MLLM, Multiple Modalities, One Model
Last update: April 23rd, 2024 This is part of a series describing the key principles underpinning the current AI revolution. To fully understand this blog post, I highly encourage you to take a look at the blog post about Large Language Models (LLMs) and Transformers. As we discussed in the previous blog post about Large […]
LLMs, The Backbones of Frontier AI
Last update: April 17th, 2024 This article assumes the readers knowledge on embeddings, the attention mechanism, and ultimately Transformers architectures. Please refer to these links for in-depth explanations of every concept. Large Language Models, or LLMs, have become synonymous with intelligent AI systems. Nonetheless, they are the backbone of all our best AIs, from ChatGPT […]
Transformers, The Great Paradigm Shift
Last update: April 17th, 2024 This article is part of a series that aims to describe how our frontier AI models are created in easy-to-understand terms, with today’s topic being Transformers, a seminal component of these models. In particular, this piece assumes the reader understands what embeddings are and how the attention mechainsm works. Otherwise, […]
Foundation Models, When AI Became General-Purpose
ChatGPT did not start the AI revolution, foundation models did. But what are they such a monumental shift to the space?
In-Context Learning, LLMs’ Greatest Superpower
Last updated: April 23rd, 2024 It’s hard to deny how, at this point, things have changed in AI with the arrival of Large Language Models (LLMs). And much of their success is thanks to in-context learning, the greatest feature of LLMs and the reason why they are sometimes referred to as «foundation models«. But what […]
Mixture-of-Experts, The New Standard for LLMs
In the fast-paced world of AI, things come and go. But seminal breakthroughs stay, and one of those is Mixture-of-Experts. But what is it?
