Preprint
Self-Organizing Agent Teams Learn to Reason Together
Frozen teams learn reusable coordination strategies, with gains depending partly on their ability to recognize correct reasoning.
Published · OP · Aneesh Pappu · author post ↗
A living reading list / Ashish Makani
AI × Science.
Better questions. Reliable discoveries.
Human agency at the center.
The future I want
to help build.
I want a future in which AI agents help people ask better questions, explore more possibilities and turn reliable discoveries into benefits that reach more people. Science and mathematics offer extraordinary opportunities for this kind of collaboration, especially in medicine and biology, where better understanding can ultimately mean less suffering and more healthy life. I am interested in human–AI teams and collaborations across laboratories around the world, with each contributing strengths the others lack.
Progress should deepen human agency and meaning: the freedom to choose what matters, understand the work, challenge an answer and share in discovery. That means evaluating evidence rather than just fluent output, preserving uncertainty and giving people real authority over consequential decisions. It also means designing against accidental harm and deliberate misuse, taking dual-use risks seriously, and making the benefits of scientific capability broadly accessible.
Papers, perspectives & conversations
The reading desk
Dates are first public posting/publication where verified; talks use upload dates. Year-only dates retain their original precision. OP means an original author/team post or identified commentary. Missing posts are marked as unverified. Inclusion means worth thinking about, not endorsement. External links open in a new tab.
Preprint
ScientistTwo: Pioneering the Human Knowledge Frontier with Autonomous AI
An autonomous research pipeline combines experiments, ablations and simulated peer review; its reported successes require careful attention to selection and evaluation.
Published · OP not yet verified
Report
AI in Science: Early Insights
Combines model-use data, a specialist-model inventory and a researcher survey to examine adoption, time savings and verification demands.
Published · OP · Arthur Turrell · author commentary ↗
Technical article
AI Infrastructure at Periodic
Describes infrastructure for long scientific tool runs, specialized models and efficient training; performance claims come from the company.
Published · OP · Liam Fedus · founder commentary ↗
Viewpoint
Reflecting on 25 years of cancer research: transformative advances and unmet expectations
Six researchers reflect on cancer biology, translational disappointments and opportunities for human–AI co-science.
Published · OP not yet verified
News article
Medical school lab scientists get a new partner: AI
Describes medical researchers integrating specialized AI agents with vetted data, laboratory workflows and human oversight.
Published · OP not yet verified
Post
Latent-space reasoning as a third axis of test-time scaling
François Chollet highlights latent iterations alongside longer reasoning and parallel exploration.
Published · OP · François Chollet · original post ↗
Talk
Imagining a new future for science
Eunice Jun explores representations and interfaces that make scientific reasoning more inspectable.
Uploaded · OP not yet verified
News article
Anthropic uses Claude to formalize proof of Fermat’s Last Theorem
Reports on AI-assisted formalization of Fermat’s Last Theorem and the role of shared proof infrastructure.
Published · OP not yet verified
Talk
The paradox at the heart of AI and science
Terence Tao discusses scientific understanding, human learning and the limits of accelerating answer production.
Uploaded · OP not yet verified
Preprint
A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms
A mathematical research swarm illustrates how shared infrastructure can spread both verifier exploits and organized resistance.
Published · OP not yet verified
Preprint
Accelerating Scientific Research with Gemini in the Real-World
Reports multi-agent research workflows across materials, biology and computing, with different levels of autonomy and validation.
Published · OP not yet verified
Perspective preprint
The scientific paper needs an uncertainty layer
Proposes attaching reusable qualifications and uncertainty records to scientific claims as humans and AI reuse them.
Published · OP · Richard Sever · author commentary ↗
Perspective
Artificial intelligence in drug discovery—what it is, where we stand and the path forward
Calls for evaluating AI by its contribution to better drug-development decisions and patient-relevant outcomes.
Published · OP not yet verified
Essay
Drug Discovery Has No Magic Wands
Daphne Koller argues that useful AI drug discovery depends on better measurements and causal understanding of human biology.
Published · OP not yet verified
Paper
Solipsistic Superintelligence is Unlikely to be Cooperative
Argues that cooperative AI must account for adaptive counterparts, institutions and human agency rather than optimize in isolation.
Published · OP not yet verified
Working paper
Some Simple Economics of AGI
Develops an economic argument that verification capacity and responsibility become scarce as automated execution becomes cheaper.
Published · OP not yet verified
Preprint
Why LLMs Aren’t Scientists Yet: Lessons from Four Autonomous Research Attempts
Four autonomous ML research attempts expose implementation drift, weak evaluation and failures of scientific judgment.
Published · OP not yet verified
Workshop paper
Eliciting Research Taste in LLMs through Future Research Direction Choice
Studies model preferences among future research directions using order-controlled pairs, without equating agreement with scientific merit.
Published · 2026 · exact date unverifiedOP · Lossfunk · research-team post ↗
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