Reviewing RSA 2025 with Jason Haddix
Unsupervised Learning
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Navigating AI Evaluation Challenges
This chapter explores the complexities of system improvements and the evolution of AI models, emphasizing the critical role of a testing engine in achieving effective outcomes. It highlights the inadequacies of current evaluation methods in security testing, which are outdated and often fail to meet the specific needs of domain applications. The discussion also weaves in humor with anecdotes while analyzing the shortcomings of relying on generic models for specialized tasks.
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