From the course: Securing the AI/ML Development Lifecycle: A Practical Guide to Secure AI Engineering
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How AI and ML products get built
From the course: Securing the AI/ML Development Lifecycle: A Practical Guide to Secure AI Engineering
How AI and ML products get built
- [Instructor] To understand how best to secure AI projects, we first need to understand how AI products are developed and built. The truth is, there are some important differences in design and development when AI is involved. Of course, no two processes are exactly the same, so specifics always vary. But in general, there are three important high-level differences that showcase how traditional software development and AI product development differ. The first is that modern AI systems are probabilistic. This is the opposite of traditional software development. In a standard development project, a primary goal is removing uncertainty from the system. Identical inputs will produce identical outputs. After all, this makes perfect sense. Can you imagine if your bank account balance was computed differently each time you looked it up? AI systems, like large language models, systems like ChatPT, Gemini, Claude, they don't work…
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