Data Acquisition Over Parameter Count for AI? | Mustafa Suleyman

High-Quality Data beats Parameter Count.

Constantly chasing larger models is futile.

Instead, the moat lies in data acquisition.

As an AI founder, you need to look for existing labeled datasets or, even better, design a UI that inherently collects data from user interactions.

This will help you:

1. Create defensibility with high-quality, proprietary data, and

2. Eliminate the need for you to depend on large-scale model providers

In this episode of Product-Led AI, I’m joined by Mustafa Suleyman of Microsoft, who clarifies why founders need to focus on data acquisition and filtering over parameter count.