Machine learning (ML) models, e.g., deep neural networks (DNNs), are vulnerable to adversarial examples: malicious inputs modified to yield erroneous model outputs, while appearing unmodified to human observers. Potential attacks include having malicious ... (more…)

A collaboration from UoC Berkeley, Stanford University and Facebook offers a deeper and more granular picture of the actual state of poverty in and across nations, through the use of machine learning. The research, entitled Micro-Estimates of Wealth for a... (more…)

by David Berg, Ravi Kiran Chirravuri, Romain Cledat, Savin Goyal, Ferras Hamad, Ville Tuulos... (more…)

Machine Learning has in impact on our climate. Here's how to estimate your GPU's carbon emissions... (more…)

An Open-Source Machine Learning Framework in Rust Δ - delta-rs/delta... (more…)