarios, the automation research report reproduction cycle has been shortened from three days to half a day; in on-chain data analysis scenarios, storage costs have been reduced to one-tenth of the original, with query responses reaching millisecond levels.Alan Nie stated that Tencent Cloud is committed to using the "Cloud + AI" dual engine to help Web3 enterprises build the next generation of smart economic infrastructure.

According to a post by Delphi Digital, stablecoins are becoming an alternative to traditional foreign exchange trading channels. The costs of traditional foreign exchange channels are high, with comprehensive fees for remittances to Argentina or Nigeria potentially reaching up to 8%, and 81% of these costs come from maintaining the underlying banking infrastructure.However, current exit mechanisms such as access to bank accounts or interbank channels remain a significant bottleneck. Delphi Digital states that most of the "friction" exists outside of the blockchain. While the minting and burning of stablecoins can be completed in just a few seconds, significant delays occur due to the batch processing mechanisms of bank wire transfers into these systems.

The a16z Crypto article "How AI 'Judges' Expand the Scale of Prediction Markets" points out that the biggest challenge facing prediction markets is not "pricing the future," but rather determining what actually happened. Similar issues frequently arise in some small-scale events, where erroneous or opaque settlement mechanisms can undermine market trust, liquidity, and the accuracy of price signals.Industry experts suggest introducing large language models (LLMs) as arbiters in prediction markets, including on-chain rule commitments, resistance to manipulation, enhanced transparency, and increased neutrality. For example, specific LLM models, timestamps, and judgment prompts could be encrypted and recorded on the blockchain at the time of contract creation, allowing traders to understand the complete decision-making mechanism in advance. The model weights would be fixed and not easily tampered with to reduce the risk of cheating, and the settlement mechanism would be publicly auditable with no arbitrary human rulings. The AI judgment mechanism could significantly improve the efficiency and scalability of prediction market settlements while ensuring transparency and fairness.

According to CoinDesk, due to domestic regulatory restrictions, South Koreans transferred over 160 trillion won (approximately 110 billion USD) to foreign cryptocurrency exchanges last year. Analysis indicates that the delay in the implementation of South Korea's "Digital Asset Basic Law" has created a regulatory vacuum, forcing investors to turn to overseas platforms.Research has found that cryptocurrency has become a major investment asset in South Korea, with the number of investors rising to 10 million, and revenue from trading platforms like Upbit and Bithumb reaching trillions of won. However, the report shows that despite South Korean investors actively trading cryptocurrencies and increasingly turning to overseas platforms like Binance and Bybit, the growth of domestic trading platforms has stagnated.However, the regulatory vacuum has raised concerns among market participants, who worry that domestic centralized cryptocurrency trading platforms are increasingly struggling to compete with overseas platforms that offer more complex trading products.

Facing global challenges such as short-term chip shortages, long-term energy constraints, and ongoing storage space bottlenecks, BitTorrent, as the cornerstone of a decentralized internet, is paving new paths for the future of AI.It is reported that BitTorrent, through its distributed architecture, transforms a vast number of edge nodes into a pool of computing and storage resources, empowering developers to store, share, and access data without intermediaries. BTFS is not only a pillar of the decentralized data economy but also turns every device into a participant in the evolution of AI, collaborating with global resources efficiently and sustainably towards a decentralized intelligent future.

ChainCatcher news, OpenAI founder Sam Altman stated that the release of OpenAI's new version may be delayed, currently facing a computing power bottleneck, and services may sometimes slow down.Previously, Sam Altman mentioned on February 12 that he plans to launch GPT-4.5 and GPT-5 in the coming weeks or months. He also stated yesterday that a "new type of open-source weight language model" with reasoning capabilities will be released in the coming months. An open-source weight language model refers to a model that can be publicly used, downloaded, modified, or deployed. Although it is not as open as a fully open-source model, it represents a significant shift compared to the completely closed GPT-3 and GPT-4. OpenAI partially open-sourced the GPT-2 model in February 2019 and completed full open-sourcing in November of the same year.

ChainCatcher message, independent researcher Chen Jian posted on X that there are currently two main ways to address the fragmentation of Ethereum liquidity. One is chain abstraction, which involves adding another chain on top of all L2s to route transactions, and the other is to solve it in a "cluster" manner, that is, placing a hub below L2 to route transactions, or what is called a shared sequencer.For example, OP Superchain follows this idea, and puffer finance's Based Rollup has a similar approach, but it is more fundamentally native, allowing Native Staking Ethereum layer nodes to receive all Layer2 transactions in advance through AVS-protected pre-confirmation.In fact, technically solving Ethereum fragmentation is relatively easy; the main bottleneck lies in the economic game theory aspect. On one hand, the Ethereum Foundation needs to be more assertive and united, and on the other hand, a balance needs to be found in terms of mutual benefits and win-win scenarios.

ChainCatcher message, analysts at the research and brokerage firm Bernstein believe that cryptocurrency micropayments are key to avoiding bottlenecks in the AI financial economy. The analysts stated that the real bottleneck in the AI financial economy is the current financial system's inability to effectively handle micropayments. AI agents may need to make very small, frictionless payments, such as for consuming data or content. However, due to the complexity of the technology and human involvement, transaction costs in traditional systems are very high, making this approach uneconomical. To meet the demands of the AI economy, the financial system needs to continuously evolve to enable seamless, low-cost micropayments that align with the consumption patterns of AI agents. This is where cryptocurrencies come into play.