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Jay Alammar

Visualizing machine learning one concept at a time.

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Moving To Substack

I’m freezing this blog and starting to post on my Substack instead. The authoring experience is much more convenient for me there. Please follow me there, and check out The Illustrated DeepSeek R-1 if you haven’t yet. And check out our How Transformer LLMs Work course!

Generative AI and AI Product Moats

Here are eight observations I’ve shared recently on the Cohere blog and videos that go over them.: Article: What’s the big deal with Generative AI? Is it the future or the present? Article: AI is Eating The World

Remaking Old Computer Graphics With AI Image Generation

Can AI Image generation tools make re-imagined, higher-resolution versions of old video game graphics? Over the last few days, I used AI image generation to reproduce one of my childhood nightmares. I wrestled with Stable Diffusion, Dall-E and Midjourney to see how these commercial AI generation tools can help retell an old visual story - the intro cinematic to an old video game (Nemesis 2 on the…

The Illustrated Stable Diffusion

Translations: Chinese, Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is the most recent AI capability blowing people’s minds (mine included). The ability to create striking visuals from text descriptions has a magical quality to it and points clearly to a shift in how humans create art. The release…

Applying massive language models in the real world with Cohere

A little less than a year ago, I joined the awesome Cohere team. The company trains massive language models (both GPT-like and BERT-like) and offers them as an API (which also supports finetuning). Its founders include Google Brain alums including co-authors of the original Transformers paper. It’s a fascinating role where I get to help companies and developers put these massive models to work…

The Illustrated Retrieval Transformer

Discussion: Discussion Thread for comments, corrections, or any feedback. Translations: Korean, Russian Summary: The latest batch of language models can be much smaller yet achieve GPT-3 like performance by being able to query a database or search the web for information. A key indication is that building larger and larger models is not the only way to improve performance. Video The last few years…

Explainable AI Cheat Sheet

Introducing the Explainable AI Cheat Sheet, your high-level guide to the set of tools and methods that helps humans understand AI/ML models and their predictions. I introduce the cheat sheet in this brief video:

Finding the Words to Say: Hidden State Visualizations for Language Models

By visualizing the hidden state between a model's layers, we can get some clues as to the model's "thought process". Figure: Finding the words to say After a language model generates a sentence, we can visualize a view of how the model came by each word (column). Each row is a model layer. The value and color indicate the ranking of the output token at that layer. The darker the color, the higher…

Interfaces for Explaining Transformer Language Models

Interfaces for exploring transformer language models by looking at input saliency and neuron activation. Explorable #1: Input saliency of a list of countries generated by a language model Tap or hover over the output tokens: Explorable #2: Neuron activation analysis reveals four groups of neurons, each is associated with generating a certain type of token Tap or hover over the sparklines on the…

How GPT3 Works - Visualizations and Animations

Discussions: Hacker News (397 points, 97 comments), Reddit r/MachineLearning (247 points, 27 comments) Translations: German, Korean, Chinese (Simplified), Russian, Turkish The tech world is abuzz with GPT3 hype. Massive language models (like GPT3) are starting to surprise us with their abilities. While not yet completely reliable for most businesses to put in front of their customers, these models…