Categories: AI/ML Research

A Gentle Introduction to Attention and Transformer Models

This post is divided into three parts; they are: • Origination of the Transformer Model • The Transformer Architecture • Variations of the Transformer Architecture Transformer architecture originated from the 2017 paper “Attention is All You Need” by Vaswani et al.

Liquid AI’s new STAR model architecture outshines Transformer efficiency

December 3, 2024

In "AI/ML News"

Building Transformer Models with Attention Crash Course. Build a Neural Machine Translator in 12 Days

Last Updated on January 9, 2023 Transformer is a recent breakthrough in neural machine translation. Natural languages are complicated. A word in one language can be translated into multiple words in another, depending on the context. But what exactly a context is, and how you can teach the computer to…

January 16, 2023

In "AI/ML Research"

Theory, Analysis, and Best Practices for Sigmoid Self-Attention

*Primary Contributors Attention is a key part of the transformer architecture. It is a sequence-to-sequence mapping that transforms each sequence element into a weighted sum of values. The weights are typically obtained as the softmax of dot products between keys and queries. Recent work has explored alternatives to softmax attention…

February 11, 2025

In "FAANG"

AI Generated Robotic Content