We design, fund, and operate high-impact programs that prototype a new model for how science is done, shared, and scaled for real-world utility.
Science Works on Twitter / X
London AI × Science Hackathon 👾Science Works × @inherent_labs • Oct 16-18Lots of scientific software is outdated, hard to use, and isn't interoperable – let alone making use of (or ready to interface with) AI.Or it's expensive. Join us to build better for the community pic.twitter.com/42Qq528DDw— Science Works (@sci_works) September 30, 2026
The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale
Sir Isaac Newton famously wrote, “If I have seen further, it is by standing on the shoulders of giants”. Scientific contributions are rarely developed in isolation, but build upon prior contributions, such as problem framings, experimental methods, and empirical findings. Understanding these prerequisite relationships is important for studying scientific progress, and for automated scientific discovery systems that must reason about which existing capabilities can be used to develop new ones (e.g. Lu et al., 2024; Jansen et al., 2025b; Baek et al., 2025).
Linking the world's research to the code it runs on - OpenAlex blog
Research relies on software. Software written by scientists, for science, runs through the entire modern research stack: NumPy and SciPy, R and ggplot2, Jupyter, BLAST, ImageJ, AlphaFold. Yet in the scholarly record, that software is nearly invisible. Software is not usually cited formally in publications and is usually just mentioned in the text, which means […]
Hyperproblems: New Ways of Doing and Communicating Science - Hyperproblems
Hyperproblems: Hyperproblems are scientific challenges whose scale, complexity, novelty and interdependence overwhelm traditional research models, requiring…
System: Formalizing Science: From Open Corpus to Computable System
Open access made much of the scientific record openly available. An enormous opportunity now exists to make it computable and systemic.
Gemini for Science: AI experiments and tools for a new era of discovery
Gemini for Science is a new collection of science tools and experiments to expand the scale and precision of scientific exploration.
We're releasing Terminal-Bench-Science: a benchmark for evaluating AI agents on research workflows across scientific domains. 🚀 An ongoing community effort out of Stanford University & Laude… | Steven Dillmann | 13 comments
We're releasing Terminal-Bench-Science: a benchmark for evaluating AI agents on research workflows across scientific domains. 🚀 An ongoing community effort out of Stanford University & Laude Institute, built by the team behind Terminal-Bench together with scientific domain experts at research institutions worldwide. 🧪 ⚛️ 🌍 ➕ ⚙️ Terminal-Bench-Science 0.1 has 70 tasks across the life, physical, earth, mathematical, and engineering sciences. Each one is contributed by a researcher porting their own workflows into challenging agentic tasks, on problems they actually care about. 🧠 Anthropic's Opus 5 dominates most scientific domains with an overall pass rate of ~30%, except the mathematical sciences, where Fable 5 and OpenAI's GPT-5.6 Sol take the lead. SpaceXAI's Grok 4.6 is one of the best models for engineering tasks, Z.ai's GLM 5.3 is the best open model, and Kimi (Moonshot AI)'s Kimi K3 is the only model beyond Opus 5 that lands on both cost and token efficiency Pareto frontiers. 🏆 All leaderboard results are live here: https://lnkd.in/gYh99UfU 💻 You can find all tasks on our Github: https://lnkd.in/gejKmXpj Special thanks to our amazing reviewer team Allen Hart, Ivan Bercovich, Joe Janssen, Jiaming H., Steffen Bollmann, Sergey Aganezov, Ben Blaiszik, Karl Krauth, Aaron Feller, Ben Blaiszik, Yiqi Liu, Han Hou, Robert Joseph G., Robert Zhang; our AI research advisors Ryan Marten, Alex Shaw, Lin Shi, Ben Feuer, Mike Merrill, Gian Segato, Jenia Jitsev, Bodhisattwa Majumder, Peter Clark, Thomas Wolf, Braden Hancock, Andy Konwinski, Alex Dimakis; and especially to our co-leads Sanmi Koyejo and Ludwig Schmidt. | 13 comments on LinkedIn
Kevin Weil 🇺🇸 on Twitter / X
💥 Today we’re introducing Prism—a free, AI-native workspace for scientists to write and collaborate on research, powered by GPT-5.2.Accelerating science requires progress on two fronts:1. Frontier AI models that use scientific tools and can tackle the hardest problems2.… pic.twitter.com/cnLysHixuQ— Kevin Weil 🇺🇸 (@kevinweil) January 27, 2026
Banff 2025, Open Science Meeting — Continuous Science Foundation
We’ve got to a big idea—and now it’s time to get practical. CSF is looking for curious, committed individuals to help us tackle some of the toughest (and most exciting) questions around how to make Composable Science real.
Ten quick tips to SNIFF out sustainable and secure scientific software
Modern computational biology depends heavily on open-source software tools, analysis pipelines, and containerized workflows developed and shared by the research community. While there is extensive guidance (including Quick Tips and Simple Rules articles) on how to build robust and sustainable scientific software, far less has been written for researchers in the role of software users evaluating whether an existing tool is reliable, secure, and sustainable enough for their work. Here we present ten quick tips to help researchers critically assess the tools they adopt. Our tips are organized around a framework that centers on key evaluation features: source, network, interaction, fit, and fragility (SNIFF). These dimensions prompt researchers to consider who maintains a tool and why, whether it is embedded in a broader ecosystem, how actively its developers and users engage, whether it matches the intended use case and licensing requirements, and how robust its dependencies and security practices are. By applying these tips, researchers can make more informed decisions, reduce the risk of relying on abandoned or insecure software, and contribute to a more sustainable scientific software ecosystem.
Seth Bannon on Twitter / X
There are some exceptionally good ideas here for reforming and accelerating science.Some of my favorite proposals:Apply the scientific method to science funding (track applications, reviewers, funding decisions, and outcomes, then experimentally test which grantmaking methods… https://t.co/Q0JmqTBPYm— Seth Bannon (@sethbannon) July 22, 2026
SCI — Software Carbon Intensity | Green Software Foundation
The global standard for calculating and reducing the carbon emissions of your software. ISO/IEC 21031:2024.
Games Demystified: Super Mario Galaxy
Want to see how Mario Galaxy created its unique gravity-based physics effects for the in-game planets? Developer Alessi analyzes and reproduces the same concepts with a playable game prototype and source code.