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Apollo Chief Economist: The profit margins of the seven tech giants are rising, while the rest of the S&P companies are stagnant

The chief economist of the American asset management firm Apollo, Torsten Sløk, released five charts, believing that AI has not yet brought significant financial returns to large American companies outside of the tech giants. The per capita revenue and profit margins of the seven tech giants continue to rise; excluding them, the 493 companies in the S&P have seen these two metrics remain basically stagnant, and the data on total factor productivity in the U.S. has not shown significant signs of AI-driven growth.Apollo cited data from the corporate payment platform Ramp, stating that among its clients, the top 10% of companies by spending contributed 99.5% of the model hosting and inference costs. Among the top 1% of companies with the highest AI spending, about 80% have venture capital backgrounds; for companies at the median spending level, this ratio is only 13%. A large amount of AI computing power consumption is concentrated in a few companies, many of which rely on venture capital support.Previous statistics from Apollo indicated that during the second quarter earnings season of 2026, 69% of S&P 500 companies had disclosed that they were actually using AI, but only 2% reported metrics for ongoing tracking of effectiveness. Another NBER study updated in October this year surveyed nearly 9,000 corporate executives from seven countries, with respondents estimating that over the past three years, AI has only improved the annual growth rate of labor productivity in companies by about 0.2 percentage points.

Pump.fun adjusts the Callout reward mechanism: high-frequency releases lead to diminishing marginal returns, with rewards placing greater emphasis on content quality

Alon, co-founder of Pump.fun, stated that two months after the launch of the platform's $15 million Callout reward program, it was found that the initial mechanism inadvertently incentivized undesirable behavior, leading to a flood of low-quality content and weakening users' willingness to continuously create high-quality content.Pump.fun subsequently adjusted the reward algorithm to place greater emphasis on content quality rather than the quantity of posts. According to the new mechanism, the more Callouts a user posts each day, the lower the marginal returns from the new content. Alon mentioned that the reward mechanism is still undergoing iterations, but there is still a lot of work to be done to ensure that a large number of users can sustainably produce high-quality content over the long term.He also stated that the rewards currently cover both top accounts and accounts with fewer than 10 followers, with no favoritism or preferential treatment. Alon suggested that users focus on recommending quality tokens, building trader trust through content, and earning rewards based on the trading volume generated by their Callouts. He emphasized that simply flooding the platform with Callouts or dumping tokens to followers will not yield sustainable returns.

CryptoQuant: Short-term on-chain profit margins hit the highest since December 2024, Bitcoin may face a correction

According to a report by The Block, CryptoQuant's research director Julio Moreno pointed out that Bitcoin's closing price last week was above the 365-day moving average, confirming the start of a new bull market. However, Moreno stated that after Bitcoin reached an eight-month high of $87,400, several indicators show that upward momentum is weakening, and a market correction may follow.The report noted that the on-chain unrealized profit margin for short-term traders has risen to 33%, the highest level since December 2024. Historically, when profit margins are at similar levels, it often prompts traders to take profits. Data shows that on September 22, Bitcoin holders realized profits of 25,700 BTC in a single day, setting a record for the highest daily profit since 2026; the altcoin market also showed signs of selling pressure. The seven-day cumulative number of altcoin transactions rose to 76,000, the highest level since October 17, 2025. Meanwhile, spot demand continues to shrink, and the growth of futures demand has significantly slowed.After Bitcoin previously reached an eight-month high of around $87,400, the upward momentum has shown signs of fatigue. Julio Moreno indicated that if a correction occurs, the 365-day moving average (around $80,000) will serve as the primary support, followed by the 200-day moving average (around $71,000) and the on-chain realized price for traders (around $67,000). Provided that the support levels hold, this correction is more likely to be a healthy consolidation in a young bull market rather than a trend reversal.

first_img Zhu Xiaohu: The model API business is difficult to maintain high gross margins in the long term

Zhu Xiaohu, founding partner of Jinsha River Ventures, stated: The model API business is difficult to maintain high gross margins in the long term. Anthropic currently has a gross margin of about 60%, primarily due to the strong intelligence capabilities of the model, especially in coding scenarios where it had a significant advantage, but that advantage has begun to cross a critical point; when other models catch up, the price may only be one-tenth of its current level, making it hard to maintain a high premium. Even if it remains ahead in the next few years, if the intelligence is only 10% stronger but the price is 50% higher, users may not continue to pay. Intelligence will ultimately become more like electricity and water, and the long-term gross margin for model APIs may be between 10% and 20%. Once capabilities converge, price wars will be hard to avoid, and Anthropic's urgency to go public may also be related to the window period.Zhu Xiaohu mentioned that the AI office market is definitely much larger than AI coding. AI coding was the first to emerge because engineers have a high acceptance of AI, tasks are clear, and results are easy to verify, but it is only part of office work; the truly larger market is the white-collar market, namely AI office, which is essentially a general-purpose agent, similar to Microsoft Office. The competitiveness of AI office products lies in Model + Harness + Product + Context, and once harnesses converge, competition will shift to Context.Regarding Tencent AI, Zhu Xiaohu stated that Tencent is a latecomer, and the Hunyuan model has squeezed into the top tier domestically, with WorkBuddy becoming the leading office agent application in the domestic top tier. Jinsha River Ventures has purchased a WorkBuddy enterprise account because it uses WeChat for Work, and the organizational relationships, historical communications, as well as Tencent Meeting and Tencent Docs constitute a ready-made Context.
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