The 1st Workshop on Nobel Turing Challenge
Date
Location
Description
Title
Workshop on Nobel Turing Challenge
Abstract
The Nobel Turing Challenge is a grand challenge aiming at developing a highly autonomous AI and robotics system that can make major scientific discoveries, some which may be worthy of the Nobel Prize and even beyond. Accomplishing this challenge requires a development of a series of technologies and in-depth understanding on the process of scientific discoveries. From the system development perspective the challenge is to make a closed-loop system from knowledge acquisition and hypothesis generation and verification to full automation of experiments and data analytics.
This series of workshops aims to discuss a process of scientific discovery and how AI can make it happen highly autonomously to yield high impact discoveries. The first workshop will focus on sharing the current status of the field, and discuss what are possible high impact targets.
Vast scientific knowledge is recorded in publications described using natural language that is at best informal and less precise form of communication. The process of how knowledge can be acquired from publications, databases, and other sources and how hypotheses can be generated and tested. Not only does it lack precision due to the inherent nature of human language behaviors, it may contain errors, fabrications, and other issues that undermine the integrity of the body of knowledge. A series of challenges is envisioned that are:
Extraction of knowledge from a body of publications
Accuracy evaluation and maintenance of integrity while allowing options for revision
Generation of hypotheses from the body of knowledge
Generation of reasoning to support and refute generated hypothesis
Formation of potentially multiple self-consistent system of knowledge that can be resolved by specific series of tests
On the automation front, development of fully connected laboratory and data analysis pipelines are essential. How can this be linked with hypothesis generation? How automation of experiments improve precision of the experiments, as well as accelerate the speed of discoveries? How can we combine a variety of experimental devices and enable flexible protocol generation and execution.?
This is not just automation of laboratories. It is the automation of science.
This workshop is designed to be a small and intense forum of those who have a vision and experiences on the related subjects. We are expecting that this workshop will be the stepping stone for creation of the larger and more comprehensive forum of the field.
Date
21st and 22nd, April 2022
Registration
Registration is required to attend this event. Registration for participation Deadline:20th April 2022
Please register from below link. After you register, the zoom link to join this workshop will be informed by email.
Register
https://oist.zoom.us/meeting/register/tJ0sdO6gqzktH93skRikJR8zQHj1v97La5N_
If you need technical assistance for Zoom operation, the operation committee will assist you individually. Please inform us in advance at iosu-workshop@oist.jp
Workshop Program
Day 1: April 21st (scheduled time in JST)
19:00 - 19:10 | Opening and housekeeping | ||
19:10 - 19:35 (19:40) | Opening Keynote The Vision and Strategy Behind the Nobel Turing Challenge Prof. Hiroaki Kitano, The Systems Biology Institute, OIST |
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19:40 - 20:05 (20:10) | Recent Progress in Robot Scientist Prof. Ross King, Chalmers University of Technology |
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20:10 - 20:35 (20:40) | Deep Reinforcement Learning, Knowledge Discovery, and Intelligence Measure Dr. Shane Gu, Google Brain |
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20:40 - 21:05 (21:10) | Towards Autonomous Robot Lab and The Levels of Autonomy of Scientific AI Dr. Koichi Takahashi, RIKEN |
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21:10 - 21:20 | Break | ||
21:20 - 21:45 (21:50) | Automated Science Approaches to Complex Biomedical Problems Prof. Robert Murphy, Carnegie Mellon University |
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21:50 - 22:15 (22:20) | Self-driving Lab towards Autonomous Discovery of Materials Dr. Xenofon Evangelopoulos, The University of Liverpool |
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22:20 - 23:00 | Wrap up |
Day2: April 22nd (scheduled time in JST)
19:00 - 19:10 | Opening and housekeeping | ||
19:10 - 19:35 (19:40) | Taxila: Towards Platforms for Leveraging and Advancing Research on Hypothesis Generation from Text Dr. Sucheendra Kumar Palaniappan, The Systems Biology Institute |
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19:40 - 20:05 (20:10) | Generating Hypotheses from Large-scale Biomedical Text Dr. Uchenna Akujuobi, Sony AI |
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20:10 - 20:35 (20:40) | Large-scale Knowledge Assembly for Hypothesis Generation and Human-machine Interaction Prof. Benjamin M. Gyori, Harvard Medical School |
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20:40 - 21:00 | Break | ||
21:00 - 21:25 (21:30) | Human-like Representations and Reasoning for AI-driven Science Prof. Kenneth D. Forbus, Northwestern University |
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21:30 - 21:55 (22:00) | Achieving Productive Aging: The Quest to Understand the Mechanism of Aging and Longevity in Mammals Prof. Shin-ichiro Imai, Washington University in St. Louis, School of Medicine |
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22:00 - 23:00 | Wrap up discussions or more talks |
Speakers
Prof. Hiroaki Kitano |
The Systems Biology Institute, OIST |
The Vision and Strategy Behind the Nobel Turing Challenge |
|
Prof. Ross King |
Chalmers University of Technology |
Recent Progress in Robot Scientist | |
Dr. Shane Gu | Google Brain | Deep Reinforcement Learning, Knowledge Discovery, and Intelligence Measure | |
Dr. Koichi Takahashi | RIKEN | Towards Autonomous Robot Lab and The Levels of Autonomy of Scientific AI | |
Prof. Robert Murphy | Carnegie Mellon University | Automated Science Approaches to Complex Biomedical Problems | |
Dr. Xenofon Evangelopoulos | The University of Liverpool | Self-driving Lab towards Autonomous Discovery of Materials | |
Dr. Sucheendra Kumar Palaniappan | The Systems Biology Institute | Taxila: Towards Platforms for Leveraging and Advancing Research on Hypothesis Generation from Text, | |
Dr. Uchenna Akujuobi | Sony AI | Generating Hypotheses from Large-scale Biomedical Text | |
Prof. Benjamin M. Gyori |
Harvard Medical School |
Large-scale Knowledge Assembly for Hypothesis Generation and Human-machine Interaction | |
Prof. Kenneth D. Forbus | Northwestern University | Human-like Representations and Reasoning for AI-driven Science | |
Prof. Shin-ichiro Imai | Washington University in St. Louis, School of Medicine | Achieving Productive Aging: The Quest to Understand the Mechanism of Aging and Longevity in Mammals |
The 1st Workshop on Nobel Turing Challenge is jointly organized by The Systems Biology Institute (SBI) and Okinawa Institute of Science and Technology Graduate University (OIST).
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