Leonardo DiCaprio stays under the radar while hitting Miami’s VIP party scene during Art Basel

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Marvell: Can't Compare to NVIDIA, Can't Meet Expectations, Overvaluation Gets Squeezed First?

Marvell Technology (MRVL.O) reported its Q2 FY2027 earnings (ending July 2026) after market close on August 27. Key points include: The company raised its full-year revenue outlook for FY2027 to $12 billion (from $11.5B) and for FY2028 to $18 billion (from $16.5B). However, these upward revisions were only slightly above market expectations and significantly trailed NVIDIA's recent explosive guidance. The Data Center segment, accounting for 79% of revenue, grew 19% quarter-over-quarter to $2.17 billion, primarily driven by connectivity products. For FY2028, management forecasts over 60% growth for this segment, again below NVIDIA's >70% outlook. A major disappointment for investors was the lack of an upward revision to the Custom ASIC business guidance, despite Marvell's recent partnership agreement with Google. The market had anticipated potential gains from Google's TPU orders, but the maintained guidance for "over 100% growth" in FY2028 (with no specific target for FY2027) led to concerns that the Google deal may be a less favorable "framework agreement" where Marvell holds a weaker negotiating position. Adjusted gross margin was flat at 58.3%. Q3 revenue guidance is $3.15 billion, slightly above consensus. Overall, the report was largely in line with expectations, but the subsequent stock decline is attributed to growth forecasts that failed to meet heightened market expectations (particularly versus NVIDIA) and lingering uncertainty around the tangible benefits of the Google ASIC partnership. High valuation faces near-term pressure, but expectations for >50% growth in the coming years and long-term ASIC opportunity may provide support.

marsbit31m ago

Marvell: Can't Compare to NVIDIA, Can't Meet Expectations, Overvaluation Gets Squeezed First?

marsbit31m ago

US Stock Market Trend (August 31st): Kashkari's Hawkish Remarks Weigh on Chip Stocks, US-Iran Weekend Strikes Boost Oil Prices

U.S. stock markets ended lower on Friday following hawkish remarks from Federal Reserve Chair Wash at the Jackson Hole symposium, which sharply increased the probability of a September rate hike from 35% to nearly 60%. Major indexes fell: the S&P 500 dropped 0.25%, the Nasdaq declined 0.52%, and the Dow was essentially flat. This shift in interest rate expectations pressured rate-sensitive assets, leading to significant declines in chip stocks. The Philadelphia Semiconductor Index fell 3.47%, with Nvidia dropping 4.57%, erasing about half its post-earnings gains. Geopolitical tensions also escalated over the weekend as the U.S. and Iran exchanged military strikes, raising concerns over the security of oil transit through the Strait of Hormuz. This pushed oil prices up over 2% in early Asian trading on Monday, reintroducing a geopolitical risk premium. In other energy news, former President Trump announced a landmark 25-year oil deal with Venezuela, aiming to significantly increase the country's oil production. However, this long-term supply boost was overshadowed in the short term by the Middle East conflict and the dominant market focus on interest rates. The core market narrative for the coming week revolves around the interplay between re-priced hawkish rate expectations and escalating geopolitical risks. Key areas to watch include the trajectory of Treasury yields, the evolution of U.S.-Iran tensions and its impact on oil prices, and whether the sell-off in high-valuation tech and semiconductor stocks stabilizes or continues under the pressure of higher rates.

marsbit47m ago

US Stock Market Trend (August 31st): Kashkari's Hawkish Remarks Weigh on Chip Stocks, US-Iran Weekend Strikes Boost Oil Prices

marsbit47m ago

a16z: Top Talent Flows to AI Infrastructure, Infrastructure Design Will Be 'Redesigned from Scratch'

