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Dalio's latest warning: the US debt crisis may explode within three years. The antidote is...

Dalio's latest warning: the US debt crisis may explode within three years. The antidote is...

Author: Ray Dalio, founder of Qiaoshui Foundation Original title: How Countries Go Broke: The Dynamic Behind What is Incurable Now Compiled and organized by: bitPushNews In “How Countries Go Bankrupt: The Big Cycle,” I detailed an analytical framework to describe dynamic processes that are highly likely to occur due to unsustainable imbalances between debt supply and demand. Recently, three things happened at the same time: 1) The Japanese government sold part of its US Treasury holdings to return capital to Japan to support the yen and the Japanese capital market, and reduce exposure to US Treasury bonds while avoiding being forced to raise interest rates beyond its wishes in order to support the yen; 2) US bond yields hit new highs under long-term leadership, while the dollar weakened. The reasons include not only the current and anticipated supply of huge debt, but also weak demand for US bonds; 3) Treasury Secretary Bessent announced this week that the US Treasury would buy US Treasury bonds and be able to buy other US Treasury bonds The amount of capital used is limited, and many people ask me : Do these events fit the classic template I set out in my book? The answer is yes. To anticipate what might happen next, let's first review this operating mechanism. The operating mechanism explains in detail that the central government's debt dynamics are the same principles as the debt dynamics of individuals or companies. The only difference is that the central government has a central bank that can print money (this will depreciate the currency), and it can obtain funds from the public through taxation. Because of this, if you imagine how the debt dynamic would work if you or the business you run could print money, or get capital from people through taxation — then you can understand this process. But remember, your goal is for the entire system to work well, not only for yourself, but for all citizens. In my opinion, the credit/market system is like the human body's circulatory system, delivering nutrients to every corner that makes up the market and economy. If credit is used effectively, it can generate productivity and income to repay debt and interest on debt, which is a healthy state of affairs. However, if credit is not properly used to generate sufficient income to repay debts and interest, debt payments will continue to pile up like plaques in blood vessels, squeezing other expenses. When debt payments become very large, debt repayment problems arise, and eventually evolve into debt rollover problems — because debt holders are unwilling to continue to roll over and instead want to sell. Naturally, this will lead to a shortage of demand and sell-off of debt instruments such as bonds; when demand is scarce relative to supply, it either causes a) interest rates to rise, thereby suppressing the market and economic downturn, or b) the central bank “prints money” and buys debt, which will reduce the value of the currency, thereby driving up inflation (compared to the original level). Banknote printing also artificially lowers interest rates and harms lenders' returns. Both options are bad. When debt sell-offs are too large and difficult to contain, and the central bank has already purchased large amounts of debt, rising interest rates can cause the central bank to lose money and damage its cash flow. If this continues, the central bank will fall into a situation where net assets are negative. When this situation became serious, the central government and central bank needed to borrow money to repay the principal and interest of the debt, while the central bank printed money to provide loans due to insufficient free market demand, so a self-reinforcing spiral between debt/banknote printing/inflation formed. In summary, the classic indicators to pay attention to are the following: the ratio of government debt payments to government revenue (which is like the amount of plaque in the circulatory system), the ratio of government debt sold to the demand for government debt (this is like a plaque falling off and causing a heart attack), and the amount of government debt purchased by the central bank to cover the gap between the demand for government debt and the supply of government debt to be sold (this is like the central bank applying a larger dose of liquidity/credit to mitigate liquidity shortages, and the central bank has a risk appetite for these debts). These indicators usually rise over a long cycle of decades — debt and debt payments continue to grow in relation to income — until this state of affairs cannot continue because: 1) debt repayment expenses unacceptably crowd out other expenses, 2) the supply of debt that must be purchased is too large, causing interest rates to rise sharply, leading to a sharp decline in the market and economy, or 3) central banks are unwilling to let interest rates rise and suffer bad market/economic consequences, so they print large amounts of money and buy large amounts of government debt to cover the demand gap, thereby making the value of the currency significant Decreased. Either way, the return on bonds will be poor until the money and debt eventually become cheap enough to attract demand, or the government can cheaply buy back or repay...

