Explore adversarial training strategies that enhance AI security, reduce attack success rates, and address industry-specific challenges.

Learn about the essential metrics like perplexity, BLEU, and ROUGE for evaluating large language models. This blog explores strategies for effective assessment, combining automated metrics with human feedback to ensure high performance and ethical responsibility in AI applications.

A concise look at methods and tools for assessing the reasoning skills of AI systems you can’t directly inspect. Learn how to integrate evaluator models, scoring frameworks, and feedback loops for robust oversight.

Secure LLMs by encrypting data, monitoring models, securing infrastructure, enforcing ethical oversight, and continuously testing security.