Blog
Fighting Contextual Drag: can a model learn from its own mistakes?
August 2026
A systematic investigation into contextual drag in Qwen3-8B.
Does Better Embedding Quality Actually Improve Bayesian Optimization with LLMs?
April 2026
A systematic investigation into BOPRO for molecular optimization
AI Therapy: What the First RCT of a Generative‑AI Therapist Really Tells Us
May 2025
Therabot’s NEJM AI RCT shows that an open‑weight LLM, fine‑tuned on rigorously curated therapy transcripts and guarded by strict safety layers, yields a moderate (~d 0.6) short‑term improvement over wait‑list controls—impressive for generative‑AI healthcare, but likely an upper‑bound effect size given design inflation.
How to train your Llama – and ChatGPT-3.5 – for a retrieval augmented generation (RAG) task.
September 2023
How to fine-tune Llama-2 and ChatGPT-3.5 for a retrieval augmented generation (RAG) task
Causal Discovery
September 2020
Causal discovery is the process of inferring the causal structure of a closed system using observational data.
This post outlines how causal discovery is possible using time series data, and explores some novel techniques developed by Runge and colleagues in a series of papers in Nature Communications, and Science Advances. The team has also created a software package, Tigramite, that implements these methods.
Collective Intelligence
June 2017
Our new publication on the wisdom of crowds has come out in Proceedings of the National Academy of Sciences here.
Engineering Behavior Change Through Social Media
June 2015
Our research on a social media intervention to increase health in a fitness program was presented in Helskini, Finland during the IC2S2 conference.