22h agoBitpushNews#indebtedness #Bitcoin #economic crisis #US debt #DALIO #gold
US Stock Value Investing Is Heading Into Another Trap

US Stock Value Investing Is Heading Into Another Trap

Source: Shenchao TechFlow Original title: (Opinion: Value investing in US stocks is not equal to fundamental investment) When “fundamentals are dead” becomes a consensus, investors who blindly organize giants will eventually experience astonishing capital destruction. Guide: When the market shouted “fundamentals are dead” and the capital frenzy formed a group of tech giants, the author used an astronomy discovery to unravel the logical loopholes behind this narrative. Starting from the composition of valuation multiples, this article reminds investors to distinguish between the true quality of an enterprise and the premium that the market is willing to pay. It is particularly cautionary about long-term allocation in the crypto and technology sector. I promise this introduction won't be as long as the last one on the weather. But please give me 90 seconds. More than 100 years ago, a woman named Henrietta Levitt was doing the tedious job of measuring the brightness of thousands of stars on photographic negatives (the way they were imaged before film appeared). She noticed one characteristic of a class of pulsating stars: the slower they pulsate, the brighter they themselves are. ¹ This might just seem a little interesting today, like “OK, that's pretty cool.” But at the time, astronomers couldn't tell the difference between a dark star very close to Earth and a very bright star far away. For them, the two left the same stain on the photographic film. Visual brightness is a messy mix of these two variables: how bright the thing itself is, and how far away it is from us. Henrietta's work decouples these two things: if you can observe the rate of pulsation, you can know its true luminosity; if you know its true luminosity, you can reverse the distance based on how dark it looks. Astronomers call it “standard candlelight.” A few years later, a man named Edwin Hubble discovered one of these pulsating stars, applied Levitt's math, and discovered what he had always thought was a cloud of gas within our galaxy; in fact, it was an entire independent galaxy, one million light years away. So in simple terms, the observable universe has grown about a trillion times larger, just because one person has figured out how to tell the difference between what things look like and what they actually look like. That in itself is obviously pretty cool. But another interesting thing is that around the same time period, two other astronomers each independently drew a scatterplot. One axis was actual luminosity, and the other axis was temperature. They discovered that stars are not randomly distributed in this space, but rather clustered into different families. The meaning behind this is: stars with the exact same visual brightness may and do belong to a completely different family, have a completely different past, and most importantly, have a completely different future... So what is written in the star? Over the past few years, there has been much discussion about markets, narratives, capital, company building, and financial nihilism. This feeling seems to have reached a feverish climax as the tech and financial world begins to face a very different future than a few decades ago. What is particularly clear is that separating progress from asset prices has become more noisy and in many ways more repulsive. But as an investor who makes a living by buying assets that (hopefully) outperform, a simple framework is: forward returns are roughly equal to growth in fundamentals multiplied by changes in valuation multiples (and multiplied by the dividends you've collected along the way). In this case, the valuation multiplier can very cleanly correspond to the smudges on the photographic film. It's an observable data point, but it entangles two things that the market can't directly see: how good the company actually is, and how far (or how long) its future cash flow is now. I think most of the money that can be made comes from investors who are most capable of unraveling these two variables earlier than others (or “perception of differences”), and we will continue to see astonishing capital ruin for investors who treat their stains as stars. Value investing is not equal to fundamental investing. I think there is a misunderstood view: fundamental investing has historically dominated the creation of excess returns. Most of these legends come from the Graham, Buffett, and Tiger Foundation lineage, as well as numerous narratives built around this group of people. It is believed that by some point in the 2000s, this approach was no longer effective, and anyone who invested in this way was overwhelmed by momentum, trends, and “direct buying tech giants.” The conclusion was (and still is?) It's “fundamentals are dead.” ² The modern version of “fundamentals don't matter” itself isn't stupid. It's rooted in a lot of ideas that many of us on the Compound team have written before. The biggest companies get the most mechanical purchases, and the software industry has a winner-take-all economic law. AI means that giants can transform scale into moats faster than challengers, and there are also reasons why the market's microstructure embeds momentum more deeply into our market infrastructure. These are all real...

