tuning – Andrew Fairless, Ph.D.

What I Read: Instruction Tuning

By Andrew Fairless on February 19, 2024December 19, 2023

https://gaotianyu.xyz/blog/2023/11/30/instruction-tuning/ Teach Llamas to Talk: Recent Progress in Instruction TuningTianyu Gao30 November 2023 “…open-ended instruction tuning… fine-tunes an LLM such that it can follow user instructions…. there have been numerousContinue readingWhat I Read: Instruction Tuning

What I Read: Enterprise AI, RAG + Fine Tuning

By Andrew Fairless on January 11, 2024November 20, 2023

https://www.montecarlodata.com/blog-the-moat-for-enterprise-ai-is-rag-fine-tuning/ The Moat for Enterprise AI is RAG + Fine Tuning – Here’s WhyLior GavishUpdated Nov 09 2023 “Data needs to be secure and private; LLM deployment needs to beContinue readingWhat I Read: Enterprise AI, RAG + Fine Tuning

What I Read: LLM Training, RLHF

By Andrew Fairless on October 30, 2023October 5, 2023

https://magazine.sebastianraschka.com/p/llm-training-rlhf-and-its-alternatives LLM Training: RLHF and Its AlternativesSebastian Raschka, PhDSep 10, 2023 “RLHF is an integral part of the modern LLM training pipeline due to its ability to incorporate human preferencesContinue readingWhat I Read: LLM Training, RLHF

What I Read: LLMs, single example

By Andrew Fairless on October 23, 2023September 9, 2023

https://www.fast.ai/posts/2023-09-04-learning-jumps/ Can LLMs learn from a single example?Jeremy Howard and Jonathan WhitakerSeptember 4, 2023 “We’ve noticed an unusual training pattern in fine-tuning LLMs. At first we thought it’s a bug,Continue readingWhat I Read: LLMs, single example

What I Read: LLMs

By Andrew Fairless on September 7, 2023August 1, 2023

https://willthompson.name/what-we-know-about-llms-primer What We Know About LLMs (Primer)Will Thompson (Twitter)July 23, 2023 “…it is worth reflecting on what we concretely know about LLMs at this point in time and how theseContinue readingWhat I Read: LLMs

What I Read: Gaussian Process, Active Learning in Physics

By Andrew Fairless on January 17, 2022December 11, 2021

https://towardsdatascience.com/gaussian-process-first-step-towards-active-learning-in-physics-239a8b260579?gi=41cc7e15ddd0 Gaussian Process: First Step Towards Active Learning in PhysicsMaxim ZiatdinovNov 1 “An approach to address these problems is a Gaussian Process…. we would like to offer a slightly unusualContinue readingWhat I Read: Gaussian Process, Active Learning in Physics

What I Read: Neural Text Generation

By Andrew Fairless on March 11, 2021March 7, 2021

https://lilianweng.github.io/lil-log/2021/01/02/controllable-neural-text-generation.html Controllable Neural Text GenerationJan 2, 2021Lilian Weng “How to steer a powerful unconditioned language model? In this post, we will delve into several approaches for controlled content generation withContinue readingWhat I Read: Neural Text Generation

What I Read: Best Practices for Building Machine Learning at Scale

By Andrew Fairless on January 24, 2021December 30, 2020

https://medium.com/dataseries/linkedins-pro-ml-architecture-summarizes-best-practices-for-building-machine-learning-at-scale-77fcb6afc9ec LinkedIn’s Pro-ML Architecture Summarizes Best Practices for Building Machine Learning at ScaleThe reference architecture is powering mission critical machine learning workflows within LinkedIn.Jesus RodriguezSep 17 “Building machine learning solutionsContinue readingWhat I Read: Best Practices for Building Machine Learning at Scale

What I Read: Autotuning Multi-Objective Optimization

By Andrew Fairless on January 19, 2021December 27, 2020

https://www.kdnuggets.com/2020/08/autotuning-multi-objective-optimization-linkedin-feed-ranking.html Autotuning for Multi-Objective Optimization on LinkedIn’s Feed RankingBy Marco Varela & Mavis Li, LinkedIn “First, we learned that in this particular optimization problem it pays to formulate your problemContinue readingWhat I Read: Autotuning Multi-Objective Optimization

What I Read: Exploring Bayesian Optimization

By Andrew Fairless on December 26, 2020December 13, 2020

https://distill.pub/2020/bayesian-optimization/ Exploring Bayesian OptimizationBreaking Bayesian Optimization into small, sizeable chunks.AuthorsApoorv AgnihotriIndian Insitute of Technology GandhinagarNipun BatraIndian Insitute of Technology GandhinagarPublishedMay 5, 2020DOI10.23915/distill.00026 “Many modern machine learning algorithms have a largeContinue readingWhat I Read: Exploring Bayesian Optimization

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