Articles about Learning in AI
Introduction Understanding BM-25: A Powerful Algorithm for Information Retrieval Bm25 is an enhancement of the TF-IDF model that incorporates term frequency saturation and document length normalization to improve retrieval performance. When it comes to search engines and information retrieval, a vital piece of the puzzle is ranking the relevance of documents to a given query. … Read more
Introduction TF-IDF (Term Frequency-Inverse Document Frequency) is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents (corpus). It combines two metrics: Term Frequency (TF) and Inverse Document Frequency (IDF). The TF-IDF value increases proportionally with the number of times a word appears in the … Read more
Introduction The latest Ollama update makes it easier than ever to run quantized GGUF models directly from Hugging Face on your local machine. With a single command, you can bypass previous limitations, no longer needing a separate model on the Ollama Model Hub. Step-by-Step Guide 1. Install Ollama 2. Select a Model from Hugging Face … Read more
Introduction OpenAI has launched a groundbreaking new feature for ChatGPT: SearchGPT. This innovative tool blends the conversational nature of a chatbot with the vast resources of the internet, potentially changing the way we search for information forever. With SearchGPT, users can ask questions in natural language and receive concise answers, complete with links to relevant … Read more
NotebookLM: An AI-Powered Research Assistant NotebookLM is a research assistant powered by Google’s Gemini 1.5 Pro model. It’s centred around the idea of using sources and then leveraging the power of Gemini to interact with and learn from them. Here are some of the key features that make NotebookLM such a powerful tool: 1. Versatile … Read more
For part 1 refer to this: Unveiling the Secrets Behind ChatGPT – Part 1 (learncodecamp.net) Implementing a Bigram Language Model When diving into the world of natural language processing (NLP) and language modeling, starting with a simple baseline model is essential. It helps establish a foundation to build upon. One of the simplest and most … Read more
Introduction Hello everyone! By now, you’ve likely heard of ChatGPT, the revolutionary AI system that has taken the world and the AI community by storm. This remarkable technology allows you to interact with an AI through text-based tasks. The Technology Behind ChatGPT: Transformers The neural network that powers ChatGPT is based on the Transformer architecture, … Read more
Introduction Intelligence: The ability to process information and use it for future decision-making. Artificial Intelligence (AI): Empowering computers with the ability to process information and make decisions. Machine Learning (ML): A subset of AI focused on teaching computers to learn from data. Deep Learning (DL): A subset of ML utilizing neural networks to process raw … Read more
The Busy Person’s Guide to Large Language Models: From Inner Workings to Future Possibilities (and Security Concerns) This post explores the fascinating world of large language models (LLMs) like ChatGPT and llama2, diving into their inner workings, potential future developments, and even the security challenges they present. It’s a summary of a talk by Andrej … Read more
Introduction Large Language Models (LLMs) are the powerhouses behind cutting-edge AI applications like chatbots and text generation tools. These complex models have traditionally relied on high-performance GPUs to handle the massive amounts of computation involved. But what if that wasn’t necessary? Recent breakthroughs, like the BitNet B1.58 model, hint at a future where LLMs can … Read more
