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橙子Joyce
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橙子Joyce

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价值投资者:以十年为单位投资美股及BTC.ETH.BNB.SOL.推特X:@Joyce88ai
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Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem. Four key takeaways: First NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize. Second Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem. Third The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships. Fourth The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating. When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
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On August 26 at 20:30, the July PCE data will be released. If the reading comes in hotter than expected, expectations for the Federal Reserve’s September policy path are likely to be affected, and fluctuations in U.S. Treasury yields may move in tandem with global risk assets. In addition, the revised estimate of the U.S. real GDP for Q2 will be released on August 26 at 20:30. On a month-over-month basis, investors expect the Fed’s preferred inflation gauge—the core PCE price index—to rise by 0.2%. If the increase is larger, it could lead investors to reconsider expectations that the Fed will stay on hold in September, potentially opening the door for a pullback in gold. Conversely, if the monthly core PCE inflation data is weaker than expected, it may help gold move higher further. Then on Thursday, August 27, traders will focus on the weekly initial jobless claims report. At 22:00 on Friday, the preliminary annual benchmark revision to nonfarm payrolls data will also be released, along with the final reading of the University of Michigan’s August consumer sentiment index. The preliminary annual benchmark revision to nonfarm employment data will indicate whether previously reported U.S. employment figures were overestimated or underestimated. After recent signs of softer hiring, this revision may become even more important. If it suggests a significant weakening in the labor market, it could affect expectations for Fed policy.
On August 26 at 20:30, the July PCE data will be released. If the reading comes in hotter than expected, expectations for the Federal Reserve’s September policy path are likely to be affected, and fluctuations in U.S. Treasury yields may move in tandem with global risk assets. In addition, the revised estimate of the U.S. real GDP for Q2 will be released on August 26 at 20:30. On a month-over-month basis, investors expect the Fed’s preferred inflation gauge—the core PCE price index—to rise by 0.2%. If the increase is larger, it could lead investors to reconsider expectations that the Fed will stay on hold in September, potentially opening the door for a pullback in gold. Conversely, if the monthly core PCE inflation data is weaker than expected, it may help gold move higher further.

Then on Thursday, August 27, traders will focus on the weekly initial jobless claims report. At 22:00 on Friday, the preliminary annual benchmark revision to nonfarm payrolls data will also be released, along with the final reading of the University of Michigan’s August consumer sentiment index.

The preliminary annual benchmark revision to nonfarm employment data will indicate whether previously reported U.S. employment figures were overestimated or underestimated. After recent signs of softer hiring, this revision may become even more important. If it suggests a significant weakening in the labor market, it could affect expectations for Fed policy.
橙子Joyce
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Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
橙子Joyce
·
--
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
橙子Joyce
·
--
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
橙子Joyce
·
--
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
橙子Joyce
·
--
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
橙子Joyce
·
--
Decoding NVIDIA’s and Poolside’s latest deal: NVIDIA pays $6 billion to obtain a non-exclusive license for Poolside’s “Model Factory” technology—core software for Poolside’s construction of the Laguna series open-source code models. At the same time, NVIDIA has extended invitations to more than 100 Poolside engineers, who will join NVIDIA’s Nemotron open-weight model project. Since it launched in 2023, the project has been developing larger, more advanced versions; reports suggest the parameter scale could reach the trillion level. There is also roughly a $1 billion equity investment to go along with it. This is a signature move from NVIDIA’s “plow with a hoe” to “dig for gold,” as Huang Renxun uses it to dive deeper into the model layer and build full-stack “AI factory” capabilities tightly integrated with NVIDIA’s ecosystem.

Four key takeaways:

First
NVIDIA aims to recreate one of the world’s strongest open-weight models, benchmarking China’s open-source models while directly challenging leading U.S. closed-source companies such as OpenAI and Anthropic. Open-weight models are cheaper to run and easier to customize.

Second
Expanding from selling GPU hardware to the software and model layers strengthens NVIDIA’s control across the entire upstream and downstream ecosystem.

