Syz the moment

Everyone’s arguing about who has the fastest chip. But that’s not the real disruption. Google isn’t trying to beat Nvidia on speed. Google is trying to beat Nvidia on economics. Here’s the overlooked truth: 1️⃣ The “Nvidia Tax” Nvidia sells to hyperscalers with 70%+ margins. AWS, Azure, and everyone else pay it, and pass it on to you. 2️⃣ Google plays a different game They’re the only hyperscaler that doesn’t need to profit from selling chips. They build TPUs at cost and control the entire stack: Chip → Interconnect → Data Center → Cloud. No margin stacking. No tax. 3️⃣ Training ≠ Inference Training = Ferrari (Nvidia dominates). Inference = Semi-truck (cheap, reliable, scaled). As AI matures, ~90% of spend shifts to inference. And here’s the bombshell: 👉 If Google drives cost-per-token toward zero with TPUs + aggressive cloud pricing… Raw speed stops mattering. Economics wins. Nvidia is selling generators. Google is building the electric grid. Cheap compute + massive distribution = 🏰 Empire. Source: Kris Patel

Nvidia says they are "delighted by Google's success" and they "continue to supply Google." They also say, "Nvidia is a generation ahead of the industry" and "offers greater performance, versatility, and fungibility." The AI wars are heating up. Source: The Kobeissi Letter

Source: Trend Spider

Source: Bourbon Capital @BourbonCap

Source: Koyfin @KoyfinCharts

Google's AI chips - TPUs, or tensor processing units - are having a moment. These semiconductors were used to train its latest genAI model, Gemini 3, which has received rave reviews, and are cheaper to use than Nvidia's offerings. 🚀 But here's the real reason Google invented the TPU Back in 2013, Google ran a simple forecast that scared everyone: If every Android user used voice search for just 3 minutes a day, Google would need to double its global data centers. Not because of videos. Not because of storage. But because AI was too expensive to run on normal chips. So Google made a bold move: 👉 Build its own AI chip - the TPU. 15 months later, it was already powering Google Maps, Photos, and Translate… long before the public even knew it existed. ⚡ Why TPUs Matter GPUs are great, but they were built for video games, not AI. TPUs were built only for AI. No extra baggage. No wasted energy. Just raw efficiency and speed. That focus paid off: TPUs deliver better performance per dollar Use less energy Are faster for many AI tasks And with each generation, Google doubles performance Even Nvidia’s CEO, Jensen Huang, openly respects Google’s TPU program. 🤔 Then why don’t more companies use TPUs? Simple: Most engineers grew up with Nvidia + CUDA, and TPUs only run on Google Cloud. Switching ecosystems is hard — even if the tech is better. ☁️ The Bigger Picture: Google’s Cloud Advantage AI is crushing cloud margins because everyone depends on Nvidia. Google isn’t. It owns the chip and the software stack. That means: ✔️ lower costs ✔️ better margins ✔️ faster innovation ✔️ and a defensible advantage competitors can’t easily copy Some experts now say TPUs are as good as or even better than Nvidia’s best chips. 🔥 The Punchline Google didn’t build TPUs to sell chips. It built them to survive its own AI growth. Today, TPUs might be Google Cloud’s biggest competitive weapon for the next decade. And the moment Google fully opens them to the world? The AI infrastructure game changes. Source: zerohedge, uncoveralpha

Source: Michael Burry Stock Tracker ♟ @burrytracker

Source: Deedy @deedydas