Rigorous Scientific Inductive Biases
Chris discusses the difference in inductive biases between scientific domains and human expertise, highlighting the rigorous priors and laws governing the universe that guide scientific machine learning. The conversation delves into the accuracy of Schrodinger's equation in describing the atomic world and the challenge of operating in a data-scarce regime.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Prof. Chris Bishop's NEW Deep Learning Textbook!
Related Questions
Are there biases in AI as discussed in the episode Yoshua Bengio: The Past, Present, and Future of Deep Learning and the clip General Inductive Biases?
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses as discussed in the episode AI For Good - Detecting Harmful Content at Scale // Matar Haller // #245 and the clip Model Bias Mitigation?
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses, as discussed in the episode 888: Marc Andreessen | Exploring the Power, Peril, and Potential of AI and the clip The Power of Computer Creativity?