AI4SCIENCE AND NOBEL TURING Challenge INITIATIVE CONFERENCE

The Joint AI for Science and Nobel Turing Challenge Conference represents an assembly of world leaders globally, to envision an ambitious convergence aimed at harnessing the potential of artificial intelligence to revolutionize the scientific discovery process. This conference is designed to foster collaboration and innovation at the intersection of ‘AI for Science’ development and the vision of the Nobel Turing Challenge, which seeks to develop autonomous systems capable of making groundbreaking scientific discoveries. By integrating AI's capabilities in data analysis, hypothesis generation, and experimental automation, the conference endeavors to pave the way for AI-driven advancements that could merit Nobel Prize recognition. 

The conference will feature a comprehensive agenda that includes keynote speeches from renowned leaders in the fields of AI and scientific research, panel discussions on the integration of AI technologies in science, and breakout sessions focused on specific challenges such as knowledge extraction from scientific literature, representation of scientific knowledge, mathematical and methods’ advancements in the pursuit of scientific discovery and the automation of experiments. A special emphasis will be placed on the development of closed-loop systems that facilitate the seamless transition from data acquisition to knowledge generation and verification, including in-silico emulator development in various fields, data, standards and benchmarks and grand challenges in various domains.

Scheduled to take place in Singapore on 23rd and 24th July 2024, the conference will offer participants the opportunity to engage with the world leaders, fostering a global dialogue on the future of scientific discovery. Interactive sessions will allow for deep dives into current advancements, potential high-impact targets, and the roadmap for AI in science. The conference aims not only to highlight current achievements and challenges but also to formulate a collaborative strategy for future research, with the ultimate goal of establishing a more expansive and inclusive forum for ongoing dialogue in this transformative field.

A list of possible topics includes, but is not limited to:

·  Integration of AI with scientific methodologies for breakthrough discoveries

·  Challenges and solutions in developing autonomous AI systems for science

·  Advances in knowledge extraction and processing from scientific publications

·  Techniques for the accurate representation of complex scientific knowledge

·  Strategies for automating hypothesis generation and verification processes

·  Role of AI in the automation of scientific experiments and data collection

·  Development of model-based active learning for uncovering latent structures

·  Utilizing AI for generating and evaluating reasoning in scientific hypotheses

·  Cross-disciplinary collaborations for enhancing AI's impact on science

·  Development of robust, interpretable, energy-efficient and scalable AI systems for scientific research

·  Overcoming data quality and accessibility challenges in scientific AI applications

·  The potential of AI in untapped areas of scientific research

Organizing committee:

Assoc Prof Kedar Hippalgaonkar (Nanyang Technological University and IMRE, A*STAR)

Prof Yang Zhang (National University of Singapore)

Prof Hiroaki Kitano (Sony AI and The Systems Biology Institute, Japan)

Prof Jun Seita (RIKEN, Japan)