OpenAI introduces GPT-4, a new large language model that surpasses human performance on various tasks. Although not yet publicly available, the article provides insights into its capabilities and how it sets a new standard for AI.
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.
Google is introducing updates to the Gemini family of models, including a new lighter-weight model called 1.5 Flash, improvements to 1.5 Pro, and a look at the future of AI assistants with Project Astra.
Researchers from NYU Tandon School of Engineering investigated whether modern natural language processing systems could solve the daily Connections puzzles from The New York Times. The results showed that while all the AI systems could solve some of the puzzles, they struggled overall.
OpenAI, the artificial intelligence research laboratory, has launched ChatGPT-4, an upgraded version of its popular chatbot. ChatGPT-4 is reportedly more powerful, private, and able to handle longer conversations than its predecessor. The chatbot uses a larger model and improved training techniques, allowing it to generate more nuanced and detailed responses. OpenAI also introduced a new feature called Instruct-1, a more precise way to guide the chatbot's responses, and a new interface for easier interaction with the AI.
This article discusses the process of training a large language model (LLM) using reinforcement learning from human feedback (RLHF) and a new alternative method called Direct Preference Optimization (DPO). The article explains how these methods help align the LLM with human expectations and make it more efficient.
This article explains the Long RoPE methodology used to expand the context lengths in LLMs without significant performance degradation. It discusses the importance of context length in LLMs and the limitations of previous positional encoding methods. The article then introduces Rotational Positional Encoding (RoPE) and its limitations, and explains how Long RoPE extends RoPE to larger contexts.
Podman AI Lab is the easiest way to work with Large Language Models (LLMs) on your local developer workstation. It provides a catalog of recipes, a curated list of open source models, experiment and compare the models, get ahead of the curve and take your development to new heights wth Podman AI Lab!
Introduces proxy-tuning, a lightweight decoding-time algorithm that operates on top of black-box LMs to achieve the same end as direct tuning. The method tunes a smaller LM, then applies the difference between the predictions of the small tuned and untuned LMs to shift the original predictions of the larger untuned model in the direction of tuning, while retaining the benefits of larger-scale pretraining.
In this tutorial, learn how to improve the performance of large language models (LLMs) by utilizing a proxy tuning approach, which enables more efficient fine-tuning and better integration with the AI model.
