Global attention! The Fed meeting minutes hit at 2:00 a.m. tonight—can they curb the “U.S. bond storm”?
① At 2:00 a.m. Beijing time on Thursday, the Fed will release the minutes of its July monetary policy meeting; ② With Fed Chair Walsh reducing communications with the outside world and the U.S. Treasury selloff wave escalating, the significance of these minutes has become increasingly evident. At 2:00 a.m. Beijing time on Thursday, the Federal Reserve will release the minutes of its July monetary policy meeting. This will be the second set of minutes released since Fed Chair Kevin Walsh took office. Against the backdrop of the Fed cutting back on external communication, the importance of these minutes has become even more pronounced. Investors who are urgently seeking incremental information are hoping to glean more clues about the Federal Reserve’s rate path from this document.
AI companies reach out for help: OpenAI records computer actions, while Google uses uploaded content to train AI.
Axios begins investigating what user data AI companies are actually collecting.
The findings show that chat logs aren’t enough anymore. Now they also want to know what you click on your computer, what photos you upload, and what content you’ve viewed—then use that data for memory, personalization, and advertising.
OpenAI has added Computer History. Once Mac users manually enable it, ChatGPT and Codex can record your clicks, inputs, and switches within specific apps and websites, gradually building a long-term work memory about you. The feature is turned off by default; it doesn’t record your screen or audio. OpenAI says temporary action logs won’t be used to train its models.
Google is even more aggressive. A new Search Services History will save images, documents, and audio/video that users upload through services like Lens, Search Live, and Translate—and it can also be used to train generative AI. For accounts that meet the criteria, it’s enabled by default; if you want to opt out, you have to do it yourself. Even some data that is later unlinked from an account may be retained for up to 4 years after entering the training process.
Advertising has kept up too. Meta will use users’ interactions with Meta AI to adjust the content and ads on Facebook and Instagram; OpenAI and Google are also exploring ad models for chatbots. The better AI understands you, the more detailed the “portrait” the ad system has in its hands.
What used to be a concern was that chat logs would be used for training. Now, even how you work on your computer—and what you throw into Google—has started to become data in the hands of AI companies.
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AI wealth-making boom: 45 newly rich people in their 20s and 30s start moving into Silicon Valley’s old-money neighborhoods
A $70 million Hillsborough mansion shows the most concrete picture of the AI wealth-making wave.
On August 6, in the northern part of the San Francisco Peninsula, a newly formed LLC bought a 12-acre estate. The main residence is 12,000 square feet, with an additional 4,600-square-foot guesthouse. There are also a tennis court, a nine-hole golf course, an 18-hole putting green, an outdoor theater, a koi pond, a 2,100-gallon aquarium, and a fountain in the style of the Bellagio—all set on a hillside surrounded by trees.
Mansion bought for $70 million by former xAI co-founder Wu Yuhui
The mansion was sold for $70 million, or about 500 million yuan. The buyer listed on the property ownership documents is Daikon no Hana Capital. But media followed the paper trail from the buyer’s broker to the estate-planning attorney and family trust, and it ultimately led to a 31-year-old Chinese man—former xAI co-founder Wu Yuhui.
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Nvidia invests $1.5 billion to take a stake in SB Energy, targeting 8GW of AI computing capacity; OpenAI will be the sole tenant
On August 17, Nvidia announced a strategic partnership with SB Energy to provide credit guarantees for the PORTS-Pike Technology Park in Ohio, helping build it into a massive data center dedicated to Nvidia’s AI computing infrastructure, with OpenAI as the sole tenant. At the same time, Nvidia invested $1.5 billion in SB Energy. With this move, Nvidia directly entered the underlying infrastructure segment of land, power, and facilities (LPS). Its significance goes far beyond a typical data center investment. The key change is that Nvidia is using its own creditworthiness to “underwrite” financing for AI infrastructure, in return for long-term and exclusive allocation of computing capacity. This marks the chip giant expanding from being merely a supplier of AI hardware into a core participant and organizer in building and operating “AI factory” infrastructure.
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