Evolution of Inductive Bias in Neural Nets

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.

This episode features Technical Fellow Christopher Bishop, who leads a global team of researchers and engineers working to help accelerate scientific discovery by merging machine learning and the natural sciences. Llorens and Bishop explore the state of deep learning; Bishop’s new textbook Deep Learning: Foundations and Concepts, his third and a writing collaboration with his son; and a potential future in which “super copilots” accessible via natural language and drawing on a variety of tools, like those that can simulate the fundamental equations of nature, are empowering scientists in their pursuit of breakthrough.

Learn more:

• Deep Learning: Foundations and Concepts | Textbook, 2023
• Pattern Recognition and Machine Learning | Textbook, 2006
• Neural Networks for Pattern Recognition | Textbook, 1995