compression – Andrew Fairless, Ph.D.

What I Read: VAE

By Andrew Fairless on May 7, 2025February 2, 2025

https://www.rehansheikh.com/blog/vae What the F*** is a VAE?Rehan SheikhJanuary 23, 2025 “A disentangled variational autoencoder aims for each latent dimension… to correspond to a single factor of variation in your dataset.”

What I Read: Toy Models of Superposition

By Andrew Fairless on December 19, 2024September 29, 2024

https://transformer-circuits.pub/2022/toy_model/index.html Toy Models of SuperpositionNelson Elhage, Tristan Hume, Catherine Olsson, Nicholas Schiefer, Tom Henighan, Shauna Kravec, Zac Hatfield-Dodds, Robert Lasenby, Dawn Drain, Carol Chen, Roger Grosse, Sam McCandlish, Jared Kaplan,Continue readingWhat I Read: Toy Models of Superposition

What I Read: Mamba Explained

By Andrew Fairless on June 10, 2024April 15, 2024

https://thegradient.pub/mamba-explained Mamba ExplainedKola Ayonrinde27.Mar.2024 “Mamba promises similar performance (and crucially similar scaling laws) as the Transformer whilst being feasible at long sequence lengths (say 1 million tokens).”

What I Read: text embeddings

By Andrew Fairless on May 20, 2024March 11, 2024

https://thegradient.pub/text-embedding-inversion/ Do text embeddings perfectly encode text?Jack Morris05.Mar.2024 “What if someone hacks into the database and gains access to all your text embedding vectors – would this be bad?….Put simply:Continue readingWhat I Read: text embeddings

What I Read: Attention Off By One

By Andrew Fairless on September 13, 2023September 4, 2023

https://www.evanmiller.org/attention-is-off-by-one.html Attention Is Off By OneBy Evan MillerJuly 24, 2023 “…the current generation of AI models have an off-by-one error in a crucial place, and it’s making everyone’s Transformer modelsContinue readingWhat I Read: Attention Off By One

What I Read: Ways Digital Minds Know

By Andrew Fairless on August 8, 2023July 9, 2023

https://moultano.wordpress.com/2023/06/28/the-many-ways-that-digital-minds-can-know/ The Many Ways that Digital Minds Can KnowRyan Moulton “…aspects of search engine quality are better analogies to describe the properties of LLMs than “generalization” and “memorization” are, andContinue readingWhat I Read: Ways Digital Minds Know

What I Read: What, Why ChatGPT

By Andrew Fairless on July 12, 2023June 15, 2023

https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/ What Is ChatGPT Doing … and Why Does It Work?February 14, 2023Stephen Wolfram “That ChatGPT can automatically generate something that reads even superficially like human-written text is remarkable, andContinue readingWhat I Read: What, Why ChatGPT

What I Learn: video quality, neural networks

By Andrew Fairless on January 26, 2023December 4, 2022

https://netflixtechblog.com/for-your-eyes-only-improving-netflix-video-quality-with-neural-networks-5b8d032da09c For your eyes only: improving Netflix video quality with neural networksby Christos G. Bampis, Li-Heng Chen and Zhi LiNetflix Technology BlogNov 14 “Recently, we added another powerful tool toContinue readingWhat I Learn: video quality, neural networks

What I Read: Illustrated Stable Diffusion

By Andrew Fairless on November 29, 2022October 20, 2022

https://jalammar.github.io/illustrated-stable-diffusion/ The Illustrated Stable DiffusionJay AlammarVisualizing machine learning one concept at a time. “The ability to create striking visuals from text descriptions has a magical quality to it and pointsContinue readingWhat I Read: Illustrated Stable Diffusion

What I Read: Snowflake Query Optimizer

By Andrew Fairless on October 11, 2022September 27, 2022

https://teej.ghost.io/understanding-the-snowflake-query-optimizer/ Understanding the Snowflake Query OptimizerSep 18, 2022 “The job of a query optimizer is to reduce the cost of queries without changing what they do…. Query optimizers aren’t uniqueContinue readingWhat I Read: Snowflake Query Optimizer

Tag: compression