1d ago深潮TechFlow#US stocks
Trump named Hyperliquid, and it wasn't a surprise

Trump named Hyperliquid, and it wasn't a surprise

On August 19, when Trump met with crypto and financial industry executives at the White House, he suddenly read out the name Hyperliquid. His original statement was that CFTC Chairman Michael Selig is working to bring Hyperliquid to the US in a “fully compliant and legal” manner. After Trump's speech, HYPE rushed from around $60 to above $70, rising 20% to 22% in the short term, once again approaching a record high of around $76.8 in June this year. HYPE had a minimum of about $3.2 when it first entered the market in November 2024, and it has increased tenfold in less than two years. However, the entire crypto market also surged on the same day. Bitcoin is at $7.2 million, and Ethereum is rising at the same time as other altcoins. Macro liquidity and US regulatory news are driving up risk appetite. Why is it called Hyperliquid? Other factors aside, it has evolved to the point where US regulators and traditional exchanges cannot ignore it. Hyperliquid's main business is perpetual contracts. According to The Block data, in March 2025, its monthly perpetual trading volume was about 3.5% of all centralized exchanges (CEX); by March 2026, this ratio was close to 6%, and the monthly turnover was close to 200 billion US dollars. It rose to 6.63% in May, reaching 14.4% compared to Binance's perpetual trading volume, both of which were new highs at the time. It is no exaggeration to say that it is eating away at CEX's business step by step. Not all of Hyperliquid's assets have been growing the fastest recently. HIP-3 allows third parties to deploy a sustainable market. Since this year, contracts for stocks, indices, commodities, etc. have been rapidly sold. In May, HIP-3 sold more than 62 billion US dollars in a single month; by July, it had contributed nearly half of Hyperliquid's average daily sustainable transactions. It also explains why Wall Street is staring at it. How did the low-key team get on with Trump? Hyperliquid's past style is very different from typical crypto projects. Jeff Yan said in a lengthy interview in 2025 that the core team at the time was only 11 people, about half of whom were engineers; the team did not have a dedicated BD department, nor a business team that connects agencies around the clock. Even HYPE was not a centralized exchange, they didn't invest much resources to promote it. The Hyper Foundation's official website still says “No investors. “No paid market makers” is clearly written. Judging from public sources, there is no public evidence of any personal relationship or commercial ties between Jeff Yan and Trump himself. All I can find is news related to my own business. In May 2025, Hyperliquid Labs officially submitted submissions to the CFTC to discuss how the US handles 24/7 derivatives and perpetual contracts. At the same time, the document also clearly stated that the front-end developed by Hyperliquid Labs was prohibited for US users to trade. In February 2026, Hyper Foundation supported the establishment of the Hyperliquid Policy Center with 1 million HYPE cards. According to the current currency value of about 29 million US dollars, this agency was doing policy research and regulatory communication in Washington. The person in charge, Jake Chervinsky, had previously been the chief policy officer of the Blockchain Association and is also a familiar lawyer in the US crypto regulatory community. The introduction to HPC is straightforward: introducing Hyperliquid to lawmakers and regulators, and promoting regulatory frameworks in DeFi, perpetual contracts, and more. As of July 15 of this year, “Hyperliquid Strategic Inc. and Hyperliquid Labs” appeared in the CFTC official minutes. In other words, Hyperliquid was already in formal contact with the CFTC prior to Trump's public nomination. So, what we can guess is that Hyperliquid wasn't good at, or even very bad at traditional business relationships; it started this past year...

1d agoBitpushNews#CFTC #HYPERLIQUID #SEC #original #Perpetual contracts #Trump #custodial #viewpoints

Binance Blockchain Week will be held in November in Bangkok, Thailand, to focus on the integration of traditional finance and the crypto industry

In comparison, Binance announced that Binance Blockchain Week will be held from November 28 to 29 at the Queen Sirikit National Convention Center (QSNCC) in Bangkok, Thailand. This is also the return of Binance Blockchain Week to Asia after Singapore, Istanbul, Paris, and Dubai. With the theme of Evolution (EVOLVE), the event is expected to bring together thousands of developers, institutional investors, fintech leaders and policy makers to focus on industry trends such as Bitcoin institutionalization, stablecoin payments, DeFi institutionalization, RWA tokenization, tokenized stocks, cross-border payments, AI and crypto industry integration, and regulatory frameworks. Binance Co-CEO Richard Teng said that Asia will become a key market for the next stage of development and large-scale application of traditional finance and crypto industries. Co-CEO and co-founder He Yi said that the next round of large-scale adoption of crypto assets will be driven by accessibility, education, and products that can create real value, and Binance will continue to explore how to make crypto assets more accessible, more trustworthy, and integrated into everyday financial life.

