YoVDO

Making GenAI Safe, Trustworthy and Fit for Purpose with Auto Alignment

Offered By: Toronto Machine Learning Series (TMLS) via YouTube

Tags

Generative AI Courses AI Ethics Courses Fairness Courses Fine-Tuning Courses Synthetic Data Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a groundbreaking alignment templating technology for enhancing the fairness, robustness, and safety of generative AI in this 56-minute Toronto Machine Learning Series (TMLS) conference talk. Delve into methods for understanding expected model behavior, measuring underperformance using synthetic test data, and iteratively improving models with minimal human intervention. Discover how this alignment platform can be applied to specific use cases, including promoting fairness towards underrepresented groups, reducing toxicity and misogyny, tailoring political viewpoints, customizing tone for customer service applications, preserving PII, and preventing harmful responses. Learn about the technology's ability to interact with users for contextual decision-making in intention-understanding, data generation, testing, and tuning processes. Presented by Rahm Hafiz, CTO and Co-Founder, and Dan Adamson, CEO and Co-founder of Armilla AI.

Syllabus

Making GenAI Safe, Trustworthy and Fit for purpose with Auto Alignment


Taught by

Toronto Machine Learning Series (TMLS)

Related Courses

What is Character? Virtue Ethics in Education
University of Birmingham via FutureLearn
Detect and Mitigate Ethical Risks
CertNexus via Coursera
Identify guiding principles for responsible AI in government
Microsoft via Microsoft Learn
Practicing Fairness as a Manager
LinkedIn Learning
Values and Ethics: Case Studies in Action
LinkedIn Learning