From the course: RAG for Cybersecurity: Use Cases and Implementation
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Introduce RAGs capabilities for risk and cyber security
From the course: RAG for Cybersecurity: Use Cases and Implementation
Introduce RAGs capabilities for risk and cyber security
- [Narrator] In the ever-evolving battlefield of cybersecurity, the threats we face grow more complex every day. Cybersecurity analysts are inundated with massive data sets from live threat intel to compliance requirements, making it harder to separate meaningful insights from the noise. This is where RAG becomes a game changer. It bridges the gap between overwhelming information and actionable insights. Let's take a look at Rag in Action. Welcome to Chapter Two. You can think of RAG as the next wave of AI, giving us more precise intelligence from those vast data pools. You'll see how RAG can shift cybersecurity from reactive to proactive. First off, why should we use RAG instead of standalone LLMs? Let's recap why LLMs are created, for a second. LLMs are pretty good at everything, but perfect at nothing, and it's because they've scanned the internet to create a model to just reduce average error in its response. And that's how the model's output is evaluated, on average error. And if…
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