3d ago

What 1: About three-quarters of Binance's US stock users are net buyers, and Gen Z is more willing to invest in the long term

Comparing the news, Ho Yi posted an article saying that according to data from the Binance research team, about three-quarters of Binance's users who invest in US stocks are net buyers, and about one-fifth of users have never sold their positions. He said that Gen Z users performed particularly well. Their net buyer ratio was the highest in the observation group, and the transaction frequency was the lowest, showing strong long-term investment tendencies. He believes that as the entry threshold for investment is lowered, a new generation of investors is participating in the market with more patience, discipline, and long-term thinking.

3d ago
Why is capital chasing AI Native and ignoring the old Internet

Why is capital chasing AI Native and ignoring the old Internet

Capital doesn't reward being old-fashioned, not because old-fashioned people are at fault. The old part is clearly priced. There is no bad information, so there is no excess profit. Global venture capital was $510 billion in the first half of 2026, surpassing $44 billion for the full year of 2025 in one and a half months. More than 70% have entered AI; OpenAI and Anthropic took 217 billion dollars, accounting for 43%. With that much money, you'd think everyone could share a little bit. The truth is that distribution is more extreme than total volume, and the first sieve doesn't screen the industry, it screens people. The category that has been screened out now has an unkind name: the internet is old. Let's just say one thing: the “old man” in this article has nothing to do with age. It refers to a set of methodologies that have been formed in the mobile internet cycle, have been tested over and over, and have brought huge returns to holders. The person holding it may be 45 years old or 32 years old. It was this methodology that was being repriced, not the year of birth. Confusing these two things is Lao Deng's most common mistake and one of the most comfortable mistakes — because if the problem is someone else's age discrimination, you don't need to change a single word. 01 What is AI Native The term has been misused. They can use ChatGPT not called AI native, nor AI in the company name, let alone in their twenties. There are three things that really separate people. First, the starting point is a model, not a requirement. The order in which Lao Deng makes a product is: look at what the user wants, write down the requirements, and find technology to implement it. The order of AI natives is reversed: first figure out what level the model is capable of today and what step it is likely to reach tomorrow, and then move from this capability boundary to the external product. The former uses the model as a tool, and the latter uses the model as the foundation. There was no difference between these two kinds of things made by humans in the first edition; by the third edition, there was a difference of one species. Article 2. The default unit of an organization is not a person. The division of labor in the Internet age is the division of one thing into ten people. AI Native's division of labor is to take ten things from one person and add a bunch of agents. The CEO of a domestic application company said that the team consists of less than ten people, but a large number of AI work at night, and the first thing employees do every morning is check the work the AI handed in the night before. Cursor's side is even more extreme. Public reports mention that the company doesn't have a product manager; engineers write their own code, talk to users themselves, and participate in recruiting people themselves. Article 3. Information is first-hand. AI Native's input sources are papers, model cards, GitHub issues, original discussions on X, and self-run evals. Lao Deng's input sources are industry summits, closed-door meetings, brokerage reports, interpretation of public accounts, and finding someone to drink coffee with. This one is the least obscure and most lethal; I'll talk about that separately later. I'm satisfied with all three. The 25-year-old is an AI native, and so is the 45-year-old. I'm not satisfied with the three rules; I'm still an old man at the age of 25. AI natives are a state, not an age group. The trouble is that tickets in this state are works, not resumes. 02 The two lists spread the results of this round on the table. These are two lists. The first one is an all-AI native company. Their valuations are not rising; they are exchanging orders of magnitude. List 1 · Upstream OpenAI raised $122 billion in a single round of financing in Q1 2026, followed by $852 billion, the largest private equity financing in history. Anthropic Q2 had a single round of $65 billion, after investing $965 billion, accounting for about half of the total global venture capital for the quarter; the revenue operating rate in May reached about $47 billion. DeepSeek raised about 70 billion yuan in its first round of financing in May 2026. In April of the same year, Liang Wenfeng raised his direct shareholding from 1% to 34%, and controlled a total of about 84.29% of the shares through related entities. The Dark Side of the Moon (Kimi) was estimated at $4.3 billion in December 2025; it went for three consecutive rounds from January to February 2026 to reach 18 billion; the D round in May was about $2 billion, breaking 20 billion dollars after the investment; the July round surpassed $3.5 billion, after investing 35 billion dollars; the pre-IPO target was 50 billion dollars. ARR broke 100 million in March, 200 million in May, and held steady at 300 million US dollars in June, with APIs accounting for more than 70%. Smart Spectrum · MiniMax successively landed in Hong Kong stocks in early 2026, with a market capitalization exceeding 100 billion yuan. It was one of the first major model companies listed in China. The second one...

