A new funding opportunity from the Advanced Manufacturing Office, U.S. Department of Energy, incudes a subtopic on Atomically Precise Manufacturing
New Funding Opportunity from U.S. DOE

A new funding opportunity from the Advanced Manufacturing Office, U.S. Department of Energy, incudes a subtopic on Atomically Precise Manufacturing
Longtime Foresight member Dave Forrest is leading DOE’s Advanced Manufacturing Office in advocating atomically precise manufacturing to transform the U.S. manufacturing base.
Sir J. Fraser Stoddart, winner of 2007 Foresight Feynman Prize for Experiment, shares the 2016 Chemistry Nobel for the design and synthesis of molecular machines.
Christine Peterson will speak on “High-Leverage Altruism” at the fourth annual conference of Effective Altruism, using reason and evidence to improve the world as much as possible, and on nanotechnology at the Singularity University Global Summit, the definitive gathering for those who understand the critical importance of exponential technologies.
Foresight President Julia Bossmann will speak on AI at the TEDxEchoPark “Paradigm Shift” event on Saturday May 14, 2016, in Los Angeles, California.
Prof. William Goddard presented four advances from his research group that enable going from first principles quantum mechanics calculations to realistic nanosystems of interest with millions or billions of atoms.
Prof. Gerhard Klimeck described the success of nanoHUB.org, a science and engineering gateway providing online simulations through a web browser for nanotechnology research and education.
Prof. Art Olson discussed how we understand what we cannot see directly, how we integrate data from different sources, and how to develop software tools to move forward.
Dr. Alex Wissner-Gross surveyed the interplay between programmability of bits and atoms in the development of technology, asking how the recent successes with programming bits can help nanotechnology progress in programming atoms.
Modeling DNA strand displacement cascades according to three simple rules can in principle mimic the temporal dynamics of any other chemical system, presenting a method to model regulatory networks even more complicated than those of biology.