Third
The moat deepens, but competition with customers also intensifies: improvements in open-weight model capabilities may drive GPU demand, but Nemotron directly competes with large customers’ closed models, which could strain relationships.

Fourth
The trend can be summarized as large-model providers developing their own chips, and chipmakers developing their own models—competition is further escalating.

When Huang Renxun publicly voiced support for open source at the end of July, it was effectively laying the groundwork for NVIDIA’s own open-source models. This deal is a crucial step for NVIDIA to push harder in the open-source race between China and the United States. If the upgraded Nemotron’s performance can catch up, it will further benefit cloud providers and software companies that control customer workflow data.
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Bullish
Partly True
The momentum of U.S. economic growth is accelerating. S&P Global’s U.S. Composite PMI rose by 1.5 points in August to 56.0, the highest level since April 2022 and the third consecutive month of gains. At the same time, the Services PMI increased by 2.2 points to 56.8, the highest level since March 2022. The Manufacturing PMI fell by 0.7 points to 53.9, the lowest level in the past five months, but it remains in the expansion range. Meanwhile, U.S. firms’ hiring activity is led by the services sector, with headcount increasing at the fastest pace since January 2025. These data suggest that the United States’ year-on-year GDP growth rate in Q3 2026 will reach +3.0%, compared with +1.5% in Q2. Artificial intelligence is driving a historic wave of growth.
The momentum of U.S. economic growth is accelerating. S&P Global’s U.S. Composite PMI rose by 1.5 points in August to 56.0, the highest level since April 2022 and the third consecutive month of gains. At the same time, the Services PMI increased by 2.2 points to 56.8, the highest level since March 2022. The Manufacturing PMI fell by 0.7 points to 53.9, the lowest level in the past five months, but it remains in the expansion range.

Meanwhile, U.S. firms’ hiring activity is led by the services sector, with headcount increasing at the fastest pace since January 2025. These data suggest that the United States’ year-on-year GDP growth rate in Q3 2026 will reach +3.0%, compared with +1.5% in Q2. Artificial intelligence is driving a historic wave of growth.
Article
Anthropic’s In-House Chip Bet: Poaches Google’s TPU Business Founder—A “Decouple from Nvidia” Gamble on the Eve of a $200B IPOAnthropic is shifting its strategic focus from “battling for compute power” to “building compute capacity.” The company has hired Amir Salek, the founder of Google’s custom chip business, to assemble an in-house chip team, while also collaborating with multiple partners including Fractile, Google, Broadcom, and Samsung to target approximately 3.5GW of TPU capacity by 2027. This “in-house R&D + diversified procurement” dual-track strategy is designed to break away from reliance on Nvidia and reduce inference costs. During the critical window to launch an IPO at a $200 billion valuation, Anthropic is shifting its strategic focus from “battling for compute power” to “building compute capacity,” seeking to directly take control of the foundational infrastructure that supports its explosive growth.

Anthropic’s In-House Chip Bet: Poaches Google’s TPU Business Founder—A “Decouple from Nvidia” Gamble on the Eve of a $200B IPO

Anthropic is shifting its strategic focus from “battling for compute power” to “building compute capacity.” The company has hired Amir Salek, the founder of Google’s custom chip business, to assemble an in-house chip team, while also collaborating with multiple partners including Fractile, Google, Broadcom, and Samsung to target approximately 3.5GW of TPU capacity by 2027. This “in-house R&D + diversified procurement” dual-track strategy is designed to break away from reliance on Nvidia and reduce inference costs.
During the critical window to launch an IPO at a $200 billion valuation, Anthropic is shifting its strategic focus from “battling for compute power” to “building compute capacity,” seeking to directly take control of the foundational infrastructure that supports its explosive growth.
Article
Dalio: U.S. debt crisis could arrive within three years—advises selling bonds, buying gold, and bitcoinBridgewater Fund founder Ray Dalio’s latest article says the U.S. annual budget deficit is as high as $2 trillion, and there is also about $10 trillion in debt that urgently needs refinancing. If the current trajectory is not changed, a debt crisis—"with a margin of error of about two years, either up or down, within three years"—could be on the way. He advises investors to cut back on bonds, raise the gold allocation to 10% to 15% of the portfolio, and hold a small amount of bitcoin to hedge risk. Bridgewater Fund founder and billionaire Ray Dalio issues a warning: the U.S. debt crisis could break out as soon as within three years, and advises investors to reduce their bond holdings, allocating 10% to 15% of their portfolio to gold. He also recommends holding a small amount of bitcoin to hedge risk.

