Transformers are changing the AI landscape, and it all began with the groundbreaking paper “Attention is All You Need.” Today, I explore the Introduction and Background sections of the paper,…
Below is a comprehensive table of key terms used in the paper “Attention is All You Need,” along with their English and Chinese translations. Where applicable, links to external resources are…
Today marks the beginning of my adventure into one of the most groundbreaking papers in AI for transformer: “Attention is All You Need” by Vaswani et al. If you’ve ever been curious about how modern…
On December 20, 2024, OpenAI concluded its 12-day “OpenAI Christmas Gifts” campaign by revealing two groundbreaking models: o3 and o3 mini. At the same time, the ARC Prize organization announced…
Ray Serve is a cutting-edge model serving library built on the Ray framework, designed to simplify and scale AI model deployment. Whether you’re chaining models in sequence, running them in parallel,…
Quantization is a transformative AI optimization technique that compresses models by reducing precision from high-bit floating-point numbers (e.g., FP32) to low-bit integers (e.g., INT8). This…
Weight Initialization in AI plays a crucial role in ensuring effective neural network training. It determines the starting values for connections (weights) in a model, significantly influencing…
Knowledge Distillation in AI is a powerful method where large models (teacher models) transfer their knowledge to smaller, efficient models (student models). This technique enables AI to retain high…