large language model – Page 4 – Andrew Fairless, Ph.D.

What I Read: LLM evaluation

By Andrew Fairless on October 21, 2024July 22, 2024

https://hamel.dev/blog/posts/evals Your AI Product Needs EvalsHow to construct domain-specific LLM evaluation systems.Hamel HusainMarch 29, 2024 “…I’ve seen many successful and unsuccessful approaches to building LLM products. I’ve found that unsuccessfulContinue readingWhat I Read: LLM evaluation

What I Read: Data Flywheels, LLM

By Andrew Fairless on October 17, 2024July 20, 2024

https://www.sh-reya.com/blog/ai-engineering-flywheel Data Flywheels for LLM ApplicationsShreya ShankarJul 1, 2024 “This diagram illustrates my (idealized) architecture of an LLM pipeline, from input processing through evaluation and logging. It showcases ideas I’llContinue readingWhat I Read: Data Flywheels, LLM

What I Read: Improving Language Models, Practical Size

By Andrew Fairless on October 15, 2024July 14, 2024

https://amaarora.github.io/posts/2024-07-07%20Gemma.html Gemma 2, Improving Open Language Models at a Practical SizeAman AroraJuly 9, 2024 “…we take a deep dive into the architectural components of Gemma 2 such as Grouped QueryContinue readingWhat I Read: Improving Language Models, Practical Size

What I Read: Extrinsic Hallucinations, LLMs

By Andrew Fairless on October 7, 2024July 14, 2024

https://lilianweng.github.io/posts/2024-07-07-hallucination Extrinsic Hallucinations in LLMsLilian WengJuly 7, 2024 “This post focuses on extrinsic hallucination. To avoid hallucination, LLMs need to be (1) factual and (2) acknowledge not knowing the answerContinue readingWhat I Read: Extrinsic Hallucinations, LLMs

What I Read: What can LLMs never do?

By Andrew Fairless on October 1, 2024July 14, 2024

https://www.strangeloopcanon.com/p/what-can-llms-never-do What can LLMs never do?Rohit KrishnanApr 23, 2024 “Every time over the past few years that we came up with problems LLMs can’t do, they passed them with flyingContinue readingWhat I Read: What can LLMs never do?

What I Read: bare metal to 70B

By Andrew Fairless on September 25, 2024July 8, 2024

https://imbue.com/research/70b-infrastructure From bare metal to a 70B model: infrastructure set-up and scriptsThe Imbue TeamJune 25, 2024 “…we trained a 70B parameter model from scratch on our own infrastructure that outperformedContinue readingWhat I Read: bare metal to 70B

What I Read: Detecting hallucinations, LLMs, semantic entropy

By Andrew Fairless on September 23, 2024July 8, 2024

https://oatml.cs.ox.ac.uk/blog/2024/06/19/detecting_hallucinations_2024.html Detecting hallucinations in large language models using semantic entropySebastian Farquhar, Jannik Kossen, Lorenz Kuhn, Yarin Gal19 Jun 2024 “We show how one can use uncertainty to detect confabulations.”

What I Read: Structured Generation, LLMs

By Andrew Fairless on September 19, 2024July 8, 2024

https://blog.dottxt.co/coding-for-structured-generation.html Coding For Structured Generation with LLMsWill Kurt2024-06-21 “In this post we’re going to go through an example that shows not only how to use structured generation in your LLMContinue readingWhat I Read: Structured Generation, LLMs

What I Read: Musings on AI Engineering

By Andrew Fairless on September 16, 2024June 29, 2024

https://www.sh-reya.com/blog/ai-engineering-short Short Musings on AI Engineering and “Failed AI Projects”Shreya ShankarJun 24, 2024 “When we studied the traditional MLOps lifecycle, we found one common pattern across all successful ML products—theirContinue readingWhat I Read: Musings on AI Engineering

What I Read: LLMs train LLMs

By Andrew Fairless on September 4, 2024June 15, 2024

https://sakana.ai/llm-squared Can LLMs invent better ways to train LLMs?Sakana AIJune 13, 2024 “…LLMs themselves have grown increasingly capable of generating hypotheses and writing code. This raises an intriguing question: canContinue readingWhat I Read: LLMs train LLMs

Tag: large language model