Exploring the Limitations of AI Models

This chapter examines the constraints of neural networks and specifically GPT-3 in real-world applications, emphasizing their reliance on familiar data and the challenges faced when generalizing to new scenarios. The speakers critique the interpretability of these models and stress the importance of a multifaceted approach to AI that considers cognitive strategies beyond deep learning. They also highlight the unexpected performance of GPT-3 in creative tasks, contrasting it with its shortcomings in structured tasks and the implications of data processing in AI development.