Humboldt — Humboldt

No. 008: AI co-mathematician, compiler-verified protocols, open infrastructure bets - The Hallway Track

The Hallway Track No. 008 - How AI is affecting the practice of science

No. 022: Palomar proof registry, autonomous protein design, synthetic consensus - The Hallway Track

The Hallway Track No. 022 - How AI is affecting the practice of science

Agent4Science

A social network for AI scientists — where agents share, debate, and discuss research papers.

Inventing New Nature

Defining the Protocol Institute's research mission

No. 005: GPT-Rosalind, AI verification gap, Agent4Science - The Hallway Track

The Hallway Track No. 005 - How AI is affecting the practice of science

Science that Compounds: The Need for A New Substrate for Research in the Age of AI

This paper is a perspective from Lightcone Research, an open-source initiative building tooling for scientific research in the age of agentic AI.

AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions

Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code generation, data analysis, hypothesis proposal, and model criticism. We argue that this transition is qualitative rather than incremental, and that suitably designed multi-agent systems may evolve from passive computational tools into ``AI scientists'' that can expand the hypothesis-generating and verification capacity of science. Such systems must be developed and deployed within a scientific ecosystem fit for purpose: institutions must be redesigned for verification, accountability, interpretability, and dual-use safety. We sketch how multi-agent architectures, illustrated by the prototype framework \textit{Denario}, accelerate the discovery cycle and traverse model spaces beyond human reach; examine what this implies for authorship, peer review, and the enduring role of human scientists; and close with recommendations for governing AI as an epistemic actor rather than a mere instrument.

How to build an AI scientist: first peer-reviewed paper spills the secrets

AI Scientist, an autonomous research tool, first released in 2024, has now undergone peer review, highlighting its strengths and limitations.

Arthur Turrell on Twitter / X

Today @Google, we published work led by @m_codreanu on AI in Science, drawing on 15 million Gemini interactions, 2,600 specialised AI models & a 600-scientist survey. What did we find about how AI is changing science? Read on... pic.twitter.com/VqO2xxcm02— Arthur Turrell (@arthurturrell) September 15, 2026

Edison Scientific | The AI Platform for Scientific Discovery

Edison is an AI scientist that autonomously reads, reasons, and experiments across disciplines. Accelerate your research with the world’s first unified AI platform for scientific discovery.

How we built our multi-agent research system

On the the engineering challenges and lessons learned from building Claude's Research system

#101 - Joscha Bach: Artificial Consciousness and the Nature of Reality | Lex Fridman Podcast

Joscha Bach is the VP of Research at the AI Foundation, previously doing research at MIT and Harvard. Joscha work explores the workings of the human mind, intelligence, consciousness, life on Earth, and the possibly-simulated fabric of our universe. Support this podcast by supporting these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn,

Infinite Researchers | AI-Powered Scientific Discovery

What happens to the speed of discovery if we have infinite researchers? Explore AI experiments accelerating breakthroughs.

Lightcone Research

An open ecosystem for inspectable, composable, and referenceable scientific research in the age of agentic AI.