AI security blog

Data poisoning challenges the integrity of AI technology. This article highlights essential prevention measures, including secure data practices, rigorous dataset vetting, and advanced security tools, to safeguard AI against such threats.

Ensure your Large Language Model operates at peak efficiency with our definitive monitoring guide. Discover essential strategies, from proactive surveillance to ethical compliance, to keep your LLM secure, reliable, and ahead of the curve.

Discover strategies for AI security and learn how to establish a robust AI security framework. In this guide, we discuss various risks, and propose a number of best practices to bolster the resilience of your AI systems.

Discover the inner workings of Retrieval Augmented Generation (RAG) and how it enhances language model responses by dynamically sourcing information from external databases.

Discover Canica, Lakera's interactive text dataset viewer that elevates data analysis with visual exploration tools like t-SNE and UMAP. Now available for the machine learning community under the MIT license.

Explore the complex world of Adversarial Machine Learning where AI's potential is matched by the cunning of hackers. Dive into the intricacies of AI systems' security, understand adversarial tactics evolution, and the fine line between technological advancement and vulnerability.