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#韩股跌超6%触发交易暂停 South Korean Stocks Midday Update: KOSPI Plunges 5.61%, Semiconductor Sector Sells Off Across the Board
South Korea’s KOSPI index is currently at 6484.69, down sharply by ‑5.61%. The index has fluctuated violently intraday, opening at 6528.77 today and rising to 6614.39 before turning lower, hitting an intraday low of 6400.81, with an amplitude of 3.11%. China-South Korea semiconductor ETFs also plunged 5.32%, with memory chip-heavy constituents becoming the main force behind the sell-off.
Market Analysis
South Korean stocks opened higher this morning but failed to extend their gains before plunging unilaterally. The South Korean stock market is a global bellwether for memory chips, with Samsung and other memory giants accounting for a large weighting in the index. After the memory sector continued rising in the previous period and accumulated substantial profit-taking pressure, funds rushed to lock in profits today, directly dragging the broader market sharply lower. This formed an internal and external resonance with the large capital outflows from memory leaders such as GigaDevice and CXMT in the A-share market today.
Sentiment across Asia-Pacific markets has shown a chain reaction. South Korean stocks are not the only market weakening today; the Shenzhen Component Index and ChiNext Index in the A-share market also plunged sharply, while growth and technology sectors came under broad pressure. Overseas funds have begun taking partial profits from this round of AI memory rally, no longer simply chasing prices higher, and risk appetite has clearly declined.
There is a clear divergence among sectors. Technology manufacturing has retreated sharply, while funds have likewise shifted toward defensive assets. Semiconductors and hardware stocks have sold off, while defensive assets have held up relatively well. This fund-flow behavior is highly consistent with today’s A-share market logic, with global funds simultaneously rotating from high positions to low positions. The volatility in South Korean stocks offers strong reference value. Their late-session performance will directly affect the opening sentiment of the A-share semiconductor and memory sectors this afternoon. If South Korean stocks continue to fall, high-position technology stocks in the A-share market will face further sentiment pressure; only if South Korean stocks can stop falling and stabilize will domestic technology sectors have an opportunity for sentiment recovery.
This sharp decline in South Korean stocks is not an independent move in a single market, but rather reflects the concentrated realization of profits globally after the technology sector’s major rally in this round. For A-share investors, it is important to recognize changes in the external environment. Do not rush to bottom-fish in high-position memory and computing-power sectors; wait for synchronized stabilization signals in domestic and overseas markets before considering positioning.
Asia-Pacific markets are retreating across the board. Do you think the semiconductor sector’s short-term correction is over?#我的七夕交易分享 $SK Hynix ‌

#OpenAI二季度亏损扩大 OpenAI's Revenue Grew 18% Yet Was Overtaken—What Exactly Is Wrong with AI's Business Model?
OpenAI released its second-quarter data: revenue reached $6.7 billion, up 18%, yet it was overtaken by Anthropic, while losses continued to expand.
This is not merely a question of which company is ahead; the business model of the entire AI foundation model industry is undergoing a profound crisis.
The Fierce Race in AI and the Balance Between Profit and Loss
The data is brutal. OpenAI's revenue was $5.6 billion in the first quarter and $6.7 billion in the second quarter, with quarter-over-quarter growth of 18%, which looks good. But Anthropic's revenue during the same period was $8.5 billion—not only overtaking OpenAI but leading by $1.8 billion. More importantly, OpenAI's losses are expanding—this is the most dangerous signal.
Many people are still debating which model is smarter and which technology is more advanced. I want to say: don't be misled by technology's halo. When a company's losses are growing and it is overtaken by a competitor in revenue, this already points to a fundamental problem: today's AI business model may be heading in the wrong direction.
AI's “Power Plant Dilemma”: The Stronger the Technology, the Higher the Cost
Let's first look at a reality: generating a single image with OpenAI costs approximately 2.12 cents. Processing 1,000 tokens costs anywhere from 0.03 to 12 cents. How much do users pay? ChatGPT Plus costs $20 per month, which does not seem expensive.
Foundation Models Are Like High-Energy-Consuming Power Plants
But that is precisely where the problem lies. AI foundation models are like super power-hungry power plants: the more electricity they generate, the more coal they burn. The more frequently users use them, the more severely the company loses money.
My observation is that foundation model companies have fallen into a vicious cycle: to prove that their technology is leading, they must make their models larger and smarter; the larger the model, the higher the inference cost; the higher the cost, the harder it is to make money. This is a dead loop.
