数字经济 · 1632

Central Cyber Security and Information Technology Commission: Accelerating legislation in emerging fields such as artificial intelligence, anti-cyber violence, digital economy, online platforms, and blockchain

Comparing news, the Central Cyber Security and Information Technology Commission issued the “Action Plan to Promote the High-Quality Development of Internet Communications Enterprises (2026-2030)”. Among them, it is mentioned to strengthen the establishment of the rule of law on the Internet. Actively carry out forward-looking research on legislation in the field of Internet communications. Accelerate legislation in emerging fields such as artificial intelligence, anti-cyber violence, digital economy, online platforms, and blockchain. Promote the revision of the “Administrative Measures on Internet Information Services” and improve legal systems such as Internet information service management, “self-media” management, and algorithm governance. Promote the enactment of the Telecommunication Law, the Cybercrime Prevention and Control Law, and cybersecurity level protection regulations, and improve the supporting provisions of the “Regulations on the Protection of Minors on the Internet” and “Regulations on the Administration of Network Data Security”. Standardize administrative inspections involving Internet communication enterprises to minimize interference with the normal production and operation activities of Internet communication enterprises. Improve supervision, management and enforcement measures adapted to the new characteristics of Internet development and governance, and strictly crack down on internet violations and regulations. This article is sponsored by GENG, Build Your Fortune on GENG (https://geng.one)

1d agoburnking

When local city investment started selling tokens, did this student agree?

Author: Cookie Original title: When local CITIC began selling tokens on July 30, the Jiaxing Yangtze River Delta (Jiaxing) Token Operation Center was officially launched. The operator standing in front of the stage is Jiaxing City Investment and Development Group, an urban construction state-owned enterprise that has repaired roads, bridges, gas, and renovated the city. During the investigation, city leaders asked what everyone wanted to ask: “Why did you do CITIC?” In the past 20 years, the default division of labor in China's urbanization was: government development, urban construction and road construction, and enterprises moving up. Now, a state-owned urban construction enterprise has begun to personally sell tokens. Some people explained that on the day the city entered the market, the token profit peaked. The road builder sold the token and first clarified a concept: CITIC does not directly produce tokens, nor does it build a Wanka cluster. Ma Yinxiao, the head of the operation center, put it bluntly: “We are carriers,” which means integrating scattered computing power and models to become a “model wholesaler.” Take the Jiaxing model as an example. Its core is the “five unifications”, which unify API entry, unify token measurement, unify fee settlement, unify policy deductions, and unify security audits. Once connected, enterprises can use more than 100 mainstream models such as DeepSeek and Qwen as needed, and provide three types of services: inclusive packages, on-demand packages, and exclusive customization. The goal is to make AI capabilities “as convenient and transparent as water and electricity, and can be used as needed”. Why is local CITIC starting to sell tokens now? China's infrastructure construction over the past 30 years has a clear path: once any new type of infrastructure is recognized as a “public service” by the country, it will follow the same path. First, private capital will explore the path, then state-owned platforms will take over the operation, and eventually become municipal utilities. Water, electricity, gas, broadband, all without exception. Pathfinders are responsible for proving the existence of demand, and state-owned assets are responsible for turning it into a public good that can be used by humans, at a manageable price, and operated for a long time. Jiaxing's operation this time, from a logical point of view, is that the computing power infrastructure has reached the “state-owned assets takeover” stage of this path. Moreover, Jiaxing has a strong reputation: as a national computing power hub city, the city has gathered four 10,000 card computing power centers, Runze, Ali, China Telecom, and China Mobile, ranking first in Zhejiang in terms of computing power; on the industrial side, the city has 6,327 regulated industrial enterprises and more than 230 AI science and innovation enterprises. Road construction aggregates scattered travel needs into a toll road network, and selling tokens aggregates scattered AI requirements into a measurable computing power network. The subject is different, and the method is the same. With an increasingly crowded table, urban investors aren't the only state-owned players who want to sell tokens. In the spring of 2026, the three major operators announced their entry into the “Token Hour” almost simultaneously. China Telecom Chairman Ke Ruiwen's original phrase was “An intelligent cloud system is a word management system.” China Mobile wants to promote “Byte+Token double high-speed growth,” and Shanghai Mobile directly launched a general service of 1 yuan 400,000 tokens, which can even pay phone bills. Operators' motivation to switch to Token is simple: in 2025, China Mobile's revenue growth rate was 0.9%, China Telecom 0.07%, and China Unicom 0.68%. The growth rate of all three companies fell to less than 1%, and the traditional traffic business peaked, and new measurement units must be found to support the growth curve. From selling Bytes to selling Tokens, the underlying logic hasn't changed. Whoever controls the next generation of “pipelines” can charge toll fees. Looking further up, cloud vendors (Alibaba Cloud, Tencent Cloud, Baidu Smart Cloud) are selling tokens, model companies (DeepSeek, Smart Spectrum, KIMI) are selling tokens, token factories (silicon-based streaming) are selling tokens, transit stations are selling tokens... Now, even CITIC has arrived. List the players on this table: model companies, cloud vendors, token factories, the three major operators, and local city investors. From upstream to downstream, from making tokens to transporting tokens to distributing tokens, the entire industry chain is focused on the act of “selling tokens.” As mentioned above, tokens are being fully electrified, so the profit margin for “selling tokens” will drop dramatically. On the one hand, the acquisition cost of AI capabilities will continue to decrease, the threshold for enterprises and individuals to use AI will disappear, and tokens will become the underlying supply for the digital economy like water and electricity. On the other hand, the profit margin of simply selling tokens will infinitely approach selling tap water, electricity,...

