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🚨NVIDIA UNVEILS 72-GPU SUPERCHIP SET TO REVOLUTIONIZE AI Jensen Huang introduced the GB200 NVL72, a data center powerhouse packing 72 Blackwell GPUs, 1.4 exaFLOPS of compute, and 130 trillion transistors. This "superchip" enables test-time scaling, a groundbreaking approach that lets AI reason in real time, mimicking human thought. Huang...

300,346 views • 1 year ago •via X (Twitter)

11 Comments

Major's profile picture
Major1 year ago

Can I use it to mine bitcoin?

NetMind.AI's profile picture
NetMind.AI2 years ago

Get access to a wide range of GPUs like H100, A100, 4090, 3090 and save over 90% at NetMind Power. Rent Now!

Walker Seattle Ranger's profile picture
Walker Seattle Ranger1 year ago

Does it run Roblox?

N Hanh's profile picture
N Hanh1 year ago

you are scammer

NathGraty🕯️'s profile picture
NathGraty🕯️1 year ago

Don't think, just $Stupid and chill CA: 4zUDFduzd6dWisjkrS7d7VSEw3EdrV3t7KkYPznZpump

Sweden4Trump's profile picture
Sweden4Trump1 year ago

wonder if good to start inverst nvidia shares

Artur's profile picture
Artur1 year ago

Moore’s Law isn’t dead .. it just planned to moved into a really big house

Mazzagatti's profile picture
Mazzagatti1 year ago

Bros got a captain America shield with 72 4090’s on it

Kacee Allen's profile picture
Kacee Allen1 year ago

AI is going to be a major boost for all economies.

AI IA's profile picture
AI IA1 year ago

Y’all don’t know

Liberty Watch's profile picture
Liberty Watch1 year ago

Wild stuff

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NVIDIA CEO Jensen Huang says one scaling law multiplies AI faster than NVIDIA can hire engineers. Most people know three AI scaling laws. Pre-training. Post-training. Test-time. Each one multiplies intelligence by throwing more compute at a different stage. Jensen Huang says there's a fourth and it's the one that will dominate... Agentic scaling law. "During test time, that agentic system goes off and does research, bangs on databases, uses tools," Huang says. "And one of the most important things it does is spawn off a whole bunch of sub-agents." That's the multiplier. One AI worker can become a team. Then a department. Then a company. "It's so much easier to scale NVIDIA by hiring more employees than it is to scale myself," Huang says. Now imagine scaling without a payroll constraint. "The agentic scaling law — it's kind of like multiplying AI," Huang says. "We could spin off agents as fast as you want to spin off agents." Each agent spins off sub-agents. Each sub-agent spins off more. The compute requirement compounds inside a single query. And every agent generates new data, new experiences, new edge cases. "Wow, this is really good. We ought to memorize this," Huang says. "That data set comes back to pre-training." The four scaling laws don't compete. They feed each other. Agentic systems produce data, which feeds pre-training, which smartens the base model, which enables better agents, which produce more data. A flywheel that compounds forever. The companies pricing in three scaling laws are mispricing the fourth. The fourth eats the other three for lunch. P.S. Pull the thread on any story like this and you'll find the hidden incentive at the other end. As Munger said: "Show me the incentive and I'll show you the outcome." So I wrote a short book on how to spot them and design your own. Comment "INCENTIVES" and I'll send you the details. If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

GeniusThinking

92,806 views • 2 months ago

Jensen Huang just doubled NVIDIA's demand forecast to $1 Trillion through 2027 🤯 Then spent two hours explaining why that number is conservative… Here's everything today from GTC: - NemoClaw: NVIDIA's open-source enterprise AI agent stack built around OpenClaw. Jensen called OpenClaw "the operating system for personal AI" and said every company needs a strategy for it. - Space-1: NVIDIA is putting Vera Rubin data centers in orbit. Not a concept. An actual system being designed for space deployment right now. - DLSS 5: 3D-guided neural rendering that blends raw graphics with generative AI. Jensen called it the future of real-time rendering. - AWS: Deploying 1 million+ NVIDIA GPUs starting this year. Azure was the first hyperscaler to power up Vera Rubin. - Vera Rubin: NVIDIA's next-gen AI supercomputer. 10x more performance per watt than Blackwell, 700 million tokens per second, shipping later this year. - Groq 3 LPU: First chip from NVIDIA's $20B Groq acquisition. A purpose-built inference accelerator that ships Q3. NVIDIA now owns training AND inference. -Feynman: The architecture after Rubin, coming 2028. New GPU, new LPU, new CPU. NVIDIA is on a 12-month chip cadence and the treadmill never stops. - Autonomous driving: BYD, Hyundai, Nissan, and Geely building Level 4 vehicles on NVIDIA. Uber deploying NVIDIA-powered robotaxis across 28 cities by 2028. The man doubled his demand forecast to a trillion dollars, announced data centers in space, and closed the show with a robot singing country music. This is NVIDIA's world. Everyone else is just renting compute in it.

Josh Kale

45,875 views • 4 months ago