What Are Foundation Models?

Summary: The video discusses foundation models, a cutting-edge type of AI capable of performing diverse tasks, from language translation to image generation, thanks to their training on extensive unstructured data. While they offer significant performance and productivity benefits, they also face challenges such as high computational costs and trustworthiness issues. IBM is actively working to enhance the efficiency and reliability of these models across various applications.

Keypoints:

• Foundation models are a type of AI that performs a wide range of tasks.
• They are trained on massive amounts of unstructured data.
• Fine-tuning for specific tasks can be achieved through prompting or tuning.
• Advantages of foundation models include high performance and productivity gains.
• Disadvantages include high compute costs and trustworthiness issues.
• IBM is innovating to improve the efficiency and reliability of foundation models.
• Applications being explored include language, vision, and code.
• IBM aims to make these models more trustworthy and efficient.
• Viewers are invited to follow IBM Technology on their journey.