4d ago深潮TechFlow#token #Arithmetic power

YGG 3.0 officially launched and transformed into a cross-domain infrastructure layer

Comparatively, Yield Guild Games (YGG) announced the official launch of YGG 3.0, transforming from a Web3 game pioneer to an interdisciplinary infrastructure layer, providing a platform for organizing manpower, skills, and capital for various communities, covering collaboration in the digital economy. The core of YGG 3.0 includes the Guild Protocol open framework, which consists of three components: Guilds (social networking), Assets (capital), and activities (operation), to promote decentralized networks to become a productive economic engine. In terms of World Model Training, the Guild collects human spatial data to serve physical AI and robots, and distributes collection tasks through the @yggalerts mission platform. Additionally, YGG provides @vibecode_game with a human coordination layer for AI-assisted game development, responsible for trial play, curation, and ranking; Institutional DeFi supports independent professional associations to manage idle capital through automated, risk-controlled revenue strategies.

5d ago

US Senator Lummis: Clarity bill extension is not the time to give up, the fight is far from over

Comparatively, on August 7, the Senate announced that voting on the Clarity bill would be postponed until September. Clarity bill supporter and US Senator Lummis posted on the X platform that I have worked so long and hard on this bill, so you can imagine how frustrated I am at the moment. Someday I'll have more to say, but for now, allow me to say that we've reached this point, and now is definitely not the time to give up. I'm not going to give up on this because I deeply believe that the industry should thrive on US territory with clear rules; consumers should be protected from fraud, and have the confidence to participate in our digital economy; and law enforcement should also have the necessary tools to hold bad actors to account. The Clarity Act is the only way we can achieve these goals. The status quo is showing its flaws in every way, and I'm not going to stop there until we fix this broken system. I will continue to work with my colleagues to achieve this goal, and the fight is far from over.

14d ago

Crypto Agent commercialization is accelerating, why are stablecoins the most critical part?

