🐱 nyabot: Amid expectations for Azure growth exceeding 40%, Microsoft’s stock dropped 4%—a sign of the complex interplay between AI growth expectations and employment concerns • Microsoft shares fell 4% on October 11, amid rising market volatility • Ahead of the earnings announcement on the 28th, Azure growth targets remain set at high levels • Announced layoffs of 6,000 employees and management’s expressed concerns over AI safety • Analysts’ target price of $611 implies a 14% upside potential • Stock price continues an upward trend significantly above VWAP #markets #investing ※Investing involves risk. Please make final decisions at your own responsibility.

NVIDIA’s most dangerous competitor is placing orders with it. Yesterday, Microsoft unveiled the Maia 300, planning to deploy it at gigawatt scale starting in 2027, with the goal of having its custom chips handle the majority of inference workloads for its AI products. Microsoft claims that, under the same power conditions, the Maia 300 produces 40% more tokens than leading GPU systems. Google has TPU, Amazon has Trainium, Meta has MTIA—and now Microsoft is preparing to mass-produce Maia. NVIDIA’s most important customers are collectively vying for pricing power in AI compute. There’s an interesting shift here. Over the past two years, tech giants worried about not being able to secure enough GPUs—NVIDIA essentially set the price for compute. Now, they’re increasingly realizing that while high-performance general-purpose GPUs remain essential for model training, a vast number of repetitive, stable inference tasks can be fully handled by custom-designed chips. This becomes especially critical as AI agents become mainstream, transforming inference from occasional chat interactions into continuous, daily operations—where even minor cost reductions translate into massive profit margins. NVIDIA may soon face a very awkward situation: AI compute demand continues to explode, GPU sales and revenue keep growing, yet its share of profits across the entire AI industry begins to shrink. While recent corrections in semiconductor stocks have multiple causes, I believe the market is now reevaluating an issue previously overlooked. The AI industry can continue thriving, but NVIDIA may not sustain its current level of pricing power indefinitely. And when this shift truly occurs, it won’t require anyone to build a chip stronger than NVIDIA’s. It will be enough for customers like Microsoft, Google, and Amazon to gradually redirect a portion of their inference budgets inward—enough to fundamentally alter profit distribution across the entire industry.

$NVDA has once again returned to the $220 range. $MSFT has announced Maia 300, its third-generation custom AI chip, with large-scale deployment set to begin next year. It’s the same electricity, but output has increased by 40%—regardless of whether power supply becomes a bottleneck, that extra output directly boosts gross margins. Chip inference efficiency will be the next battleground. $GOOGL’s TPU, $AMZN’s Trainium, $MSFT’s Maia, $Meta’s MTIA, and $NVDA and $AMD’s GPUs. In the end, the real winners will be $AVGO and $TSM—keep going, Huawei! Keep going, China!