Dalio: U.S. debt crisis could arrive within three years—advises selling bonds, buying gold, and bitcoin

Bridgewater Fund founder Ray Dalio’s latest article says the U.S. annual budget deficit is as high as $2 trillion, and there is also about $10 trillion in debt that urgently needs refinancing. If the current trajectory is not changed, a debt crisis—"with a margin of error of about two years, either up or down, within three years"—could be on the way. He advises investors to cut back on bonds, raise the gold allocation to 10% to 15% of the portfolio, and hold a small amount of bitcoin to hedge risk.
Bridgewater Fund founder and billionaire Ray Dalio issues a warning: the U.S. debt crisis could break out as soon as within three years, and advises investors to reduce their bond holdings, allocating 10% to 15% of their portfolio to gold. He also recommends holding a small amount of bitcoin to hedge risk.
【Anthropic is expected to match or exceed SpaceX’s IPO record】 Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion. According to people familiar with the matter, the AI company Anthropic expects its IPO size to match or exceed the record set by SpaceX. As the AI company accelerates its preparations for going public, a mega-IPO is being lined up. The people familiar with the matter said that Anthropic is conducting related calculations and preparing to file for a potentially large IPO as early as later this month. They added that a recent investor communications meeting chaired by Chief Financial Officer Klao avoided discussing valuation. Data shows that at the time of its IPO, SpaceX—an aerospace company for rockets and satellites—raised $75 billion, becoming the largest initial public offering in history. Because it exercised so-called over-allotment options, the figure ultimately rose to $86.2 billion. This mechanism is typically triggered in the early period after the stock begins trading. Anthropic’s target reflects how leading companies in the AI industry are reshaping the tech investment landscape in an extremely short time. Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
【Anthropic is expected to match or exceed SpaceX’s IPO record】

Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.

According to people familiar with the matter, the AI company Anthropic expects its IPO size to match or exceed the record set by SpaceX. As the AI company accelerates its preparations for going public, a mega-IPO is being lined up. The people familiar with the matter said that Anthropic is conducting related calculations and preparing to file for a potentially large IPO as early as later this month. They added that a recent investor communications meeting chaired by Chief Financial Officer Klao avoided discussing valuation. Data shows that at the time of its IPO, SpaceX—an aerospace company for rockets and satellites—raised $75 billion, becoming the largest initial public offering in history. Because it exercised so-called over-allotment options, the figure ultimately rose to $86.2 billion. This mechanism is typically triggered in the early period after the stock begins trading. Anthropic’s target reflects how leading companies in the AI industry are reshaping the tech investment landscape in an extremely short time. Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
Article
SpaceX has an AI advantage that OpenAI and Anthropic cannot replicateSince 2002, every rocket test and engineering project completed by aerospace giant SpaceX (SPCX) could now be used as training material for artificial intelligence (AI). This makes it far more appealing than simply merging with xAI, which is much more than just a merger between two companies owned by Musk. In fact, according to Musk, Grok 4.7 is currently undergoing additional training using a large amount of SpaceX data, and Grok 5 is expected to use the company’s complete historical dataset. If everything goes according to plan, SpaceX could provide Grok with engineering training that competitors such as OpenAI and Anthropic cannot replicate on their own.

