How to Build Good AI Solutions When Data Is Scarce

Data-efficient AI techniques are emerging — and that means you don’t always need large volumes of labeled data to train AI systems based on neural networks.

Rama Ramakrishnan

November 23, 2022

Conventional wisdom holds that you need large volumes of labeled training data to unlock value from powerful AI models. For the consumer internet companies where many of today’s AI models originated, this hasn’t been difficult to obtain. But for companies in other sectors — such as industrial companies, manufacturers, health care organizations, and educational institutions — curating labeled data in sufficient volume can be significantly more challenging.

There’s good news on this front, however. Over ...