🐭 The Mouse is Free
The duck is next
Welcome to the fifty eights ever issue of Monday Morning Data Science from the Fred Hutch Data Science Laboratory. We are excited to show you what we have been working on (Fresh from the Lab), plus links that we think you would be interested in (Our Weekly Bookmarks Bar). Part of the purpose of this newsletter is to start conversations, so if you have a question or there is something you would like to share with us please let us know by responding directly to this email.
Our Weekly Bookmarks Bar
[Blog Post: Happy Public Domain Day 2024] The Public Domain Review celebrates Public Domain Day 2024, highlighting the entry of various works into the public domain. This includes the original 1928 version of Mickey Mouse in "Steamboat Willie", works of authors who died in 1953 (in countries with a copyright term of "life plus 70 years"), and a range of literary and artistic works from 1928, each significant in different cultural and historical contexts.
[Article: Bash One-Liners for LLMs] This post on Justine Tunney's website describes her collaboration with Mozilla to launch an open source project called llamafile, which enables running large language models (LLMs) on personal computers. The post details various Bash one-liners for tasks such as image summarization, filename generation, URL summarization, and more, showcasing the flexibility and utility of llamafile in handling diverse tasks with LLMs. Click the link above for detailed information and examples.
[Blog Post: What are Embeddings and Why They Matter] Simon Willison explains embeddings, a key concept in machine learning, particularly in the context of Large Language Models (LLMs). Willison discusses how embeddings convert content into a fixed-length array of numbers representing coordinates in a multidimensional space, and explores various applications of this technology, such as building related content features, semantic searches, and vibes-based search engines, enhancing the functionality and scope of LLMs in practical scenarios.
As always you can contact us by replying directly to this email, you can contact the Data Science Lab at data@fredhutch.org, or you are welcome to join us on the Fred Hutch Data Slack Workspace. For more information about the Fred Hutch Data Science Lab, visit our website: https://hutchdatascience.org/. See you next week!
- The Fred Hutch Data Science Laboratory