Our CEO Jensen Huang explains why AI can take on routine tasks, boost productivity, and help people focus on more meaningful work.

📈 NVIDIA tops AI leaderboards and benchmarks with open models driven by extreme co-design across compute, networking, memory, storage, and software.This includes models for biology, AI physics, agentic AI, physical AI, robotics, and autonomous vehicles.By being vertically integrated and horizontally open, NVIDIA enables its ecosystem to scale agentic workflows at every layer of the stack with the lowest cost per token.

Don't miss the livestream of NVIDIA CEO Jensen Huang's keynote at #NVIDIAGTC Taipei.Hear Jensen unveil the breakthroughs in physical AI, scaling infrastructure, science, and more — and what's driving the next generation of AI. It all starts here.📍 Monday, June 1 | 11 a.m. Taipei Time📍 Sunday, May 31 | 8 p.m. Pacific Time🎥 Tune in for one of the biggest moments of GTC:

Nvidia will now pay you to put a mini AI data center on your houseIt looks like a normal AC unit in the yard.But inside sits 16 Nvidia Blackwell GPUs and Dell servers.A startup called Span builds them, backed by Nvidia.They bolt onto your home and you get paid for the power and Wi-Fi.Some estimates put that around $1,000 a month in your pocket.That is rent money just for hosting a box outside.Span says it deploys way faster and cheaper than a real data center.The AI boom is literally moving into

Everyone’s watching what comes next.Start with the NVIDIA GTC Live pregame show at COMPUTEX 2026.Then watch Jensen Huang take the stage in Taipei to unveil the latest breakthroughs in AI and accelerated computing.Tune in: https://t.co/fDljCHv7sO📍 Monday, June 1 | 9 a.m. Taipei Time📍 Sunday, May 31 | 6 p.m. Pacific Time#NVIDIAGTC

NVIDIA MADE A $249 DESK CHIP THAT TURNS LOCAL LLMS INTO A TINY PRIVATE BACKENDjetson orin nano super is basically a pocket-size ai board: 67 TOPS, 1024-core ampere gpu, 8gb memory, 7-25w power draw. not a gaming pc, not a rented cloud box, just a small nvidia dev kit running llama, mistral, qwen and deepseek from your own tablethat changes the cost structure. the same automations people casually run through openai for $100-200/month can move the boring work local: summaries, drafts, code checks,