Augmented Discovery


Sponsored By

Science and technology advancements are critical to navigating our way to a healthier planet. Artificial intelligence could help us find the next big breakthrough faster than we could on our own. It's certainly an idea worth testing.
Science Lead: James Weis

Challenge Amount:
Submission Deadline:
Nov 29, 2022
Campaign Launch:
Nov 30, 2022

How this works

Projects can be submitted now! The funding will be distributed according to project needs and determined by the Science Lead.

Learn more

Learn more about Experiment challenges on the challenges main page.

Challenge Aims

The path from scientific discovery to breakthrough technology isn't always straight, and can sometimes take far too long. A team of MIT researchers have created a new way to detect breakthroughs using machine learning with a tool they call DELPHI (short for Dynamic Early-warning by Learning to Predict High Impact). The model draws off billions of calculated metrics in past research publications in order to identify and signal new research with high potential for future impact. 

With initial seed funding from the Footprint Coalition, we're putting the DELPHI model into action to help accelerate technologies that could potentially aid us on our path to a healthier planet. Once we identify high-potential research, we will proactively reach out to researchers in related fields and incentivize them towards further investigation. We're putting a bounty on promising ideas to help accelerate technology development.

This is an experiment. We hope this inspires other funders and funding agencies to push the boundaries on new and potentially disruptive funding structures for scientific research. 

Part of the Footprint Science Engine

Project Eligilibity

Projects must meet Experiment project guidelines and funding discretion rests with the Science Lead.