This tutorial introduces the essential topics of the PyTorch deep learning library in about one hour. It covers tensors, training neural networks, and training models on multiple GPUs.
Newsweek interview with Yann LeCun, Meta's chief AI scientist, detailing his skepticism of current LLMs and his focus on Joint Embedding Predictive Architecture (JEPA) as the future of AI, emphasizing world modeling and planning capabilities.
The attention mechanism in Large Language Models (LLMs) helps derive the meaning of a word from its context. This involves encoding words as multi-dimensional vectors, calculating query and key vectors, and using attention weights to adjust the embedding based on contextual relevance.
The article delves into how large language models (LLMs) store facts, focusing on the role of multi-layer perceptrons (MLPs) in this process. It explains the mechanics of MLPs, including matrix multiplication, bias addition, and the Rectified Linear Unit (ReLU) function, using the example of encoding the fact that Michael Jordan plays basketball. The article also discusses the concept of superposition, which allows models to store a vast number of features by utilizing nearly perpendicular directions in high-dimensional spaces.
The self-attention mechanism is used to capture interactions between words within input and output sequences. It involves computing keys, queries, and values vectors, followed by matrix multiplications and a softmax transformation to produce an attention matrix.
Explore the intricacies of the attention mechanism responsible for fueling the transformers.
Researchers from the University of California San Diego have developed a mathematical formula that explains how neural networks learn and detect relevant patterns in data, providing insight into the mechanisms behind neural network learning and enabling improvements in machine learning efficiency.
An article discussing the concept of monosemanticity in LLMs (Language Learning Models) and how Anthropic is working on making them more controllable and safer through prompt and activation engineering.
Stay informed about the latest artificial intelligence (AI) terminology with this comprehensive glossary. From algorithm and AI ethics to generative AI and overfitting, learn the essential AI terms that will help you sound smart over drinks or impress in a job interview.
