每30个韩国成年人就有1人快爆仓的 找了一下韩国金融投资协会的数据，韩国一共超过120万个杠杆账户触及margin call，假设韩国成年人约 3600万人，3530万÷120万≈29.4😂 截至7月13日，韩国因为投资者没有及时补足交易欠款而被券商强制卖出的股票，累计达到4519亿韩元。 仅月9日一天，强制卖出规模就达到1422亿韩元，接近前一天288亿韩元的5倍。

今天王宁去了苹果总部，还给两任CEO送了价值499的labubu 段永平表示，他今天也去见了新CEO，但刚好错过了 不知双方达成了什么合作。现在泡泡玛特一线城市和海外开店，都会优先选在苹果店隔壁

Today, we launched GPU compute forward curves derived from our prediction market prices. Forward curves are now available on Nvidia B200. H200, and A100 chips. Forward curves track implied future prices. They are how mature commodity markets form expectations, allocate capital, and manage risk. Energy, interest rates/SOFR, FX, metals, and agricultural markets all rely on market-implied forward prices. Despite becoming one of the key inputs in the global economy, compute has lacked that market-derived infrastructure. Compute right now is where oil was before NYMEX — traded only via OTC deals, just like oil used to trade OTC between producers and refiners. As compute becomes as fundamental to the economy as energy, the industry will need a similar derivative market to promote efficient price discovery. Prediction markets are uniquely suited to this problem. Compute is not one uniform commodity and spans many chips, grades, tenors, locations, and contract structures. A live prediction market can aggregate those dispersed views into transparent prices that reflect market expectations for different maturities. The opportunity is big. Hyperscalers are spending over $700B on compute this year and the market is expected to grow to $7-10T by 2030. If this market behaves like traditional commodity markets, a liquid derivative market could be 10-20x bigger than the underlying spot market. Compute is still not uniform enough, but this is a step towards standardization as forward curves will help us see the rise and fall of different model prices and how they correlate. The forward curve is a first step. Up next: futures and perps.