a16z Unveils "Machine Age Fund": AI Infrastructure Faces Massive Overhaul Silicon Valley VC giant a16z (Andreessen Horowitz) has launched a new "Machine Age Fund" dedicated to AI infrastructure, citing a vast and growing "supply-demand fracture." Key takeaways: * **Unlimited Demand vs. Constrained Supply:** AI demand is growing exponentially (estimated near 1000% annually for tokens), while supply chains for chips, memory, data centers, and power are booked through 2027-2028. GPU prices are rising against historical trends. * **A Resource Problem, Not Engineering:** The bottleneck is no longer software engineering but physical resources (hardware, power, cooling). Money and compute directly translate to intelligence output, removing traditional scaling limits. * **Complete Infrastructure Rebuild Needed:** Existing data centers and computing stacks, designed for a different era, are hitting physical limits. Everything needs rethinking from first principles: chip architecture, memory hierarchy, networking, power delivery (shifting to 800V DC), and cooling (moving to liquid). * **Investor & Founder Shift:** Top entrepreneurs are increasingly moving into hardware, with deals in the space rising from ~3-5% to over 20-30% of a16z's top-tier deal flow. Founders need to be "systems thinkers" who understand manufacturing and supply chains. * **Massive Economic Scale:** Training a frontier model now costs $3-5B. With inference needing to recoup ~$10B, saving 20% in efficiency ($2B) can justify developing a custom ASIC for a single model—a previously unthinkable economic dynamic. * **Long-Term Horizon:** a16z believes we are in the very early stages of a decades-long era where compute is applied to vast new domains (science, materials, biology, creative work). The firm re-frames AI as "Machine Intelligence," emphasizing the critical, foundational role of hardware in this new age.

marsbit1h ago

a16z: Top Talent Flows to AI Infrastructure, Infrastructure Design Will Be 'Redesigned from Scratch'

marsbit1h ago

OpenAI Buys Tens of Thousands of Macs for Reinforcement Training! NVIDIA's Job Gets Snatched by Apple

OpenAI is reported to have purchased tens of thousands of Mac mini and Mac Studio computers for reinforcement learning tasks, specifically to train "computer-use agents." This surge in demand from AI companies like Anthropic as well has made Mac Apple's fastest-growing product line. Apple is promoting its hardware's suitability for local AI processing, highlighting advantages like the unified memory architecture of M-series chips and robust cooling in desktop Macs. However, this unexpected enterprise demand has led to supply shortages for high-end configurations. Nvidia has taken notice, launching its DGX Spark desktop AI computer as a direct competitor. While Apple has begun building internal servers with its chips for AI tasks, it currently does not sell them, relying instead on partners to expand its enterprise reach.

marsbit1h ago

OpenAI Buys Tens of Thousands of Macs for Reinforcement Training! NVIDIA's Job Gets Snatched by Apple

marsbit1h ago

ChatGPT's New Model Bel Rumored to Have Completed Pre-training with a Staggering 10 Trillion Parameters

ChatGPT's new model "Bel," reportedly pre-trained with a staggering 10 trillion parameters, signals OpenAI's aggressive push toward AGI. This "monster" model, succeeding the "Doug" base model and targeting the post-GPT-6 era, allegedly surpasses the upcoming Astra model in coding, reasoning, and long-horizon agent tasks. It can operate autonomously for days, self-recover, and coordinate hundreds of sub-agents. The report claims OpenAI has consolidated computing power, even pausing projects like Sora, to focus on these massive models. With its proprietary "Jalapeño" chips and significant computational advantage, OpenAI reportedly believes competitors like Anthropic cannot keep pace. Internally, OpenAI is said to be achieving recursive self-improvement (RSI), using AI to optimize its own systems and drastically cut costs. Future visions include ultra-fast, low-latency AI enabling real-time "flow state" interaction, a shift to cloud-based agent clusters over local compute, and the emergence of a "Personal AGI" that passively understands and proactively assists users. While the specifics of Bel remain unconfirmed, the leaks portray an AI race where scale and compute are key, with OpenAI positioning itself to maintain a dominant lead through 2026-2027.

marsbit1h ago

ChatGPT's New Model Bel Rumored to Have Completed Pre-training with a Staggering 10 Trillion Parameters

marsbit1h ago

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