4d agoWendy#AI #DeepSeek
When local city investment started selling tokens, did this student agree?

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
After losing 10 billion US dollars in three months, why did DAT's stock price not fall but rise?

After losing 10 billion US dollars in three months, why did DAT's stock price not fall but rise?

Author: Eric, Foresight News Original title: After losing 10 billion US dollars in 3 months, DAT began to return to rationality. The financial reporting season, which had just ended, the Crypto Treasury Company (DAT) handed over a seemingly terrible answer. Strategy's net loss for the second quarter was US$8.22 billion, of which 8.32 billion was a reduction of the fair value of Bitcoin holdings; Strive had a net loss of US$258 million, with over 90% falling prices of Bitcoin and STRC preferred shares held by it; Sharplink's net loss of US$394 million; Metaplanet's net loss of 182.8 billion yen (about US$1.15 billion) in the first half of the year, of which about US$430 million in the second quarter; Bitmine, due to the fiscal year ending in August, It lost only $83.6 million in the March-May fiscal quarter, but the cumulative net loss over the past nine months has exceeded $9 billion. The five companies combined had a net loss of about 10 billion US dollars in the second quarter, and accumulated more than 30 billion US dollars in the first half of the year. A year ago, such a statement was enough to trigger a panic sell-off. But what actually happened was a different story. Strategy's stock price closed up 4.73% on the day the earnings report was released, while the options market originally fluctuated 8% in both directions. From the low at the end of June, Bitmine rebounded about 36%, Sharplink rebounded about 37%, Strategy and Strive rose more than 10%, and Metaplanet also rebounded about 15% from its late-June low. Losses are real, but everyone knows that DAT's second-quarter earnings report must have been a huge loss, the difference between 10 billion and 9.9 billion dollars. Large DAT companies have their own dashboards, or at least there are people who continuously count relevant data. Every financing, every time Bitcoin or Ethereum is being watched by the world with a magnifying glass. Therefore, everyone in the market can see how much money was lost in the second quarter. The financial report simply confirmed what had already happened. What has caused the stock prices of these DAT companies to “bottom up” is that both the market and the company have returned to rationality. In the second quarter, Strategy raised $8.4 billion in a single quarter, surpassing any quarter of last year; in May, it repurchased $1.5 billion of convertible bonds at a face value of 9.2 billion, reducing total convertible bonds from 8.2 billion to 6.7 billion dollars; and in June, Sharplink completed a targeted increase of $75 million at a price higher than net asset value, while using an average price of $4.70 to buy back its shares. In the performance guidance and earnings call, most of these companies invariably gave the same direction: focus on increasing the “content” of each share of crypto assets. Last year, DAT told a story of growth. Whoever buys coins faster will rise. The tide receded this year, and the surviving companies all exchanged KPIs for the same indicator, the number of crypto assets corresponding to each share. Strategy's Bitcoin content per share increased 5% month-on-month in the second quarter; Metaplanet's fully diluted Bitcoin holdings increased 9.6% in the first half of the year; Sharplink repeatedly emphasized the increase in ETH content per share. Accompanying this goal is discipline. Metaplanet clearly implements a set of capital allocation policies. When MNaV is above 1x, it issues additional shares to buy coins, stops issuing additional shares when it is less than 1x, and instead uses preferred shares and credit instruments, and even repurchases stocks. In the second quarter, just because its MNaV fell below 1 times, the company voluntarily abandoned targeted increases from third parties, preferring to slow down the growth rate of its holdings rather than dilute shareholders at a discount. Sharplink and Strategy have also launched repurchases. Treasury companies are no longer brainlessly expanding, but are returning to a simple question: how to make each share more money behind it. Strategy even went against its promise to “never sell coins” for this goal, and its stock price also had the lowest rebound among mainstream DAT companies. This is a pain that must be experienced from “above” to rationality. A new tool for STRC model apprentices to achieve this goal is STRC, invented by Strategy in July of last year, a perpetual preferred stock with a face value of 100 dollars anchored and dividends adjusted monthly. The logic is simple, use around 12%...

