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AI Chips & No-Code Revolution: Nvidia $5T, Copilot App Builder, Synthetic Data Boom – Oct 28–29, 2025

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1. Nvidia Hits $5 Trillion: 20 Million Blackwell Chips Ordered Through 2026On October 29, 2025, Nvidia became the first company to cross $5 trillion market cap – fueled by 20 million Blackwell chip orders locked in through 2026, 5x the prior generation. The surge reflects AI's "new oil" status, with demand outstripping supply by 3:1.Case from Taiwan: A TSMC fab in Hsinchu (Nvidia’s primary partner) ramped Blackwell B200 production from 50K to 500K units/month in Q3 2025. Engineers reported 30% yield improvement using AI-driven defect prediction – a breakthrough enabled by Nvidia’s own CUDA tools. Metric H100 (2024) Blackwell B200 (2025) FP8 TFLOPS 4,000 20,000 Memory 80GB HBM3 192GB HBM3e Power 700W 1,000W Orders 4M 20M Chiêu 2: Bảng so sánh – Schema-eligible.US-China supply race: Silicon Valley data centers (Google, Meta) pre-ordered 60% of supply, while Shenzhen hyperscalers (Tencent, ByteDance) secured 25% via long-term contracts. This leaves indie US labs scrambling f...

AI November 2025: 3 Breakthroughs – Veo 3.1 Goes Pro, DeepSeek R-1, xAI Grok 4

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1. Google Veo 3.1 Pro: The First 4K Real-Time Audio Video Model – Silicon Valley Just Killed the $50K Ad Budget On November 15, 2025, Google DeepMind silently dropped Veo 3.1 Pro , a model so advanced it renders traditional video production agencies obsolete in under seven minutes. This is not an incremental upgrade. This is a category collapse . Veo 3.1 Pro generates 4K resolution, 120-second cinematic videos with real-time lip-sync audio, multi-character dialogue, physics-aware motion, and full cinematic camera control — all from a single text prompt. You can type: "A dolly zoom on a female founder in a San Francisco loft while a male investor reacts in shock, with ambient city sounds and a Hans Zimmer-style score" — and get a broadcast-ready clip in 180 seconds. The technical leap is staggering. Veo 3.1 Pro integrates three previously separate diffusion pipelines — visual, motion, and audio — into a single unified latent space . It uses Flow Matching 2.0 (a Google inve...

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