[Podcast] Building Production-Ready Probes For Gemini скачать в хорошем качестве

[Podcast] Building Production-Ready Probes For Gemini

https://arxiv.org/pdf/2601.11516 This paper by Google DeepMind details the development and deployment of activation probes as a cost-effective method to prevent the misuse of Gemini for cyber-attacks. While standard LLM classifiers are effective monitors, they are computationally expensive; in contrast, probes utilize a model’s internal hidden states to detect harmful intent at a fraction of the cost. The researchers identified that traditional probes often fail when encountering long-context distribution shifts, leading them to design novel architectures like MultiMax and Max of Rolling Means to maintain robustness. By utilizing AlphaEvolve for automated architecture search and implementing cascading classifiers that defer uncertain cases to an LLM, they achieved higher accuracy than standalone models. These production-ready probes are now used in Gemini to mitigate risks involving offensive coding and cyber-security threats. Ultimately, the study demonstrates that architectural innovation and diverse training data are essential for creating reliable, low-cost safety guardrails for frontier AI systems. #ai #google #deepming #largelanguagemodels #research Disclaimer: This video is generated with Google's NotebookLM.