Interactive hypothesis generation

Interactive hypothesis generation accelerates scientific discovery by using AI to propose and refine hypotheses in real-time.

This technology empowers researchers to navigate complex datasets with unprecedented speed. For example, IBM Research has demonstrated its utility in materials science, where an AI system called 'Sherlock' (Hypothesis Generation and Ranking) rapidly sifts through vast scientific literature and experimental data to suggest novel material compositions for specific applications. Users can then interactively refine these hypotheses, guiding the AI toward more promising avenues and significantly reducing the time from data to discovery. This iterative human-AI collaboration streamlines the scientific method, enabling faster breakthroughs across diverse fields.

https://www.ibm.com/blogs/research/2023/11/interactive-hypothesis-generation/