| https://www.linkedin.com/in/benblaiszik |
🛫 A new generation of scientific understanding and #AI is on the horizon with the Exascale Aurora system. Very nice article profiling the efforts of Rick Stevens, Michael Papka, and the Argonne Leadership Computing Facility team.
“You’ve got a community of people that have been working on advancing high-performance computing for decades. And it powers the whole economy.” - Rick Stevens
Article: https://lnkd.in/g2s3w-U5
January 2023 #ML and #AI for Science developments including: 🔹 ML for polymeric drug formulation; 🔸A new Recursion RXRX dataset; 🔹The Year of #OpenScience @WHOSTP; 🔸AI to understand reaction mechanisms; 🔹10 yrs of battery testing data.
Let's go 🚀
LinkedIn Thread: https://www.linkedin.com/posts/benblaiszik_ml-ai-openscience-activity-7026259777672421376-XHPN?utm_source=share&utm_medium=member_desktop
Research automation is an emerging way to connect #ExaScale computing, #ML in the loop, and large experimental user facilities while enabling sharing of data in ways that support #OpenScience.
These automation services handle auth, enable the specification of reusable and shareable research processes, modular actions (e.g., transfer, email, compute, metadata index), and the execution/orchestration of automation flows.
Paper: https://lnkd.in/gw-FcfX2
Registration is now open for the Materials Research Data Alliance (MaRDA) annual conference! The conference will be held fully virtual with free registration (Feb 21-23). List of speakers forthcoming soon, but I can guarantee there are exciting people involved and the discussions will be great.
Registration: https://lnkd.in/g5gyZuUy
#ai #ml #openscience #data #materialsscience #acceleratedscience
Yes!
US National Science Foundation looks to shake up funding with ‘Golden Ticket’ pilot
The agency wants to give individual reviewers the power to fund proposals they think are promising, even if other panelists disagree. The aim is to avoid only backing the least controversial applications
The US National Science Foundation (NSF) is looking to give its review panel members a ‘Golden Ticket’ to fund proposals they think have great potential, even if this goes over the heads of other panellists and programme officers. NSF hopes the pilot could help shake up how it distributes its $8.8 billion annual budget, preventing a “regression to the mean” in consensus-based funding decisions that risk rewarding only the least divisive proposals, not those with most potential.
What's the easiest way to find everyone interested in lab automation, #AI4Science for #materials, #chemistry, etc. from the old site? Should I just follow everyone that follows @aspuru?
If you're interested in these topics, give me a follow and I'll follow back!
Brian Nosek