Membership inference attacks can detect examples used to train machine learning models even after those examples have been discarded.
In a new NeurIPS paper, Geoffrey Hinton introduced the “forward-forward algorithm,” a new learning algorithm for artificial neural networks inspired by the brain.
The two main types of machine learning categories are supervised and unsupervised learning. In this post, we examine their key features and differences.
Dimensionality reduction slashes the costs of machine learning and sometimes makes it possible to solve complicated problems with simpler models.
Reinforcement learning from human feedback (RLHF) is the technique that has made ChatGPT very impressive. But there is more to RLHF that large language models (LLM).