SpaceX has an AI advantage that OpenAI and Anthropic cannot replicate

Since 2002, every rocket test and engineering project completed by aerospace giant SpaceX (SPCX) could now be used as training material for artificial intelligence (AI). This makes it far more appealing than simply merging with xAI, which is much more than just a merger between two companies owned by Musk. In fact, according to Musk, Grok 4.7 is currently undergoing additional training using a large amount of SpaceX data, and Grok 5 is expected to use the company’s complete historical dataset. If everything goes according to plan, SpaceX could provide Grok with engineering training that competitors such as OpenAI and Anthropic cannot replicate on their own.
Verified
Article
U.S. Federal Debt First Surpasses $40 Trillion! Minutes of the Fed Meeting: Do More Officials Think Further Rate Hikes May Be Needed?U.S. federal debt first tops $40 trillion, with interest expense reaching $1.17 trillion this year U.S. Treasury Department data shows that as of Tuesday’s close, the outstanding balance of U.S. public debt rose to $40.05 trillion, marking the first time it has crossed the $40 trillion mark. It is less than five years since it surpassed $30 trillion in January 2022. So far this fiscal year, federal interest expense has reached $1.17 trillion, up 15% year over year, becoming the third-largest federal spending item after Medicare and Social Security. Previously, U.S. Treasury Secretary Bessent announced an expansion of the long-term U.S. Treasury bond repurchase program. After the news was released, Treasury yields fell. More recently, auction yields for the 30-year and 10-year Treasury notes have risen to levels not seen in about 25 years and since 2007, respectively.

U.S. Federal Debt First Surpasses $40 Trillion! Minutes of the Fed Meeting: Do More Officials Think Further Rate Hikes May Be Needed?

U.S. federal debt first tops $40 trillion, with interest expense reaching $1.17 trillion this year
U.S. Treasury Department data shows that as of Tuesday’s close, the outstanding balance of U.S. public debt rose to $40.05 trillion, marking the first time it has crossed the $40 trillion mark. It is less than five years since it surpassed $30 trillion in January 2022. So far this fiscal year, federal interest expense has reached $1.17 trillion, up 15% year over year, becoming the third-largest federal spending item after Medicare and Social Security. Previously, U.S. Treasury Secretary Bessent announced an expansion of the long-term U.S. Treasury bond repurchase program. After the news was released, Treasury yields fell. More recently, auction yields for the 30-year and 10-year Treasury notes have risen to levels not seen in about 25 years and since 2007, respectively.
Article
Is the crypto market finally “bullish”? Bitcoin suddenly surges, briefly breaks $70,000—how should it be interpreted?On Wednesday in U.S. Eastern Time, BTC suddenly rebounded strongly. The price hit a high of $70,059.9, the highest level since early June, and it also recorded the largest single-day gain since March. As the market quickly reversed, a large number of shorts were forced to cover, triggering the biggest wave of Bitcoin short liquidations since 2021, based on available records. According to Coinglass data, within just about an hour, more than $1 billion worth of Bitcoin short positions were forcibly liquidated. Bitcoin had been falling for months, at one point dropping to just over $60,000, while bearish sentiment continued to build. As the price suddenly turned upward, large amounts of passive buy orders generated by short-covering further pushed the coin’s price higher, forming a typical “short squeeze” pattern.

Is the crypto market finally “bullish”? Bitcoin suddenly surges, briefly breaks $70,000—how should it be interpreted?

