Levers for Progress

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).

The Engine of Scientific Discovery: How New Methods and Tools Spark Major Breakthroughs

Abstract. How do we spark new scientific discoveries? Why do some breakthroughs seem even accidental? And most importantly, how can we accelerate them and

What stories should we tell about scientific progress now?

In search of the mysterious fruits of basic science

Thomas Kuhn Foundation | Science Intelligence for the New World

The world's first science intelligence engine capable of monitoring scientific progress in real time

Push-button science

Technological advances change not only what we can learn as scientists, but also how science is conducted. Here we explore how automation and outsourcing are affecting the act of doing science.

science-live-platform/zotero at main · ScienceLiveHub/science-live-platform

Science Live Platform - Transform research into connected knowledge - ScienceLiveHub/science-live-platform

Rebuilding the Architecture of Science

Science built the modern world. It’s time to rebuild the world of science.

PRISM: Capturing the Invisible Art of Scientific Practice

A New Tool for Recording and Scaling Laboratory Expertise

Science Needs Scientists

And Scientists Need Science

Without a theory of intelligence

The history of science — and of progress — is a series of benefits that are direct results of new tools.

Design in The Age of Biology: Shifting From a Mechanical-Object Ethos to an Organic-Systems Ethos

In the early twentieth century, our understanding of physics changed rapidly; now, our understanding of biology is undergoing a similar rapid change.

A Data Utopia for Science-of-Science

Here I want to briefly sketch out a vision for how to solve a key set of problems facing science-of-science researchers, using the relatively new idea of a ‘data trust.’ In my ideal wor…

Fulcrum - Leverage for Discovery

We place AI engineers with research labs working on hard scientific problems.

Broadening Access to Data Science Education in High School and Higher Education through Open Source Tools and Training

As data plays a more integral part to our daily lives, there is a growing need for data science education. However, access to curriculum, tooling, and infrastructure is not readily available to many students in the U.S. We review the current state of data science education tools and implementations as well as highlight a set of emerging tools and technologies. We conclude that broadening data science education requires a multifaceted approach, involving technological accessibility, instructional equity, curricular relevance, and long-term sustainability.