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Serenity: OpenAI and Anthropic extensively use Apple Mac devices, making Apple an unexpected beneficiary of AI infrastructure

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Serenity published a post stating that OpenAI is stockpiling tens of thousands of Apple Mac mini and Mac Studio units for reinforcement learning tasks. Anthropic, meanwhile, is renting Apple Mac minis from Amazon to carry out similar AI work. Serenity quipped that Apple appears to have "accidentally become a major winner of the AI boom without taking any direct action". Additionally, on August 27, Anthropic partnered with Raspberry Pi to launch a new model hardware standard. No information has yet emerged indicating that either Anthropic or OpenAI is purchasing Raspberry Pi devices for similar tasks.

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Perspective: August CPI will be a make-or-break factor for the September interest rate decision, as the Federal Reserve’s hawkish rhetoric has surged sharply.

Wall Street's so-called "Fed Whisperer" Nick Timiraos said that Fed Chair Walsh delivered clear hawkish signals at last week's annual global central bank conference, noting that current financial conditions are hardly restrictive, and recent improvements in inflation are insufficient to prove underlying price pressures have materially eased. As a result, markets have lifted their expectations for a September rate hike by the Fed, with some institutions even forecasting one rate hike each in September and December this year. Timiraos pointed out that the August CPI data, set to be released on September 11, will be a key determinant of the Fed's September policy path. If inflation continues to cool, the Fed may have reason to hold interest rates steady; however, if CPI rebounds sharply, Walsh will face greater policy pressure, and keeping rates unchanged would be hard to justify. Meanwhile, the hawk-dove divide within the Fed has intensified. Three officials dissented at the last FOMC meeting, while other officials openly supported rate hikes. Markets are currently closely monitoring inflation data, as well as whether tariffs, Middle East tensions and the AI investment boom will further fuel price pressures.

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Pons cumulative trading volume surpasses $4 billion, trading activity in the Robinhood Chain ecosystem continues to heat up.

Official announcement from Pons: Its cumulative trading volume has surpassed $4 billion. The platform’s native token, PONS, has reached a market capitalization of $331 million, with a 24-hour trading volume exceeding $66 million. Pons has now emerged as one of the most active trading and launch platforms in the Robinhood Chain ecosystem, with market interest continuing to grow.

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US stock momentum trading faces 'collective backlash': S&P 500 Momentum Index set to notch its worst quarterly performance in 25 years.

Amid sharp swings in AI-related stocks and intensifying short covering, Wall Street’s long-popular "buy strong, sell weak" momentum strategy is facing a sharp reversal. Data shows that since July 1, the S&P 500 Momentum Index has fallen more than 9%, while the S&P 500 Index has risen about 2.8% over the same period, pushing the momentum index toward its worst quarterly performance in 25 years. In the second quarter of this year, the S&P 500 Momentum Index surged 44%, marking its best quarterly performance on record, with a cumulative gain of 133% over the past five years, and was once one of the most crowded trading strategies among institutional investors. But entering the second half of the year, some stocks that had been heavily shorted suddenly rebounded, triggering large-scale liquidation by quantitative funds and short covering. Data from Bank of America shows that momentum trading in July this year posted the second-worst performance in nearly 40 years, second only to the 2009 financial crisis period. Goldman Sachs data shows that August 19 was one of the worst trading days for systematic long-short funds in nearly two years, with about half of losses stemming from the failure of momentum strategies. Meanwhile, net short positions held by Nasdaq 100 futures speculators have risen to near 20-year highs. Market analysts warn that while the broader U.S. stock market is still rising, AI overvaluation, surging capital expenditures by tech giants, and crowded momentum trades are exposing the market to a higher risk of sudden reversals.

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Generating faster than playback: MiniMax H3 Max Live transforms AI videos into infinite live streams, where bullet comments can alter the plot in seconds.

Beating AI News Brief (Dongcha): AI inference platform fal engineer Rehan Sheikh has integrated H3 Max directly with Twitch. Since the model generates videos faster than viewers can stream them, the live broadcast can run while generating subsequent frames in the background, enabling theoretically endless streams. Sheikh dubbed this "Infinite Cross-Dimensional TV". MiniMax’s official account reposted the experiment, and fal later launched the H3 Max Live experiment. The live content is not pre-generated: viewers can input !prompt directly in Twitch chat. fal stated new requests appear on screen in seconds, with every scene shaped by chat input. There is no fixed script or runtime; as long as generation continues, the show runs indefinitely. The biggest hurdle for this use case was generation speed: if a 15-second video required minutes of wait time for the next segment, true live streaming was impossible. H3 Max has cut that wait time to under playback time, letting the AI prepare the next segment while viewers watch the current one. This marks the first time a video model has shifted from "waiting for output" to delivering continuous real-time content. H3 Max is a version trained by fal Research based on MiniMax’s open-source H3, optimized for fal’s inference system. Official metrics show it generates a 5-second video in under 3 seconds, with throughput ~35 times that of MiniMax’s official H3 API. Currently, in Artificial Analysis’s audio-inclusive leaderboard, its image-to-video model ranks first with 1202 Elo, while its text-to-video model ranks third with 1235 Elo, trailing only Wan 3.0 and Gemini Omni Flash.

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Tom Lee: Four Key Catalysts Could Trigger Ethereum (ETH) Rally; If Bitcoin (BTC) Rises to $150,000 and ETH/BTC Returns to 0.04, ETH Could Reach $6,000

Bitmine Chairman Tom Lee recently told the Milk Road Show in an interview that asset tokenization and AI agent finance will be the core narratives driving the crypto market over the next five years. Ethereum is poised to become the underlying settlement layer of the global financial system, and ETH remains severely undervalued relative to BTC. Lee projects ETH could be boosted by four key catalysts in the remainder of 2026: the U.S. Clarity Act is expected to pass in September, over-the-counter short positions and sidelined funds returning to the market, Asian funds reallocating to crypto assets, and global institutional fund managers chasing top-performing crypto assets amid quarterly performance pressures. He forecasts the ETH/BTC exchange rate will retest its historical high of 0.08. Even a conservative recovery to 0.04 would put ETH at $6,000 if BTC hits $150,000. Lee also stressed Bitcoin still has long-term upside, but the crypto industry’s bigger overarching trends over the next five years will be the "full asset tokenization super cycle" and "AI agent finance".

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Wintermute’s short positions on Hyperliquid turned profitable, with unrealized profits reaching $1.73 million.

According to monitoring by Onchain Lens, as the broader crypto market corrects, Wintermute’s large short positions previously established on Hyperliquid have returned to profitability. Currently, the firm holds roughly $149.2 million in short positions, with only about $5.01 million in long positions, translating to an overall unrealized profit and loss (PnL) of approximately $1.73 million. Specifically, Wintermute’s short positions include around $58.36 million in ETH, $26.11 million in SOL, and $19.16 million in BTC. Data shows its current portfolio remains highly skewed toward a bearish structure.

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