On Wednesday in U.S. Eastern Time, BTC suddenly rebounded strongly. The price hit a high of $70,059.9, the highest level since early June, and it also recorded the largest single-day gain since March. As the market quickly reversed, a large number of shorts were forced to cover, triggering the biggest wave of Bitcoin short liquidations since 2021, based on available records.
According to Coinglass data, within just about an hour, more than $1 billion worth of Bitcoin short positions were forcibly liquidated. Bitcoin had been falling for months, at one point dropping to just over $60,000, while bearish sentiment continued to build. As the price suddenly turned upward, large amounts of passive buy orders generated by short-covering further pushed the coin’s price higher, forming a typical “short squeeze” pattern.
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Bullish
Verified
The U.S. Treasury steps in to support the market, pushing down the U.S. Treasury yields that have been pressuring global stock markets. The U.S. Treasury announced that it will at least double the size of its buyback program for long-term Treasury bonds. After the news broke, the prices of ultra-long Treasury bonds issued by the U.S. government surged sharply. The backdrop to this move is that global long-term bond markets have recently suffered large-scale selling, and the yield on the 30-year U.S. Treasury briefly spiked to the highest level since 2007 on Monday. At the same time, traders are preparing for a new issuance auction of $16 billion worth of 20-year Treasury notes scheduled to take place soon. In a statement, the U.S. Treasury said, “By increasing the size of the repurchase operations, the Treasury aims to provide stronger liquidity support for the long-dated nominal Treasury market. Within these maturity ranges, market participants have consistently demonstrated strong and stable appetite, which is evidenced by the large volume of high-quality bids the Treasury regularly receives in its long-dated Treasury repurchase operations.” Under the accelerated repurchase plan, the Treasury will focus on repurchasing Treasuries in the 10-to-20-year and 20-to-30-year maturity ranges. Since the end of June, the U.S. Treasury markets in these maturities have been plagued by a “buyer walkout,” with investors’ willingness to take on the bonds clearly lacking. According to the Treasury’s announcement, the government will increase the maximum size of each repurchase operation “by at least” double—from $2 billion to “at least” $4 billion. #黄金 #silver
The U.S. Treasury steps in to support the market, pushing down the U.S. Treasury yields that have been pressuring global stock markets. The U.S. Treasury announced that it will at least double the size of its buyback program for long-term Treasury bonds. After the news broke, the prices of ultra-long Treasury bonds issued by the U.S. government surged sharply. The backdrop to this move is that global long-term bond markets have recently suffered large-scale selling, and the yield on the 30-year U.S. Treasury briefly spiked to the highest level since 2007 on Monday. At the same time, traders are preparing for a new issuance auction of $16 billion worth of 20-year Treasury notes scheduled to take place soon. In a statement, the U.S. Treasury said, “By increasing the size of the repurchase operations, the Treasury aims to provide stronger liquidity support for the long-dated nominal Treasury market. Within these maturity ranges, market participants have consistently demonstrated strong and stable appetite, which is evidenced by the large volume of high-quality bids the Treasury regularly receives in its long-dated Treasury repurchase operations.” Under the accelerated repurchase plan, the Treasury will focus on repurchasing Treasuries in the 10-to-20-year and 20-to-30-year maturity ranges. Since the end of June, the U.S. Treasury markets in these maturities have been plagued by a “buyer walkout,” with investors’ willingness to take on the bonds clearly lacking. According to the Treasury’s announcement, the government will increase the maximum size of each repurchase operation “by at least” double—from $2 billion to “at least” $4 billion.
#黄金
#silver
A single greeting, carries the tenderness of Qixi; a blessing, is the softness of Qixi. May all the deep feelings in this world not be let down, may all true love be cherished well, and may every rush of pursuit be met with the gentlest echoes. 🐦‍🔥🐲🌹🌹🌹🌹🌹🌹🌹🌹🌹
A single greeting, carries the tenderness of Qixi; a blessing, is the softness of Qixi. May all the deep feelings in this world not be let down, may all true love be cherished well, and may every rush of pursuit be met with the gentlest echoes. 🐦‍🔥🐲🌹🌹🌹🌹🌹🌹🌹🌹🌹
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AI burns a billion, Microsoft passes and Meta crashes — the stark contrast between two earnings reports moving in opposite directions clearly shows the market’s differentiated pricing logic for returns on AI spending.The AI race among tech giants is facing a “earnings exam” — Microsoft’s answer was impressive, while Meta stumbled. After trading on Wednesday, the two companies released their quarterly reports on the same day, yet received sharply different market reactions: Microsoft surged higher after hours on the strength of its steady capital expenditure guidance and cloud business growth that beat expectations; meanwhile, Meta fell hard after hours despite posting a record-high revenue figure, as profits came in below expectations. Ongoing AI spending and costly lawsuit payouts have intensified investors’ concerns about free cash flow turning negative, driving the stock price down significantly after the bell. The contrasting outcomes—one report lifting the stock and the other dragging it down—clearly illustrate the market’s differentiated pricing logic for returns on AI investment.