Core view: For AI agents to become real economic agents, the core obstacle is that traditional payment systems cannot support their autonomous payments. Stablecoins represented by USDC, along with dedicated infrastructure launched by companies such as Coinbase, Circle, and Stripe, are building a native programmable, all-weather, small, high-frequency “currency layer” for AI agents, spawning a program-driven on-chain microeconomy. Key elements: 1. Four major barriers to traditional payments: Agents cannot pass the identity barrier (no ID card), authorization (verification code required), time (not 7 x 24 hours), and cost (high fixed processing fee), and cannot perform small-amount high-frequency transactions. 2. Native advantages of stablecoins: programmable (automatic code execution), no license (self-generated wallet), 7 x 24 hours, transparent accounts and stable value, perfect for agent payment needs. 3. Implementation practices of leading companies: Coinbase launched AgentKit and X402 protocols (more than 50 million transactions have been processed); Circle launched the CCTP cross-chain protocol and AgentStack; Stripe launched a stablecoin API and supported USDC subscription payments. 4. Typical application scenario 1 (ultra-small payment): The x402 protocol and Circle's Gateway Nanopayments achieve $0.000001 micropayments, unlocking the long-term economy of pay-per-use billing for API calls, data access, etc. 5. Typical application scenario 2 (automatic generation): AI agents can achieve “self-hematopoiesis” through yield-bearing stablecoins (such as aUSDC), cover operating costs with interest, and platforms such as Ymax can achieve 8-12% annual stablecoin returns. 6. Large-scale implementation challenges: Private key management is vulnerable to attacks (such as the Owockibot incident), gaps in compliance (agents cannot be identified), and inaccurate AI intentions may lead to irreversible financial losses. Generative AI is changing from a “chatbot” to an AI agent (AI agent) that can do things by itself. A real question then popped up: How do these silicon-based “employees” receive money and how do they pay? Traditional banking stuff — real-name authentication, manual authorization, public accounts — inherently disapproves of AI agents. One answer that is rapidly evolving is to use stablecoins (USDC, USDT, and stablecoins with interest) to create a native “currency layer” for AI. This article will break down the implementation of leading companies such as Coinbase, Circle, and Stripe in this field, while also discussing compliance and security risks. The technical infrastructure is ready, but how to drive it is still a big problem. 1. The “payment breakpoint” encountered in the commercialization of AI agents Today's AI agents are already very capable: book air tickets, write codes, adjust interfaces... but they get stuck as soon as they get to the “payment” step. Traditional payment systems are designed for humans — you have to have an ID card, enter a verification code, operate on weekdays, and have a low processing fee for each transaction. These are all barriers for agents. Specifically, traditional payment systems set up four hurdles for agents: identity barriers: opening a bank account or credit card requires an ID card, face recognition, or even bank transactions, and agents can't even pull it out. Authorization: SMS verification codes, manual confirmation, and 3D security authentication are often required during payment, and agents cannot click buttons even if they cannot receive SMS. Time limit: Banks only process transfers on weekdays and business hours, while agents work 7×24 hours. Cost barrier: Each transaction has a fixed processing fee, such as starting at 30 cents for credit cards, so the pay-per-use model of $0.001 doesn't work at all. However, the financial behavior of agents requires exactly this kind of small, high-frequency charge (such as per number of API calls, per usage). The more fundamental problem is that the entire payment system has never considered direct “program to program” transfers. Even between two technology companies, the process is often: the agent generates an order → sends an email → person approves → person logs in to online banking to transfer money → each other's financial reconciliation. The agent can only do the first two steps and the final record. The most important step, “money from A to B”, must be done by hand. Current experiments: they are all modelling...

18d ago22#AI #stablecoins #wallets

Vietnam's Ministry of Public Security proposes legislation to implement electronic identification of digital assets

Comparative news, according to Vietnamese media An Ninh Tien Te, Vietnam's Ministry of Public Security proposed expanding the scope of electronic identification targets in the draft “Electronic Identification and Authentication Law” to include data, applications, digital assets, and various other assets. The draft stipulates that electronic identification targets not only include institutions, organizations, and individuals, but also extend to physical entities such as products, commodities, and equipment, as well as digital resources and digital assets such as databases, files, images, and videos. Digital asset recognition is carried out in accordance with the provisions of the Digital Technology Industry Law. The draft also provides mechanisms for the suspension, reinstatement and cancellation of electronic identifiers and identification codes. The Ministry of Public Security said that currently electronic identification mainly serves the digitization of citizens and the government, but in the context of the rapid development of the digital economy and digital society, it is necessary to establish a unified identification mechanism to cover all types of entities in physical and digital environments.

