Dear Reader,

Welcome to the 338th edition of the Data Science Briefing.

Agents forget, and they push. One developer lost half a session to silent context compaction and now keeps memory in files, with handoff documents, shared specs and a clear test of done. His agent then deferred 11 of 15 review findings into a release that did not exist. A rule that lets the model stop at done fixed it. Long sessions cost money too. Cache reads dominate an agent’s bill, and output tokens make up only 9 to 18 percent of spend.

Classification is back in fashion. A history of text classifiers ends with Jev, which scored 96.47 percent on IMDb for 65 cents with no fine-tuning. One researcher traces its secret to calibrated multiway reward modeling. At the other extreme, gzip becomes a text generator with no weights at all. A naive $2,071 earnings gap for a job training program hides large differences between the two groups. A seasonal ARIMA beats a naive household power forecast by a small margin, and that margin is the lesson.

Human activity leaves a mark on disease. A study of 58,318 outbreaks of 32 diseases in 169 countries ties risk to people and livestock living near fragmented forests. Each extra hour of travel to a clinic cuts the odds of detecting an outbreak by 32 percent, so many hotspots mark good surveillance. Dengue risk is rising in Europe, and awareness is high. In France and Italy, 91 percent of 2,904 people surveyed knew of dengue, but only 59 percent took even one preventive step. Missing information carries its own risk. Across vaccine rollouts in six European countries, information voids lined up with more misinformation.

Machines now stand in for people, and they pick up our social habits. A new paper weighs when language models can replace human subjects in research. Classic network models still teach a lesson. Coupling a cooperation game with a second social process, like opinion spread, helps prosocial behavior win. The same social forces expose AI agents. In populations of language model agents, a small adversarial group can flip a shared convention through stepping-stone states, with fewer members than a direct attack needs.

Attacks and defenses keep scaling. One model writes 200 jailbreak suffixes for a single query in 4 seconds, with near 100 percent success on two open models and 99 percent on GPT-3.5. On defense, Jev screens for alignment failures with no training. Across 44 benchmarks and 10 failure types, it reached a median AUROC of 0.886 at 63 times lower cost than LLM judges.

Our latest book recommendation is “Hands-On LLM Serving and Optimization” by C. Wang and P. Hu. In this week’s video, we have a lecture on Deterministic Concurrency.

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Semper discentes,

The D4S Team