AI burns a billion, Microsoft passes and Meta crashes — the stark contrast between two earnings reports moving in opposite directions clearly shows the market’s differentiated pricing logic for returns on AI spending.

The AI race among tech giants is facing a “earnings exam” — Microsoft’s answer was impressive, while Meta stumbled.
After trading on Wednesday, the two companies released their quarterly reports on the same day, yet received sharply different market reactions: Microsoft surged higher after hours on the strength of its steady capital expenditure guidance and cloud business growth that beat expectations; meanwhile, Meta fell hard after hours despite posting a record-high revenue figure, as profits came in below expectations. Ongoing AI spending and costly lawsuit payouts have intensified investors’ concerns about free cash flow turning negative, driving the stock price down significantly after the bell. The contrasting outcomes—one report lifting the stock and the other dragging it down—clearly illustrate the market’s differentiated pricing logic for returns on AI investment.
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The Fed won’t raise rates—investors aren’t buying Wosch’s inflation-fighting script!Federal Reserve Chair Kevin Wosch has vowed to bring inflation down and keep the annual price increase at 2%, consistent with the Fed’s long-term goal. However, many investors believe the Federal Reserve made little progress toward that target on Wednesday. At the July policy meeting, the Federal Open Market Committee (FOMC) voted 9-3 to keep interest rates unchanged. In addition, at the post-meeting press conference, Wosch did not clarify under what circumstances the central bank would choose to raise rates to curb inflation—over the past five years, the inflation rate has remained far above 2%.

The Fed won’t raise rates—investors aren’t buying Wosch’s inflation-fighting script!

Federal Reserve Chair Kevin Wosch has vowed to bring inflation down and keep the annual price increase at 2%, consistent with the Fed’s long-term goal. However, many investors believe the Federal Reserve made little progress toward that target on Wednesday.
At the July policy meeting, the Federal Open Market Committee (FOMC) voted 9-3 to keep interest rates unchanged. In addition, at the post-meeting press conference, Wosch did not clarify under what circumstances the central bank would choose to raise rates to curb inflation—over the past five years, the inflation rate has remained far above 2%.
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Has an A-share stock king emerged? Changxin Technology’s issue price of 6.8 yuan—now up to 55 yuanRiding to the top immediately after listing. Changxin Technology officially landed on the STAR Market; at the open it surged 471.59%, with a total market cap of 3.31 trillion yuan, surpassing Industrial and Commercial Bank of China to become the A-share “No. 1” by market value. Those who won an allocation could be up more than 20,000 yuan in profit. Trading value exceeded 1 trillion yuan within less than an hour of listing, setting a new A-share single-day record for an individual stock’s turnover. Northeast Securities provided a valuation range of 3.2 trillion to 5.7 trillion yuan. Nomura Securities set a target price of 116 yuan, implying a valuation of about 7.76 trillion yuan. Listed and topped the charts immediately. On July 27, $N Changxin (688825.SH)$ was officially listed on the STAR Market. In the call auction, the highest bid reached 50 yuan per share; the stock opened at 49.5 yuan, up 471.59% from the issue price of 8.66 yuan.

Has an A-share stock king emerged? Changxin Technology’s issue price of 6.8 yuan—now up to 55 yuan

Riding to the top immediately after listing. Changxin Technology officially landed on the STAR Market; at the open it surged 471.59%, with a total market cap of 3.31 trillion yuan, surpassing Industrial and Commercial Bank of China to become the A-share “No. 1” by market value. Those who won an allocation could be up more than 20,000 yuan in profit.
Trading value exceeded 1 trillion yuan within less than an hour of listing, setting a new A-share single-day record for an individual stock’s turnover. Northeast Securities provided a valuation range of 3.2 trillion to 5.7 trillion yuan. Nomura Securities set a target price of 116 yuan, implying a valuation of about 7.76 trillion yuan.
Listed and topped the charts immediately.
On July 27, $N Changxin (688825.SH)$ was officially listed on the STAR Market.
In the call auction, the highest bid reached 50 yuan per share; the stock opened at 49.5 yuan, up 471.59% from the issue price of 8.66 yuan.
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