What We’re Reading: Trends & Takeaways from the NeurIPS 2021 Conference

At the 35th Annual Conference on Neural Information Processing Systems, researchers from the Gretel research team highlighted several trends and takeaways related to machine learning and data privacy. These included advances in diffusion models for image and audio synthesis, improvements in language model performance for longer sequences, fine-tuning large pre-trained models, and addressing challenges with differential privacy (DP) such as balancing fairness and privacy, reducing worst-case privacy loss, and improving the efficiency of DP algorithms. Additionally, new datasets and metrics were introduced to improve data analysis and evaluation in supervised learning tasks.