ColBERT is a new way of scoring passage relevance using a BERT language model that substantially solves the problems with dense passage retrieval.
Andrej Karpathy's recommended paper reading list, covering various aspects of Language Models (LLMs), including attention mechanisms, unsupervised multi-task learning (GPT-2), instruction-following language models (InstructGPT), LLaMA, reinforcement learning from human feedback (RLAIF), and early experiments of GPT-4, offering insights into significant research developments in LLM and their role in AI landscape, benefiting both novice and experienced AI enthusiasts.
- Challenges in measuring similarity between unstructured text data like movie descriptions.
- Simple NLP methods may not yield meaningful results; thus, a controlled vocabulary is proposed.
- Using an LLM, a genre list is generated for movie titles, which helps improve the similarity model.
A function is created to find the most similar movies to a given title based on cosine similarity scores.
Network visualization highlights clusters of genres linked via movies, showcasing potential improvements in recommender systems.
The TextWrapper class provides functionality for wrapping long pieces of text into multiple shorter lines while preserving the initial and subsequent indents.
- Embeddings transform words and sentences into sequences of numbers for computers to understand language.
- This technology powers tools like Siri, Alexa, Google Translate, and generative AI systems like ChatGPT, Bard, and DALL-E.
- In the early days, embeddings were crafted by hand, which was time-consuming and couldn't adapt to language nuances easily.
- The 3D hand-crafted embedding app provides an interactive experience to understand this concept.
- The star visualization method offers an intuitive way to understand word embeddings.
- Machine learning models like Word2Vec and GloVe revolutionized the generation of word embeddings from large text datasets.
- Universal Sentence Encoder (USE) extends the concept of word embeddings to entire sentences.
- TensorFlow Projector is an advanced tool to interactively explore high-dimensional data like word and sentence embeddings.