Private AI and Mila Announce Partnership to Elevate Data Privacy Research
Private AI et Mila annoncent un partenariat pour faire progresser la recherche sur la confidentialité des données
Private AI
Top 7 Differential Privacy Papers for Language Modeling
Differential privacy is a hot topic given the many conflicting opinions on its effectiveness. For some background, we previously wrote a comprehensive post on the Basics of Differential Privacy where we discussed the risks and how it can also enhance natural language understanding (NLU) models. The differential privacy papers in this post are just a … Read more
The Basics of Differential Privacy & Its Applicability to NLU Models
Over the years, large pre-trained language models like BERT and Roberta have led to significant improvements in natural language understanding (NLU) tasks. However, these pre-trained models pose a risk of potential data leakage if the training data includes any personally identifiable information (PII). To mitigate this risk, there are two common techniques to preserve privacy: … Read more
ML Model Evaluations & Multimodal Learning
In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Dr. Aida Nematzadeh (Staff Research Scientist at DeepMind) to discuss machine learning models and multimodal learning. Before joining DeepMind, Dr. Nematzadeh was a postdoctoral researcher at UC Berkeley advised by Tom Griffiths and affiliated with the … Read more
Discussing Responsible AI & International Governance
In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Dr. Sarah Shoker (Research Scientist at Open AI) to discuss her recent work on the responsible use of AI. Dr. Shoker is part of the policy research team at Open AI on the policy research team … Read more
Language Modelling via Learning to Rank
In the previous episode of Private AI’s ML Speaker Series, Patricia Thaine (CEO of Private AI) sat down with Arvid Frydenlund (PhD candidate at the University of Toronto in the Computer Science Department and Vector Institute) to discuss his latest paper Language Modelling via Learning to Rank, presented at AAAI-2022 and published at the 6th Workshop on Structured Prediction for … Read more