NC unit secretary
2020-10-11 14:27:58

This is a discussion channel for “Nobel Turing Challenge : A Grand Challenge on AI for Scientific Discovery” by Prof. Hiroaki Kitano (Okinawa Institute of Science and Technology).  A link to the talk is the following. Please do not share the link to anyone outside of this slack workspace. Access Pass code can be found at the announcement channel.   URL: https://vimeo.com/471291070 (34 minutes)

👏 Taiki Miyagawa
Hiroaki Kitano
2020-10-11 15:12:19

A longer version of the slide

Nobel-Turing-2020.pdf
Hiroaki Kitano
2020-10-11 15:16:52

https://www.iva.se/en/tidigare-event/the-nobel-turing-challenge--when-will-the-first-nobel-prize-be-awarded-for-ai/ A longer version of the talk at Royal Swedish Academy of Engineering Sciences back in 2017.

iva.se
The Nobel Turing Challenge – When will the first Nobel Prize be awarded for AI?
The focus of the Nobel Turing Challenge is to develop AI systems with the ability to make scientific discoveries that are worthy of a Nobel Prize. This would also give us deeper insights into and perhaps redefine the scientific processes.
Original URL: https://www.iva.se/en/tidigare-event/the-nobel-turing-challenge--when-will-the-first-nobel-prize-be-awarded-for-ai/
Hiroaki Kitano
2020-10-11 15:20:03

A Japanese paper published in 人工知能　from Japanese Society for Artificial Intelligence

JSAI-Scientific-Discovery-2016-Kitano.pdf
Hiroaki Kitano
2020-10-11 15:21:42

I will be giving a talk tonight as well. https://www.thoughtworks.com/engineering-research-symposium

thoughtworks.com
E4R Symposium 2020 | AI for Nobel Prize?
ThoughtWorks Engineering for Research (E4R) Symposium brings together scientists, academicians and engineers to discuss the role of computer science in accelerating scientific exploration.
Original URL: https://www.thoughtworks.com/engineering-research-symposium
Hiroaki Kitano
2020-10-11 16:19:36

an example of recent outcome from my team on knowledge extraction and hypothesis generation that have not mentioned in my video. IEEE Transactions on Knowledge & Data Engineering, vol. , no. 01, pp. 1-1, 5555. doi: 10.1109/TKDE.2020.3017687, url: https://doi.ieeecomputersociety.org/10.1109/TKDE.2020.3017687

Mark Foley
2020-10-14 11:35:23

Interesting talk, thank you. Some discoveries can come from 'inspiration' from totally unrelated areas. For example, I could be looking at a tree, and that gives me a breakthrough of "Ah, maybe that's similar to the unknown structure in my sample". So inspiration from outside the 'Scientific truths circle'. Maybe could give the AI random images to use as hints to describe the unknown experimental phenomena.