GTC AI Opportunity Lab
Four tools that turn a question into a plan you can act on: what AI infrastructure costs, which digital twin to build first, which NVIDIA resources fit a startup, and what architecture a project needs.
GTC AI Opportunity Lab
Four tools that turn a question into a plan you can act on. They run in your browser, need no sign-up, and say when NVIDIA technology is not needed.
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The Machine
AI Factory Efficiency Lab
Model what tokens and GPU capacity cost today, and what changes when efficiency or demand moves.
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The Mirror
Digital Twin Opportunity Lab
Find the first digital twin worth building for a factory, warehouse, city, data center or robot.
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The Makers
Startup-to-NVIDIA Match
See which NVIDIA tools and programs fit your startup, and what the published Inception criteria ask.
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Solution Architect
Build your AI technology stack
Describe what you are building and get an explainable architecture, gaps and a phased roadmap.
How the labs work
Every lab runs in your browser from published rules, with no sign-up and no AI service. Each result shows its assumptions, what would change it, and the official sources behind it, and it says plainly when NVIDIA technology is not needed. Read the methodology.
Challenge the Architect
Three fictional scenarios. Each opens the right tool with its assumptions filled in, and every answer can be changed. None of them describes a real customer.
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Illustrative scenario
A city with 10,000 cameras
Traffic, safety and privacy at city scale: what to model first, what to keep out of scope.
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Illustrative scenario
A startup building autonomous robots
Simulation, on-robot computing and the startup resources that fit an early team.
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Illustrative scenario
An AI company spending $1 million a month on inference
What a cheaper token does to the bill when demand grows, and where the break-even sits.
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