𝗠𝗼𝗼𝗿𝗲’𝘀 𝗟𝗮𝘄 𝗶𝘀 𝗗𝗲𝗮𝗱. 𝗪𝗲𝗹𝗰𝗼𝗺𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗔𝗴𝗲 𝗼𝗳 𝗛𝘆𝗽𝗲𝗿 𝗠𝗼𝗼𝗿𝗲’𝘀 𝗟𝗮𝘄!

In just eight years, NVIDIA has achieved a 1000x increase in computational power—leapfrogging the performance gains once defined by Moore’s Law.

In a recent interview on 'No Priors', Jensen Huang shared Nvidia’s key strategic priorities, revealing an exciting path for transformative AI. Here are the key takeaways:

No Priors Ep. 89 | With NVIDIA CEO Jensen Huang Link

1. Moving Beyond Moore’s Law by Co-Designing Hardware and Software

Nvidia is targeting 2-3x performance gains each year—not just on individual chips but at scale—while reducing costs and energy by similar factors. This is made possible by co-designing both hardware and software, allowing Nvidia to break through traditional limits on speed and efficiency.

2. Flexible Infrastructure for Training and Inference

Nvidia’s adaptable infrastructure seamlessly switches between training large models and running them in real-time (inference). This flexibility maximizes efficiency and makes AI more accessible across industries.

3. AI Factories that generate tokens of value

Jensen described treating traditional data centers as “AI factories.” These aren’t meant for just storing data; they’re producing intelligence. AI factories generate "tokens" — the building blocks for language models, robotics instructions, synthetic molecules, and more. Every industry will need its own intelligence generator.

4. "Data Center as a Product" Approach

Nvidia now builds entire data centers with compute, networking, cooling, and optimized software, delivering real-world performance that matches its promises. This “data center as a product” approach makes Nvidia’s tech scalable and customizable, sold as modular components that integrate seamlessly into diverse environments.

5. AI-Driven Chip Design to drive impact internally at Nvidia

AI isn’t just a tool at Nvidia—it’s a collaborator. AI-driven chip design allows Nvidia to explore more complex possibilities and optimize chips in ways that human engineers alone couldn’t. This virtuous cycle of AI designing for AI amplifies innovation.

6. The Future: AI Employees & Robotics

Jensen envisions a future workforce with “AI employees”—intelligent agents specialized in tasks like marketing, supply chain, and design. These aren’t mere assistants; they’re autonomous and capable, expanding the possibilities of AI to physical robots as well.

The image was created with Midjourney, showing a futuristic AI factory/ data center. A robot designing a chip.