Скачать с ютуб Intro to LLM Security - OWASP Top 10 for Large Language Models (LLMs) в хорошем качестве

Intro to LLM Security - OWASP Top 10 for Large Language Models (LLMs)

Workshop links: WhyLabs Sign-up: https://whylabs.ai/free LangKit GitHub (give us a star!): https://github.com/whylabs/langkit Colab Notebook: https://bit.ly/whylabs-OWASPLLM10 Join the Responsible AI Slack Group: http://join.slack.whylabs.ai/ Join our workshop designed to equip you with the knowledge and skills to use LangKit with Hugging Face models. Guided by WhyLabs CEO Alessya Visnjic, you'll learn how to assess the security risks of your LLM application and how to protect your application from adversarial scenarios. This workshop will cover how to tackle the OWASP Top 10 security challenges for Large Language Model Applications (version 1.1). LLM01: Prompt Injection LLM02: Insecure Output Handling LLM03: Training Data Poisoning LLM04: Model Denial of Service LLM05: Supply Chain Vulnerabilities LLM06: Sensitive Information Disclosure LLM07: Insecure Plugin Design LLM08: Excessive Agency LLM09: Overreliance LLM10: Model Theft What you’ll need: A free WhyLabs account (https://whylabs.ai/free) A Google account (for saving a Google Colab) Who should attend: Anyone interested in building applications with LLMs, AI Observability, Model monitoring, MLOps, and DataOps! This workshop is designed to be approachable for most skill levels. Familiarity with machine learning and Python will be useful, but it's not required to attend. By the end of this workshop, you’ll be able to implement security techniques to your large language models (LLMs) . Bring your curiosity and your questions. By the end of the workshop, you'll leave with a new level of comfort and familiarity with LangKit and be ready to take your language model development and monitoring to the next level.