24d ago

Web3 AI infrastructure AIW3 completed a pre-TGE round of financing of approximately US$5 million, led by Hongzhuo Capital

Comparatively, AI W3, a Web3 AI infrastructure project, announced the completion of a pre-TGE round of financing of approximately $5 million. This round of financing was led by Hongzhuo Capital, followed by Kirin Capital and Crestwave Capital (Crestwave Capital), and 0G Labs made strategic investments. According to reports, the lead investor in this round is a private equity fund focused on investing in growing enterprises, focusing on technological innovation and the development of emerging industries for a long time. This investment in AI W3 is the first time that Hongzhuo Capital has deployed in the Web3 field. It said it is optimistic about the long-term development potential of blockchain and encryption technology in the future digital economy, and recognizes the next-generation infrastructure innovation opportunities brought by the integration of AI Agent and Web3. 0G Labs' strategic investment further reflects the ecological value of AI W3 in the field of decentralized AI infrastructure. 0G Labs is committed to promoting the integrated development of AI and blockchain technology. This strategic investment further strengthens the ecological collaboration between the two parties in the direction of AI Agent, decentralized computing, and open intelligent economy on the chain. Recently, AI W3 also launched community incentive activities around ecological construction to attract user participation through airdrop missions and ecological interaction, and promote early community growth and ecological expansion.

25d ago#financing

Changxin went public or Fuying trillion yuan. This small town, which was ridiculed back then, gambled to win Chinese chips

Source | A Little Bit of Finance Author | Curated by Zou Jun | Tristan can make a city earn 1 trillion dollars once a company goes public? Recently, Changxin Storage Station's Science and Technology Innovation Board subscription threshold is expected to create the largest A-share IPO this year. The only domestic company that can mass-produce mainstream DRAM memory chips is already a popular fried chicken in the AI community. After the news came out, many people calculated another account: How much can Hefei actually make? According to the Tianyancha App, Changxin is headquartered in Hefei, and entities related to Hefei's state-owned assets hold a total of about 36.79% of Changxin's shares. Some agencies predict that Changxin's market value may reach 3 trillion yuan after listing. Based on this calculation, Hefei's book revenue may exceed 1 trillion yuan. What is the concept of 1 trillion? That's about the GDP of Hefei for a whole year. Everyone is amazed at Hefei's huge profits, but they forget that ten years ago, every time the central provincial capital took action, it was viewed by the entire industry as a big gamble they could not control. Hefei invests in star companies such as BOE and NIO. Which one was not initially described as crazy and later punched in the face of the questioner? This provincial capital, which was ridiculed as the “largest county town in China” back then, relied on heavy betting time and time again to become the “best venture capitalist” in the city club. Changxin's listing is just the latest footnote. What makes people curious is why is Hefei able to step on the right spot every time, and where does it bet on the next bet? Hefei's “Three Big Gambles” Hefei's counterattack began in 2008. The global financial crisis that year saw layoffs and contractions everywhere, yet Hefei did something that no one could understand — it wanted to be introduced to BOE. Today's young people probably don't know. Back then, LCD panels in China were stuck to death. Most televisions, computers, and mobile phones need to be imported as long as they have a block screen. Samsung and LG in South Korea, Sharp in Japan, and Youda in Taiwan basically have the final say. In 2008, the global economy was cold, and money bags were tightened everywhere. BOE's performance at the time was poor, and its stock price fell to suck. No one dared to touch the asset-heavy panel line. Wang Dongsheng, the founder of BOE, was looking for money to build a sixth-generation line, but almost no place was willing to pick it up. The reason is simple. A six-generation line requires investment of more than 10 billion dollars. The risk is high and the return is slow. No one wants to go through this muddy water. Hefei said, “I'll come.” The total fiscal revenue of Hefei in that year was only about 30 billion dollars. At the time, Hefei's attitude was very clear; they were breaking the pot to sell iron, and they also wanted to bring in this sixth-generation line. In the end, Hefei promised to pay 60 to 9 billion dollars, which is equivalent to spending less than half a year. Seen at the time, this decision was almost crazy. In an inland provincial capital, they are busy eating their own meals. What kind of high-risk LCD panels are they going to buy? There is a lot of ridicule on the internet, saying that Hefei punches people with swollen faces and makes them fat. But in the end, they got punched in the face. After BOE's Hefei 6th generation line was put into operation, it directly broke the overseas panel monopoly. Within a few years, China became the world's largest producer of LCD panels, and BOE also became the world's largest, and its market capitalization soared. What Hefei received was far more than just that equity return. Because after BOE landed, upstream and downstream slowly became attracted. Corning for glass substrates, Sanli Spectrum for polarizers, Lianyong for driving chips... they built factories one by one in Hefei. The display industry alone has consumed hundreds of billions of dollars in output value in Hefei. It's not about investing in a project; it's about “throwing a seed into a forest.” Because only by turning the project into an industrial cluster can upstream and downstream complete support without leaving the province, reduce costs, and preserve technology. Individual projects may lose, but once the industrial chain grows, it takes root. For a city, if it has its own industrial cluster, taxes, employment, and talent have all settled down, and only then can the economic base stand. After winning the first big gamble, Hefei also found a way: seize the key links in the industrial chain, turn it into a climate, and the upstream and downstream will naturally gather. In 2016, it took another gamble, betting on DRAM memory chips. DRAM is the memory in mobile phones and computers. Your phone card doesn't stick, and it depends on how many apps you can open at the same time. In 2016, China's presence in this field was almost nil. Samsung, Hynix, and Micron monopolize over 90% of the global market. China spends more money on importing chips a year than buying oil, and DRAM is the bulk of it. The DRAM industry burns money fast and returns are slow, and how many major international companies are still at a standstill after burning tens of billions of dollars. In 2016, Hefei and Zhu Yiming, founder of Zhaoyi Innovation, co-founded Hefei Changxin, with a total investment of over 150 billion dollars. Back then, Hefei's fiscal revenue for the whole year was only around 100 billion dollars. This amount of money was equivalent to spending more than a year on the family budget. Questions are once again flooding in: a city in inland China, why? In response to this, Hefei chose to continue to work hard. 201...