Why was Anthropic able to overtake OpenAI in revenue? My analysis is that it may have found a more effective customer base. Enterprise customers and developers—groups willing to pay for certainty—are the breakthrough point for AI commercialization. OpenAI, meanwhile, still relies heavily on consumer users, which happens to be the hardest market to monetize.
Lack of Product Thinking: A Foundation Model Does Not Equal a Good Product
Here I want to point out a fact many people are unwilling to admit: technological leadership does not equal product success. OpenAI has GPT-4o, Sora, and the world's most advanced foundation models. But so what? Users do not want technical specifications; they want products that can solve problems.
For example, what does a small or medium-sized business owner care about when using ChatGPT to write marketing copy? They care about the hassle of having to retune the prompt every time, the uncertainty of outputs that are sometimes good and sometimes bad, and concerns about data security. Has OpenAI solved these pain points?
I don't think so. Foundation model companies generally suffer from “technological narcissism”—believing that their models are smart enough and that users should adapt to them. This is completely misguided product thinking.
What does genuine product thinking look like? It means thinking from the user's perspective: What problems do you need to solve every day? What are you willing to pay for? What is your biggest pain point?
Judging from its financial data, OpenAI has clearly not gone far enough down this path. Revenue growth alongside expanding losses indicates that costs are out of control. Being overtaken by Anthropic indicates that it is half a step behind in commercial deployment.
Three Fatal Misconceptions in the Business Model
In my view, the business model of AI foundation models contains three fatal misconceptions.
First, excessive reliance on the API economy. Many foundation model companies think that opening up APIs for developers to use will allow them to build an ecosystem. But in reality, an API is merely a tool, not a solution. Developers want AI capabilities that are stable, affordable, and reliable—not services that become more expensive from time to time.
Second, neglecting vertical applications. Foundation models can do everything, but they do not do anything deeply enough. Healthcare, law, education, and finance—each vertical has unique needs and barriers to entry. General-purpose foundation models often struggle in these fields.
Third, underestimating enterprise needs. Enterprises do not want flashy AI demonstrations; they want AI tools that can be integrated into workflows, are secure and controllable, and deliver predictable results. This market has high barriers to entry, but also great value. Anthropic's overtaking OpenAI may well be the result of a breakthrough in this market.
My judgment is that the future winners in AI will not necessarily be the companies with the strongest technology, but those that best understand how to turn AI technology into commercial value.
The Way Forward: From a Technology Race to Value Creation
OpenAI's predicament has sounded an alarm for the entire AI industry. The speed at which the technology race is burning money has already surpassed the speed of commercial monetization.
So where is the way out?
First, move from general-purpose to vertical applications. Foundation models need to “go deeper,” penetrating specific industries and scenarios. A specialized model proficient in medical diagnosis may have greater commercial value than a general-purpose model that can do a little of everything.
Second, move from models to applications. Users do not buy models; they buy solutions. How to package AI capabilities into products that enterprises are willing to pay for will be the key to competition in the next phase.
Third, move from burning cash to generating cash flow. AI companies must find sustainable profit models instead of relying forever on investors for funding. This means strictly controlling costs, precisely identifying paying users, and establishing genuine commercial barriers.
OpenAI's second-quarter data appears on the surface to show revenue growth alongside being overtaken. At a deeper level, it reflects the collective anxiety over the business model of the entire AI industry.
The excitement surrounding technological breakthroughs has passed. It is now time to face the harsh commercial reality. AI is not magic; it needs to solve real-world problems, create real-world value, and earn real-world profits.
Over the next two years, we will see the first large-scale shakeout in the AI industry. Companies that only know how to build models but do not understand how to build products will gradually fall behind. Those that truly understand users, cultivate applications deeply, and establish sustainable business models will become the new winners.
OpenAI still has a chance, but time is running out. Every AI entrepreneur should read a clear signal from this set of data: technology is important, but business is more important. Technological breakthroughs without commercial support will ultimately be nothing more than toys in a laboratory.
