[D]efenders face the daunting task of securing against all cyber threats, while attackers need to successfully find and exploit only a single vulnerability. This fundamental asymmetry has made securing systems extremely difficult, time consuming and error prone. AI-powered cybersecurity workflows have the potential to help shift the balance back to the defenders by force multiplying cybersecurity professionals like never before.
Effectively powering SecOps workflows requires state-of-the-art reasoning capabilities and extensive current cybersecurity knowledge. Sec-Gemini v1 achieves this by combining Gemini’s advanced capabilities with near real-time cybersecurity knowledge and tooling. This combination allows it to achieve superior performance on key cybersecurity workflows, including incident root cause analysis, threat analysis, and vulnerability impact understanding. — Read More
Daily Archives: April 7, 2025
How to evaluate an LLM system
Evaluating large language model (LLM) based applications is inherently challenging due to the unique nature of these systems. Unlike traditional software applications, where outputs are deterministic and predictable, LLMs generate outputs that can vary each time they are run, even with the same input. This variability arises from the probabilistic nature of these models, which means there is no single correct output for any given input. Consequently, testing LLM-based applications requires specialized evaluation techniques — known today as ‘evals’ — to ensure they meet performance and reliability standards. — Read More
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