Training vs Inference in AI — The Security Implications #2 ( AI Security MasterClass ) скачать в хорошем качестве

Training vs Inference in AI — The Security Implications #2 ( AI Security MasterClass )

Artificial Intelligence systems operate in two fundamentally different phases: training and inference. Most people understand the surface-level difference. Very few understand the security implications. In this episode of the AI Security Masterclass, we break down: • What happens during model training • What happens during inference • Why training is vulnerable to data poisoning and supply chain risks • Why inference is exposed to prompt injection and runtime attacks • How enterprise security controls differ between the two phases If you’re working in cloud security, architecture, DevSecOps, or AI integrations, understanding this distinction is critical. Securing a training pipeline is not the same as securing an AI API. Training determines what a model learns. Inference determines how it behaves in the real world. This foundational clarity is essential before moving into advanced AI threat modeling and defense strategies. Subscribe for practical, architecture-level AI security insights designed for security engineers and architects. #cybersecurity #aisecurity #infosec