The second half of AI is only just beginning$OPENAI ‌

#宇树科技上市首日大涨629% 🚀 Phenomenal Surge: A Historic Moment for A-Shares
On August 19, 2026, Unitree Robotics (688836.SH) officially debuted on the STAR Market of the Shanghai Stock Exchange. It opened at 1,100 yuan per share, surging 629.44% from its IPO price of 150.80 yuan, sending its total market capitalization soaring to 444.9 billion yuan. Based on 500 shares per lot, investors allocated shares saw unrealized gains of up to 474.6k yuan per lot, setting a new profit record for new listings since the launch of China’s registration-based IPO system.
🏆 The “First Humanoid Robotics Stock”’s Strong Fundamentals
Founded in 2016, Unitree Robotics is a global leader in the high-performance general-purpose robotics industry.
· Global shipment leader: Its cumulative sales of quadruped robots have exceeded 33,000 units, while humanoid robot shipments surpassed 5,500 units in 2025, placing both categories first globally.
· Astonishing explosive growth: From 2023 to 2025, revenue surged from 159 million yuan to 474.6k yuan, with a compound annual growth rate as high as 226.78%; gross margin increased from 44.22% to 60.13%, and the company turned a profit.
· Backing from top strategic investors: Its strategic placement lineup includes DeepSeek, Tencent-affiliated entities, and the National Council for Social Security Fund, among others.
⚠️ Concerns Beneath the Celebration: High Valuation and Slowing Performance
Behind the surge, the risks and disagreements are equally significant:
· Valuation has reached astronomical levels: Even at the IPO price, the price-to-earnings ratio had reached 219x; based on the opening price on the first day, the forward P/E ratio was as high as approximately 1,600x.
· Significant slowdown in earnings growth: In the first half of 2026, revenue increased 48.54% year on year to 1.7B yuan, while net profit attributable to the parent company excluding non-recurring items fell 19.34% year on year. The company attributed this to a higher comparison base, moderating industry enthusiasm, and intensifying competition.
Unitree Robotics’ listing marks an important milestone in China’s humanoid robotics industry’s transition from the laboratory to commercialization. However, a forward P/E ratio as high as 1,600x has fully, or even excessively, priced in future growth expectations. For investors, this is both an opportunity to witness history and a risk-laden wager requiring immense courage and caution.

The Big Three Storage Chipmakers Face a “Black Tuesday,” with the Entire Sector Plunging
On August 19, 2026 (Tuesday), the U.S. storage chip sector faced a systemic sell-off. The three giants—SanDisk, Micron, and SK Hynix—all plunged, while the Philadelphia Semiconductor Index tumbled nearly 5%, marking its biggest single-day decline since July 29.
SanDisk (SNDK) closed down $161.07, or 9.01%, at $1,625.78, with trading volume reaching $30.25B. SanDisk had just surged 8.88% in the previous session and had risen sharply by approximately 35% on a weekly basis, making concentrated profit-taking the direct catalyst for the plunge. After-hours data showed that SanDisk continued to decline, at one point falling to $1,586.24, with the loss widening to 2.43%. Notably, SanDisk’s share price has climbed more than 35-fold from its 52-week low of $43.20, but remains approximately 32% below its record high of $2,354.39 on June 22.
Micron Technology (MU) closed down $70.99, or 7.02%, at $940.76. Although its decline was smaller than SanDisk’s, Micron topped the U.S. stock trading volume rankings with $34.95 billion in turnover, highlighting the intense capital battle. Micron had just broken above the $1,000 mark on Monday, bringing its five-session winning streak to an end.
SK Hynix became the hardest-hit stock in the Asia-Pacific market. Its U.S. ADR (SKHY) fell 9.2% to close at $155.62. The decline in its South Korean-listed shares was even more severe—during early trading on August 19, they fell as much as 8.2% to 1.52M won, with the intraday loss briefly widening to 10%. South Korea’s KOSPI Index plunged more than 6% at one point as technology stocks collapsed across the board, triggering a circuit breaker, while Samsung Electronics fell more than 7%.
The plunge resulted from the convergence of three pressures: the U.S. 30-year Treasury yield surged intraday to 5.3361%, its highest level since 2007, significantly raising the discount rate for growth-stock valuations; Pennsylvania introduced the strictest data-center regulations in the U.S., requiring developers to provide their own power and bear all related costs, directly undermining expectations for AI infrastructure investment; and rising energy and inflation risks due to tensions in the Middle East accelerated fund withdrawals from the storage chip sector, which had posted massive gains this year. Mizuho Securities analysts noted that market trading volume was low in August, and program trading may have further amplified the decline in chip stocks.
