Is Word Error Rate Useful?
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.
Deep Learning
Deep dives into AI, research, coding, and other topics.
What is Residual Vector Quantization?
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 vs RLAIF for language model alignment
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.
Why Language Models Became Large Language Models And The Hurdles In Developing LLM-based Applications
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.
How RLHF Preference Model Tuning Works (And How Things May Go Wrong)
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.