Hi everybody, Wanted to get some advice on learning material or resources, I currently work in a GRC job on a infosec side. Ofc a main topic always being discussed upon is AI threats, tools and overall implementation of it. I’m still fairly new to the workforce and security side and want to start developing a speciality in AI security and I personally think I mainly lack the knowledge on the architecture and infrastructure side, My goal isn’t necessarily to become an ML engineer, but rather to understand how everything fits together so I can apply that knowledge in my work. Some areas I’m interested in: AI/ML architecture fundamentals LLM infrastructure and how models are trained, fine-tuned, and served GPUs, clusters, vector databases, embeddings, and RAG MLOps and AI deployment pipelines AI security risks and attack surfaces Data governance and model governance Cloud architectures for AI workloads How organizations actually run AI in production Are there any books, courses, YouTube channels, blogs, or learning roadmaps that helped you understand the end-to-end architecture of modern AI systems? Thanks submitted by /u/geirbveheke
Originally posted by u/geirbveheke on r/ArtificialInteligence
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