4d agoForesight News#DAT
Meta can't keep the Chinese University of Science and Technology hegemony: the big model in Silicon Valley, the Chinese are starting to form their own games

Meta can't keep the Chinese University of Science and Technology hegemony: the big model in Silicon Valley, the Chinese are starting to form their own games

He dropped a $100 million, four-year “contract” in exchange for leaving after 14 months — the talent Zuckerberg had taken from OpenAI and left Meta. In the summer of 2025, Zuckerberg personally knocked out Jiahui Yu (Jiahui Yu), the head of multimodal research, from OpenAI using a salary plan with a total value of up to 100 million US dollars and covering four years. Silicon Valley is on the sidelines, and the industry calls it “stealing people at sky-high prices.” However, just 14 months later — on August 14, 2026, the star researcher, whom Meta had high hopes for, announced his departure and started his own business. A year ago, the blockbuster in the industry ended up being held for a shorter period of time than an NBA season. Just eight days before leaving his job, Muse Spark, the multi-modal model he led, had just been updated to version 1.2. From forming the team to continuously launching the four product lines Muse Spark, Voice Mode, Muse Image, and Muse Video, Yu Jiahui's year at Meta covered almost the entire process of this new team from construction to intensive delivery. Muse Image finished second in the Arena Wensheng Trials Test, beating Google Nano Banana, behind OpenAI GPT Image 2; Muse Video ranked third in the Wensheng video rankings. For Meta, this is certainly an impressive report card. But for Yu Jiahui, this is just an interlude. In his departure statement, he said he was “increasingly drawn to an issue that is critical to the future of humanity but has yet to be fully explored.” Details of the new company have not been disclosed, but he has decided to leave. From the junior class to the history of Yu Jiahui, the top in Silicon Valley, he is at the “top” level for any major AI company. Born in 1995 in Cixi, Zhejiang. In 2012, while still in his sophomore year of high school, he was admitted early to the Junior Class College of the Chinese University of Science and Technology. During his undergraduate studies, he won several contests, including the National Parallel Application Challenge Championship. After graduating in 2016, he went to the University of Illinois at Urbana-Champaign (UIUC) to study for his PhD in computer vision. This scholar trained many famous figures in the field of AI, such as Zhou Xi, founder of Yuncong Technology, and Han Xu, founder of Wenyuan Zhixing. After graduating from her PhD, Yu Jiahui's career progressed step by step. He has worked as a senior research scientist and manager at Google Brain and Google DeepMind, and has participated in the development of visual modules for the Gemini multi-modal project. Joined OpenAI in October 2023 as the head of the Perception (Perception) team, leading the development of GPT-4O and O-series inference models. In June 2025, Zuckerberg personally stepped down, and Yu Jiahui joined former OpenAI researchers such as Zhao Shengjia, Bi Shuchao, and Ren Hongyu into Meta's newly formed super intelligent team. According to foreign media Wired, Meta's compensation package was as high as $100 million — although Meta CTO Andrew Bosworth later clarified that this was not a one-time signing bonus, but a four-year total compensation plan that included stocks, bonuses, and performance conditions. But even so, this is one of the few sky-high contracts in the AI field. (Photo source: One mu of three-quarters of land) After conversion, even though Yu Jiahui only worked for 14 months, Meta paid an estimated cost of more than 25 million dollars for this short period of cooperation — but the actual cost of sunk was even higher. After all, the investment in team building and project start-up cannot be proportionately calculated. The fanaticism of the capital market is driving Silicon Valley's talent exodus, and Yu Jiahui's departure is by no means an exception. In fact, Silicon Valley in 2026 is experiencing an unprecedented “exodus” of AI talents. According to data from the research platform AlphaXiv, Meta alone has lost more than 200 well-known researchers, and another 929 researchers have “worked at Meta but have left their jobs.” In October of last year, Meta drastically cut more than 600 researchers in the AI business. In June of this year, with Llama 4's poor market performance and the company's implementation of more stringent performance reviews, it is expected that 15% to 20% of employees will be rated as “below expectations”, and many senior researchers have switched to competitors. Tech author Gergely Orosz pointed out that Meta's internal organizational restructuring and efficiency adjustments have caused engineers to feel uneasy, and many senior experts have begun to remain open to external opportunities. Google's situation is no less than happy...

