AI & Data

In this learning path, you will gain a fundamental understanding of Large Language Model (LLM) security. Through a series of articles and videos you will explore topics like what is an LLM, data security risks, the OWASP Top 10 for LLMs, strategies for defending LLM systems, and the critical role users play in maintaining security.

Generative AI is a cutting-edge technology that has been making waves across various industries in recent years. Unlike traditional AI systems that are designed to analyze and interpret existing data, generative AI has the remarkable ability to create entirely new content, from text and images to music and even code. This revolutionary technology leverages complex machine learning algorithms and neural networks to understand patterns and structures in vast amounts of data, enabling it to generate original and often highly realistic outputs. As generative AI continues to evolve and improve, it promises to transform creative processes, problem-solving, and innovation across numerous fields, from art and entertainment to scientific research and product development. Learn about what Generative AI is and how it works, in this Learning Path.

NVIDIA AI Enterprise (NVAIE) offers a robust suite of AI tools for various applications, including reasoning, speech & translation, biomedical, content generation, and route planning. It features community, NVIDIA, and custom models. NVAIE provides essential microservices such as NIM and CUDA-X used for security advisory, enterprise support, cluster management, and infrastructure optimization. Designed for cloud, data centers, workstations, and edge environments, NVAIE ensures scalable, secure, and efficient AI deployment.

In this learning path you will gain a fundamental understanding of AI security by exploring topics such as the AI development lifecycle, data flow during this lifecycle, as well as attack surfaces present in the AI development lifecycle. You will also learn about topics such as the attacks that AI models face and the risks of user data and privacy when it comes to AI.