100+ Top Google TechTalks Online Courses [2026]

Evaluating Data Misuse in LLMs - Introducing Adversarial Compression Rate as a Metric of Memorization

Cascading Adversarial Bias from Injection to Distillation in Language Models

Continual Release Moment Estimation with Differential Privacy

Private Adaptations of Large Language Models

Streaming Private Continual Counting via Binning

The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage

Privacy Auditing of Large Language Models

Going Back and Beyond - Emerging Old Threats in LLM Privacy and Poisoning

Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training

Threat Models for Memorization - Privacy, Copyright, and Everything In-Between

POPri - Private Federated Learning using Preference-Optimized Synthetic Data

The Limits and Possibilities of One Run Auditing

Stable Estimators for Fast Private Statistics

Watermarking in Generative AI - Opportunities and Threats

Beyond Trust - Proving Fairness and Privacy in Machine Learning

Google TechTalks Courses

Evaluating Data Misuse in LLMs - Introducing Adversarial Compression Rate as a Metric of Memorization

Cascading Adversarial Bias from Injection to Distillation in Language Models

Continual Release Moment Estimation with Differential Privacy

Private Adaptations of Large Language Models

Streaming Private Continual Counting via Binning

The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage

Privacy Auditing of Large Language Models

Going Back and Beyond - Emerging Old Threats in LLM Privacy and Poisoning

Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training

Threat Models for Memorization - Privacy, Copyright, and Everything In-Between

POPri - Private Federated Learning using Preference-Optimized Synthetic Data

The Limits and Possibilities of One Run Auditing

Stable Estimators for Fast Private Statistics

Watermarking in Generative AI - Opportunities and Threats

Beyond Trust - Proving Fairness and Privacy in Machine Learning