4d agoBitpushNews#AI #Yu Jiahui #original #Silicon Valley
After disbanding AI Lab and spending 84.6 billion dollars to buy cards in half a year, Tencent is going against the current

After disbanding AI Lab and spending 84.6 billion dollars to buy cards in half a year, Tencent is going against the current

Author: Activision BeatingOriginal title: Tencent Still Has Dreams On August 12, 2026, Tencent released its financial report for the second quarter. Capital expenditure for a single quarter, $52.78 billion. Three months ago, that number was 31.9 billion. Moving forward a year, the total for the whole year would be less than 79.2 billion. This company has always been known for spending money with restraint. The speed at which it bought cards was once slow enough to make the market wonder if it actually wanted AI at the table. Now, it has brought the speed of spending money to this level within a year. At the earnings conference on the same day, Ma Huateng said that Tencent is “building a brand new, AI-enabled Tencent.” The hybrid was renamed HY, and Hy4 will be released soon. The last time this company described itself as “brand new” was in the era when WeChat was born. Tencent still has dreams. Its dream is not just AI; it needs to relearn to be an unstable company. In 2018, Pan Ran said in “Tencent Has No Dreams” that Tencent is a company like water. Water is good for all things, and there is no dispute; wherever there is a channel, it flows. Water has no personality, so water doesn't have dreams. It is natural for water to flow to a low place; backflow is for those who have reflux. In 2026, the 28-year-old company did something against nature. It admits that the article from eight years ago was right. It admits that it is no longer possible to live like water. On Wednesday, May 5, at 9 p.m., “Tencent Has No Dreams” was published. 13,000 words. At 2 o'clock in the evening, Liu Chiping and Tencent PR director Zhang Jun responded in the circle of friends. Liu Chiping said that Tencent is a larger organization and ecosystem than the outside world can imagine. “It's too narrow to reduce Tencent to the gains and losses of a product, a kind of strategic deployment, and one person's will.” At 2:19, a screenshot suspected of Ma Huateng's response began circulating in the circle of friends. At 2:39 the real Ma Huateng spoke up, saying “It's nice to have criticism” to a friend who cares about him. Afterwards, he said, “From writing the first line of code, my dream was how to make the best product, not how much money to make.” During the day, the national media quoted almost the full screenshot of Ma Huateng's response. Even Zhang Yiming spoke for Tencent in his circle of friends, saying this was a “Don Quixote imagination.” Tencent is not only powerful, but it is also constantly evolving in every dimension. Zhang Jun was on the long-haul flight that day. After landing, he said, “We certainly weren't as bad as the outside world thought, but the criticism also made us realize that we weren't as good as we thought.” Of course, there were a few different voices about that article at the time. Hong Bo said that many of the questions mentioned in the article are real questions, but is there only one correct answer for such a large company? “Perhaps the author thinks Zhang Yiming is the only correct answer. He is a bit superstitious about Zhang Yiming.” That article also recorded an earlier story. At the beginning of 2011, just after the 3Q war ended, Tencent held a general meeting to discuss what Tencent's ability to open up is. Ma Huateng asked the 16 executives who attended each to write down what they thought Tencent's core competencies were on paper, and came up with a total of 21 answers. Finally, decide on two. Capital, flow. The term capital was advocated by Liu Chiping. Opening up means releasing traffic and turning it into an investment. Traffic is open, capital is open, “I don't do it myself anymore.” These two terms have governed Tencent for ten years. The entrance to WeChat traffic and the exit of investment traffic is in the middle is a steady stream of cash generated by games and advertisements. JD's e-commerce portal entered the WeChat Jiugong grid. Sogou picked up the search, and Meituan took over the local life. Traffic is exchanged for shares, and shares are exchanged for allies. In ten years, Tencent's market capitalization has increased tenfold, surpassing Facebook's. When that article was published, it still looked invincible. If you look back and reread it eight years later, you'll find that the article predicted almost every time Tencent fell since then. Ten years later, on December 23, 2021, Tencent distributed 14.7% of JD shares to its shareholders, with a market value of about HK$100 billion. In January 2022, Sea holdings were reduced and $3.2 billion was cashed out. In November 2022, 9.6% of Meituan was split, or approximately HK$159.4 billion. The capital, which was designated as a “core competency” back then, was personally destroyed by Tencent. The water has flowed back and forth for the first time in decades. There is a section in the first AI Dream article that not many people paid attention back then. It's written in Tencent's AI. The Go program “Amazing Art” created by AI Lab successively lost to two amateur games. One is the personal hobby of Headline's vice president, and the other is an amateur work by several engineers on the WeChat translation team. Few people realize that...

5d ago动察Beating#AI