Gemini 3's launch boosted Gemini's market share from 23% to 30%. Wild.
Source: Deedy @deedydas
Very interesting chart by Jen Zhu @jenzhuscott showing that Google has the most comprehensive stacks in AI compared to all peers/competitors.
It means they have more defensibility against the incestuous financing games that’s now the core of the “AI bubble”. She also notes that Gemini’s market share has grown rapidly from 5.6% 12 months ago to 13.7% now, mostly at the expense of ChatGPT - this was before the launch of Gemini 3. Source: The information reporting
Google went from 5% to 14% market share BEFORE Gemini 3 launch👀
WSJ: "Gemini 3’s surge past ChatGPT and other competitors on benchmark tests has handed Google an elusive victory". OpenAI/ChatGPT continues to have a massive lead but the market share has been clearly eroding. DeepSeek, Perplexity and Claude come after Gemini-. Microsoft/Copilot is barely visible on the chart. Source: Josh Wolfe @wolfejosh
The world now has 11,030 data centers:
• Americas: 4,995 • Europe: 3,476 • Asia & Oceania: 2,068 • Africa & the Middle East: 494 Source: Investing visuals @InvestingVisual, Visual Capitalist
45% of fund managers surveyed by Bank of America in November said an "AI bubble" was the biggest tail risk for markets, spiking from just 11% in September.
Over half of these investors said they think AI stocks are already in a bubble. Source: BofA
🔥 3 Bullish Signals from NVIDIA’s Earnings Call Last Night — and why the AI trade is far from over.
Most CEOs play it safe on earnings calls. Jensen Huang did the opposite. Here are the 3 comments everyone in tech, AI, and markets should pay attention to: 🚀 1. “No AI Bubble” — Just Three Structural Shifts 1️⃣ The migration from CPU ➝ accelerated computing 2️⃣ Generative AI hitting a tipping point across every workload 3️⃣ The rise of agentic AI All three require massive infrastructure builds. And the kicker? Inference demand is exploding — and is set to become a major revenue engine for NVIDIA. 💰 2. “Funding Is NOT the Problem” Worried customers are running out of capital? NVIDIA is not. Hyperscalers are already monetizing AI, sovereign buying is ramping, and agentic AI opens entirely new revenue pools. Translation: the money is there, and it's accelerating. 🧠 3. “The Ecosystem Is the Moat” This one flew under the radar but is HUGE. The CFO pointed out: A100 GPUs from SIX years ago are still fully utilized — thanks to the Kuda software stack. It means: Longer useful life for GPUs Better ROI on datacenter capex A deeper, stickier NVIDIA ecosystem Plus, NVIDIA is expanding partnerships across enterprise platforms and top AI developers. 📈 Bottom Line This was a monster print: ✔ Strong results ✔ Confident guidance ✔ Constructive multi-year outlook After-hours? NVIDIA popped ~5%, and AI-related names rallied across the board. 📊 Valuation Check (Yes, Really) NVIDIA’s stock has actually de-rated lately — earnings kept growing, the share price didn’t. And now with Q4 guidance out, investors will pivot to 2026–2027. Here’s the jaw-dropper: ➡️ Using 2027 FactSet consensus, NVIDIA trades at 21× P/E. Twenty. One. Times. Earnings. For the company powering the entire AI revolution. 🔮 The Broader Message The AI trade is alive. Healthy. And nowhere near done.
The US has 5,381 data centers — more than China (449) and every other major nation combined.
The American bet is simple: own the most compute, win the AI race. But China isn’t playing that game. Instead of chasing data center volume, China open-sourced frontier models (DeepSeek, Qwen, Baichuan) that run on cheap hardware. DeepSeek trained a frontier model for $5–6M (vs. tens of millions in the US). Inference costs are ~280x cheaper than ChatGPT. Modular data centers deploy in weeks, built around ultra-low-cost power. China isn’t scaling infrastructure. They’re scaling efficiency — and commoditizing intelligence. Meanwhile, the US is hitting a wall: the power grid. Data centers already use 6% of US electricity, headed to 11% by 2030. Spare grid capacity has fallen from 26% → 19%, on track for <15%. Some regions face 7-year waitlists just to connect new facilities. Ohio alone rejected 17 GW of new data center interconnection requests. You can build data centers. But can you power them? China can. By 2025, their installed capacity hits 3.99 TW (up 19% YoY). Renewables are nearly half of all generation. In the first five months of 2025 alone: 197 GW solar added 46 GW wind added By 2030, China is expected to have 400 GW of spare power capacity — over 3× global data center demand. The US built the most data centers. China built the power to scale whatever it wants. The real race isn’t about who has more compute today — it’s who can power their compute tomorrow. And on that dimension, China is pulling ahead. Source: StockMarket.news, Apollo
”The AI Bubble” in perspective.
What if the doomsayers are right but they have been, and they continue, miss the last +30% of the ”bubble” for their told-you-so moment? This is indeed what already happened most of this year. Source: Emre Akcakmak, Bloomberg, FT
