When Anthropic announced it would watermark text output from Claude models, Sebastian Raschka posted a short explanation of the mechanism. The post went unexpectedly viral — not because watermarking is exciting, but because almost nobody could say concretely what it does. He planned a ten-slide follow-up. It became fifty. The result is one of the better explainers of the year, and it doubles as a clean walkthrough of how LLM sampling actually works....
arXiv: 2607.15267 · PDF: 2607.15267.pdf Authors: Victoria Graf, Hannaneh Hajishirzi, et al. TL;DR Prior work on pretraining-data poisoning has mostly targeted curated sources like Wikipedia — a poor stand-in for the scale and heterogeneity of real pretraining corpora. This paper demonstrates that public discussion interfaces on the open web (comment sections, forums, Q&A pages) are a viable at-scale injection vector, and introduces HalfLife, an analysis technique for estimating whether adversarial content actually survives web-crawl-based data curation pipelines and lands in the training set....
Google DeepMind’s podcast sat down with Nenad Tomašev, senior staff research scientist at DeepMind, to ask a question that’s about to stop being theoretical: what happens when millions of agents start transacting, negotiating, and delegating to each other — not just to humans? The episode is one of the rare ones where a research lab talks publicly about open problems instead of product launches. With Gemini Spark, Antigravity, OpenClaw-style frameworks, and dozens of vendor agent runtimes all shipping, the multi-agent layer is now the part of the stack with the least standardization and the most unknown failure modes....