The Signal

Everything that matters in AI, with our take.

Updated through the day. Every headline links straight to the source. The two lines underneath are ours.

research1156 agents716 infra561 labs317 culture268 capital253 regulation233 claude175 openai149 safety103 security89 evaluation77 reasoning61 alignment52 benchmarks50 interpretability48

arXiv cs.AIPaper10d ago

When Agents Coordinate: Measuring Coordination in Multi-Agent AI Coding

This is early telemetry on how AI agents actually coordinate in practice. The finding that direct messaging scales quadratically initially then plateaus is concrete and actionable. If you're orchestrating multi-agent systems for coding or knowledge work, this benchmark gives you a vocabulary for measuring team efficiency. It's not a breakthrough, but it's the right kind of empirical work on agent teams.

agents research multi-agent measurement

arXiv cs.AIPaper11d ago

Clean Engineering, Unstable Measurement: A Preregistered Reliability Failure of Black-Box LLM Observers on Shared Endpoints

This is a systems problem that invalidates a lot of recent benchmarking work. If your leaderboards or training pipelines rely on LLM judges, your measurements are noisier than you think. The paper identifies three specific failure modes: label-to-meaning drift, sub-noise-floor variance, and non-determinism on identical inputs. Audit your evaluation pipeline now.

research measurement benchmarking reliability

arXiv cs.LGPaper14d ago

A Common Measure of Communication for Speech Brain-Computer Interfaces

Open-vocabulary mutual information (OVMI) solves a real standardization problem in BCIs: making results across different labs and conditions comparable. This matters if you're building BCI applications, less so if you're in the LLM or vision space. The practical upside is clearer measurement of which decoding approaches actually improve user communication bandwidth.

research bci measurement