Overall, this plunge does not represent a sudden deterioration in the storage industry’s fundamentals, but rather a systemic de-risking triggered jointly by surging long-term bond yields, concerns over an AI valuation bubble, and excessive short-term gains. The future direction of the storage sector after three consecutive declines remains uncertain, and continued pressure from changes in the macro interest-rate environment warrants caution.
#我的七夕交易分享

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That man, those two slices of pizza, and a one-way road
On May 18, 2010, in Florida, programmer Laszlo Hanyecz opened BitcoinTalk and typed a line that would later be engraved into crypto history:
“I’ll pay 10,000 BTC for a couple of pizzas.”
At that time, 1 BTC ≈ $0.004, 10,000 coins ≈ $40. He wanted two large pizzas, one with Italian sausage and green peppers, the other with mushrooms and olives. The post was up for four days, ignored by everyone.
On May 22, a 19-year-old British teenager with the username jercos said: “I’ll order Papa John’s for you, send me your address and the coins.” The transaction was completed. Laszlo took a photo — blurry, with an open paper box on the table, the pizza inside looking no different from the $30 delivery apps offer today.
But with that bite, two worlds were bitten off.
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What happened to him later?
Laszlo is not an ordinary person. He’s not just the “Pizza Guy” — he developed the first Mac Bitcoin client and pioneered GPU mining. The code he wrote allowed ordinary people to mine Bitcoin with graphics cards, ending the era of CPU mining. Satoshi Nakamoto himself emailed him politely, saying: “I’m a bit worried, this might lead to too much centralization of hash power.”
Laszlo later joked: “I might have messed up Bitcoin.”
As for those BTC — he spent nearly 100k coins on pizza, servers, gadgets. Today (2026.5.21), with BTC ≈ $67,200, that’s roughly $100k in total value.
When asked if he regrets it, he said:
“I regret not trying more flavors. Bitcoin is meant to be spent. If everyone just hoards and never spends, it’s just a string of code forever.”
This man ate the most expensive meal in history, yet fed the entire blockchain.
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Brainstorm 1
PoP Consensus Mechanism (Proof of Pizza)
Future L1 blockchains don’t require staking ETH or GPU power. Nodes exchange pizzas with each other; the more pizzas sent and the more popular the flavors, the higher the block weight. The penalty for double-spending is: sending the other party a lifetime supply of pineapple pizzas (Italians are furious, but Hawaiian fans rejoice).
Brainstorm 2: “Regret Pills” Perpetual Contract
Exchanges launch a new product: Pizza Perp, where the underlying isn’t BTC price but “How does Laszlo feel today if he hadn’t spent those 10,000 BTC?” Long position = you think he regrets; short position = you think he finds the pizza delicious. Leverage up to 100x, liquidation triggered by a surge in global pizza orders.
Brainstorm 3: Laszlo Meme DAO
Community launches a DAO, crowdfunding 0.1 BTC, with the goal — find Laszlo and get him to eat another pizza, with a full video recording. If he says “I don’t regret,” airdrop $NOPIZZA tokens; if he says “Actually, I do regret,” airdrop $REGRET. Whatever he says, the tokens will be worth zero. Because the market only cares about stories, not truth.
Brainstorm 4: Pizza Day AI Performance Art
On May 22, 2026, at 14:11 (the original trading time), all bots connected to OpenAI API are collectively paused for 1 second, sending 0.00001 BTC to Laszlo’s historical address with a note: “This is your tip, the rest of the coins we HODL for you.”
Bitcoin Pizza Day isn’t a dark humor mocking “missing out on a billion.” It’s a reminder:
The meaning of money lies in exchange, and the meaning of exchange is life.
Laszlo got the pizza he wanted, and the crypto world thus gained its first “real-world exchange rate.” Today, buy a slice of pizza — with BTC, USDT, or cash. Take a photo and post in the group with a message:
“Salute to the hungry man who feeds the future.”
🍕 Happy Pizza Day, don’t let your coins go hungry, and don’t let yourself go hungry.
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If someone actually issues tokens based on these brainstorms, remember to buy me a slice of pie 😋#Gate广场披萨节

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⌛ Deadline: May 12th, 12:00 PM (UTC+8)

🏮 Lantern Festival Celebration · Win Great Prizes! Gate Plaza Riddle Guessing Party Kicks Off in Excitement!
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📅 March 3rd 10:00 - March 6th 18:00 (UTC+8)