MIT Researchers Introduce IF-COMP for Uncertainty Estimation, Machine Learning in Financial Forecasting

MIT researchers propose IF-COMP, a scalable solution for uncertainty estimation and improved calibration in deep learning under distribution shifts. Explore the transformative role of machine learning in financial forecasting. Plus, a study compares large kernel ConvNets to CNNs and ViTs for robustness. Also, Europe's AI Act: How does it work and what happens next?

Sources:
https://www.marktechpost.com/2024/07/16/mit-researchers-propose-if-comp-a-scalable-solution-for-uncertainty-estimation-and-improved-calibration-in-deep-learning-under-distribution-shifts/
https://www.ibtimes.co.in/transformative-role-machine-learning-financial-forecasting-870187
https://www.marktechpost.com/2024/07/15/exploring-robustness-large-kernel-convnets-in-comparison-to-convolutional-neural-network-cnns-and-vision-transformers-vits/
https://apnews.com/article/ai-act-european-union-chatbots-155157e2be2e42d0f1acca33983d8c82

Outline:
(00:00:00) Introduction
(00:00:41) The Transformative Role of Machine Learning in Financial Forecasting
(00:03:44) Exploring Robustness: Large Kernel ConvNets in Comparison to Convolutional Neural Network CNNs and Vision Transformers ViTs
(00:06:20) Europe's AI Act: How does it work and what happens next?