Deep dives into AI, research, coding, and other topics.
Large Language Models are trained to guess the next word. But when generating text, the combination of their probability estimates with algorithms known as decoding strategies is what determines how they actually choose words. Learn how decoding strategies work in this article.
Microsoft's Florence-2 is a foundational image model that can perform almost every common task in computer vision. Learn how Florence-2 works and how to use it in this guide.
From fundamental research to productionized AI models, let’s discover how this cutting-edge technology is powering production applications and may be shaping the future of AI.
Recently, researchers have made progress towards universal audio understanding, marking an advancement towards foundational audio models. The approach is based on a joint audio-language pre-training that enhances performance without task-specific finetuning.
A new approach towards multi-speaker speech processing integrates Speaker Diarization and Automatic Speech Recognition in a unified framework. We discuss the key insights from this recent exciting development in Speech AI research.
How does OpenAI's groundbreaking DALL-E 2 model actually work? Check out this detailed guide to learn the ins and outs of DALL-E 2.
Text-to-Music Models are advancing rapidly with the recent release of new platforms for AI-generated music. This guide focuses on MusicLM, MusicGen, and Stable Audio, exploring the technical breakthroughs and challenges in creating music with AI.
What is Word Error Rate and is it a useful measurement of accuracy for speech recognition systems? In this article, we examine the answer to these questions, as well as explore other alternatives to Word Error Rate.
Neural Audio Compression methods based on Residual Vector Quantization are reshaping the landscape of modern audio codecs. In this guide, learn the basic ideas behind RVQ and how it enhances Neural Compression.
RLHF is the key method used to train AI assistants like ChatGPT, but it has strong limitations and can produce harmful outputs. RLAIF improves upon RLHF by using AI feedback. Learn the differences between the two methods and what these differences mean in practice in this guide.
What’s the difference between Language Models and Large Language Models? Let’s understand AI development trends and the difficulties of integrating LLMs into real-world applications.
Large Language Models like ChatGPT are trained with Reinforcement Learning From Human Feedback (RLHF) to learn human preferences. Let’s uncover how RLHF works and survey its current strongest limitations.
Reinforcement Learning from AI Feedback (RLAIF) is a supervision technique that uses a "constitution" to make AI assistants like ChatGPT safer. Learn everything you need to know about RLAIF in this guide.
The spotlight has been on language and images for Generative AI, but there's been a lot of recent progress in the audio domain. Learn everything you need to know about generative audio models in this article.
Speech Recognition models are key in extracting useful information from audio data. Learn how to properly evaluate speech recognition models in this easy-to-follow guide.
A Product Manager's guide to understanding Large Language Models and the building blocks of Conversational AI.
Generative AI language models like ChatGPT are changing the way humans and AI interact and work together, but how do these models actually work? Learn everything you need to know about modern Generative AI for language in this simple guide.
Modern Generative AI models for images are powering a range of creative applications and changing the way we work. This guide will overview everything you need to know about these models and how they work.
Large Language Models have been in the limelight since the release of ChatGPT, with new models being announced seemingly every week. This guide walks through the essential ideas of how these models came to be.
Generative AI has made tremendous strides recently, from models like Stable Diffusion to ChatGPT. Get up to speed on the latest advancements with this easy-to-follow introduction to Generative AI.
Generative AI has taken the world by storm in the last several months, but what actually is Generative AI, and how does it work? Learn everything you need to know about Generative AI in this easy-to-follow series.
Many cutting-edge Generative AI models are inspired by concepts from physics. In this guide, we’ll take a high-level look at how physics is driving advancements in AI.
Emergence can be defined as the sudden appearance of novel behavior. Large Language Models apparently display emergence by suddenly gaining new abilities as they grow. Why does this happen, and what does this mean?
This week’s AI Research Review is Locating and Editing Factual Associations in GPT.
Since its release, the public has been playing with ChatGPT and seeing what it can do, but how does ChatGPT actually work? While the details of its inner workings have not been published, we can piece together its functioning principles from recent research.