31d agoWendy#AI #semiconductors #chips #Changxin Storage

WSJ: The US is pushing for the establishment of global trade rules in the AI era, competing for data flow and source code protection

Comparatively, according to WSJ reports, in addition to the tariff policy, the US Trump administration is promoting a longer-term strategic layout to establish a next-generation global trade rules system around cross-border data flows, cloud computing, software, and artificial intelligence by signing agreements with major trading partners. According to the report, 43 jurisdictions around the world have implemented 146 digital trade barriers, including digital services taxes, data localization requirements, restrictions on cross-border data flows, and measures requiring enterprises to hand over source code, technology, and commercial data. The US believes that these rules are weakening the competitiveness of domestic technology companies and the digital economy. Agreements recently reached between the US and Indonesia, Cambodia, Malaysia and other countries include provisions prohibiting forced technology transfer, guaranteeing the free flow of data across borders, prohibiting the government from requiring enterprises to submit source code, and maintain electronic transmission exemption from tariffs, and are regarded as the initial framework for digital trade rules in the AI era. Analysts believe that in the future, competition for international rules around data governance, AI regulation, and digital trade standards will become an important direction in the global economic game.

31d ago

Tom Lee: AI downstream asset performance continues to increase, Ethereum outperforms DRAM by 72 percentage points in the past month

Comparing news, Tom Lee, chairman of Bitmine and co-founder of Fundstrat, said that the relative performance of “AI downstream” (AI downstream) related assets continues to increase. Among them, Ethereum (ETH) has recently shown significant excess earnings compared to the DRAM (dynamic random access memory) sector. According to data disclosed by Tom Lee, ETH's performance advantage over DRAM expanded to 7,200 basis points (72 percentage points) in the past month. Over the same period, the price of ETH increased by about 24%, while DRAM related ETFs fell by about 38%. Tom Lee believes that as AI infrastructure investment gradually spreads from the chip and computing power supply chain to the application layer and digital infrastructure, some “AI downstream” assets are being repriced in the market. As a market person who has long been optimistic about the Ethereum ecosystem, Tom Lee has emphasized many times before that with the development of stablecoins, tokenized assets, and on-chain financial applications, Ethereum may become an important part of the digital economy infrastructure in the AI era. This data comparison shows that the performance differentiation between crypto assets and traditional AI hardware supply chains is widening. This article is sponsored by GENG, Build Your Fortune on GENG (https://geng.one)

32d agoburnking