Machine learning models have recently found remarkable success in quantitative reasoning and in producing significant research results in specific scientific fields such as biology (e.g., with AlphaFold) and chemistry. This might be an indication that in the (near-term) future, AI models will be able to generate and/or test novel hypotheses or even produce research worthy of a Nobel prize. This project is about mapping out the current state-of-the-art of science-producing AI models. This will allow for a more comprehensive understanding of the “cognitive properties” or capabilities of the available models. The project focuses on models that generate impressive results in solving quantitative problems (e.g., Minerva) or have led to important breakthroughs and acceleration of scientific research, such as in the case of AlphaFold. The team will collect the relevant research papers, review them, and study the development of capabilities necessary for scientific reasoning in relation to AI risk and progress in alignment research.
If you're unsure whether you'd be a good fit, take the short quiz you can find on this page. Regardless, err towards applying. If you have any questions, feel free to message me.
Applications for AI Safety Camp 2023 have opened!
I'll be Research Lead for the project Machine learning for scientific discovery: the present and future of science-producing AI models.
Summary:
Machine learning models have recently found remarkable success in quantitative reasoning and in producing significant research results in specific scientific fields such as biology (e.g., with AlphaFold) and chemistry. This might be an indication that in the (near-term) future, AI models will be able to generate and/or test novel hypotheses or even produce research worthy of a Nobel prize. This project is about mapping out the current state-of-the-art of science-producing AI models. This will allow for a more comprehensive understanding of the “cognitive properties” or capabilities of the available models. The project focuses on models that generate impressive results in solving quantitative problems (e.g., Minerva) or have led to important breakthroughs and acceleration of scientific research, such as in the case of AlphaFold. The team will collect the relevant research papers, review them, and study the development of capabilities necessary for scientific reasoning in relation to AI risk and progress in alignment research.
If you're unsure whether you'd be a good fit, take the short quiz you can find on this page. Regardless, err towards applying. If you have any questions, feel free to message me.