natural language processing – Andrew Fairless, Ph.D.

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 Watch: How LLMs store facts

By Andrew Fairless on December 16, 2024September 3, 2024

How might LLMs store facts | Chapter 7, Deep Learning3Blue1BrownAug 31, 2024 “Unpacking the multilayer perceptrons in a transformer, and how they may store facts”

What I Read: Fine-tuning

By Andrew Fairless on December 11, 2024September 3, 2024

https://openpipe.ai/blog/fine-tuning-best-practices-series-introduction-and-chapter-1-training-data Fine-tuning Best Practices Series Introduction and Chapter 1: Training DataReid MayoAug 1, 2024 “We’ll explore how to choose the best data, common methods for collecting it, and common methodsContinue readingWhat I Read: Fine-tuning

What I Read: Evaluating LLM-Evaluators

By Andrew Fairless on December 3, 2024August 26, 2024

https://eugeneyan.com/writing/llm-evaluators Evaluating the Effectiveness of LLM-Evaluators (aka LLM-as-Judge)Eugene Yan “After reading this, you’ll gain an intuition on how to apply, evaluate, and operate LLM-evaluators. We’ll learn when to apply (i)Continue readingWhat I Read: Evaluating LLM-Evaluators

What I Read: Classifying pdfs

By Andrew Fairless on November 21, 2024August 26, 2024

https://snats.xyz/pages/articles/classifying_a_bunch_of_pdfs.html Classifying all of the pdfs on the internetSantiago Pedroza2024-08-18 “How would you classify all the pdfs in the internet? Well, that is what I tried doing this time.”

What I Read: Tool Retrieval, RAG

By Andrew Fairless on November 20, 2024August 26, 2024

https://jxnl.co/writing/2024/08/21/trade-off-tool-selection Optimizing Tool Retrieval in RAG Systems: A Balanced ApproachJason Liu2024/08/21 “When it comes to Retrieval-Augmented Generation (RAG) systems, one of the key challenges is deciding how to select andContinue readingWhat I Read: Tool Retrieval, RAG

What I Read: LLM Pre-training Post-training

By Andrew Fairless on November 18, 2024August 26, 2024

https://magazine.sebastianraschka.com/p/new-llm-pre-training-and-post-training New LLM Pre-training and Post-training ParadigmsA Look at How Modern LLMs Are TrainedSebastian Raschka, PhDAug 17, 2024 “Initially, the LLM training process focused solely on pre-training, but it hasContinue readingWhat I Read: LLM Pre-training Post-training

What I Read: Turing Test, intelligence

By Andrew Fairless on November 12, 2024August 25, 2024

https://www.science.org/doi/10.1126/science.adq9356 The Turing Test and our shifting conceptions of intelligenceMelanie MitchellScienceVol 385, Issue 6710DOI: 10.1126/science.adq935615 Aug 2024 “It’s likely that the Turing Test will become yet another casualty of ourContinue readingWhat I Read: Turing Test, intelligence

What I Read: Generative AI Platform

By Andrew Fairless on October 29, 2024August 3, 2024

https://huyenchip.com//2024/07/25/genai-platform.html Building A Generative AI PlatformChip Huyen7/24/24 “This post outlines the common components of a generative AI platform, what they do, and how they are implemented.”

What I Read: History, Transformer

By Andrew Fairless on October 28, 2024July 22, 2024

Shaping the Future of AI from the History of TransformerStanford CS25: V4 I Hyung Won Chung of OpenAIStanford Online “I will provide a highly-opinionated view on the early history ofContinue readingWhat I Read: History, Transformer

Tag: natural language processing