Publicly Detectable Watermarking for Language Models - PPML 2024 Invited Talk
Offered By: TheIACR via YouTube
Course Description
Overview
Explore a cutting-edge invited talk from the Privacy-Preserving Machine Learning Workshop (PPML) 2024, an affiliated event of Crypto 2024. Delve into Sanjam Garg's presentation titled "Publicly Detectable Watermarking for Language Models," chaired by Harish Karthikeyan. Gain insights into the latest advancements in privacy-preserving techniques for machine learning, focusing on watermarking methods for language models. Learn about the importance of public detectability in watermarking and its implications for protecting intellectual property in AI models. Discover how this research contributes to the broader field of cryptography and machine learning security during this 50-minute talk, which serves as the first of three invited presentations at the workshop.
Syllabus
PPML 2024 invited talk I by Sanjam Garg
Taught by
TheIACR
Related Courses
Microsoft Bot Framework and Conversation as a PlatformMicrosoft via edX Unlocking the Power of OpenAI for Startups - Microsoft for Startups
Microsoft via YouTube Improving Customer Experiences with Speech to Text and Text to Speech
Microsoft via YouTube Stanford Seminar - Deep Learning in Speech Recognition
Stanford University via YouTube Select Topics in Python: Natural Language Processing
Codio via Coursera