2024-04-03
- Richard Seroter
(from Richard Seroter Blog)
Today's links look at which JavaScript web framework is best, how to correctly review a pull request, and what you should know about vector search.
Today’s reading list has some depth to it, with many long articles. But, there’s a lot of wisdom in the items you’ll find here. Pick a couple to dig into.
[article] What’s the best JavaScript framework? “Best” is relative, but all these frameworks aren’t the same. I liked this evaluation and comparison. Read this for an understanding of the different approaches these frameworks take, and maybe take a new one for a spin.
[article] Leading a Company That Can Thrive in a Chaotic World. Most of you probably don’t feel like you’re in a predictable sector or environment. It’s wild out there. Here’s an article on ways you can set up a team/company to handle it better.
[blog] How to correctly review a pull request. This is helpful advice for engineering teams that want to be better at reviewing pull requests for code changes.
[docs] Build and deploy generative AI and machine learning models in an enterprise. Read through this for a rich MLOps reference blueprint. It includes links to a repo with Terraform scripts and notebooks.
[blog] On Developer Marketing. Very good take from Lee. Marketing to developers is different than the efforts towards other personas.
[article] Uncovering the Seams in Mainframes for Incremental Modernisation: Internal Interfaces. This article keeps getting updated with more content. The latest addition looks at internal data interfaces that you can shift from the mainframe.
[article] Vector Search: What You Need to Know Before Getting Started. We don’t all need to become experts on vector databases, but it’s useful to know some fundamentals.
[article] Survival Strategies for the Noisy Neighbor Apocalypse. Here’s a detailed look at detecting and mitigating a noisy neighbor in a multi-tenant environment at Netflix.
[article] How Should We Define ‘Open’ AI? Does it matter if AI models claiming to be “open source AI” don’t meet the definition? Many won’t care. It’s a blurry space at the moment.
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[Blogs]
🌎 https://seroter.com/2024/04/02/daily-reading-list-april-2-2024-289/
[🧠] [v2] article_embedding_description: {:llm_project_id=>"Unavailable", :llm_dimensions=>nil, :article_size=>4086, :llm_embeddings_model_name=>"textembedding-gecko"}
[🧠] [v1/3] title_embedding_description: {:ricc_notes=>"[embed-v3] Fixed on 9oct24. Only seems incompatible at first glance with embed v1.", :llm_project_id=>"unavailable possibly not using Vertex", :llm_dimensions=>nil, :article_size=>4086, :poly_field=>"title", :llm_embeddings_model_name=>"textembedding-gecko"}
[🧠] [v1/3] summary_embedding_description: {:ricc_notes=>"[embed-v3] Fixed on 9oct24. Only seems incompatible at first glance with embed v1.", :llm_project_id=>"unavailable possibly not using Vertex", :llm_dimensions=>nil, :article_size=>4086, :poly_field=>"summary", :llm_embeddings_model_name=>"textembedding-gecko"}
[🧠] As per bug https://github.com/palladius/gemini-news-crawler/issues/4 we can state this article belongs to titile/summary version: v3 (very few articles updated on 9oct24)
{"id"=>5264,
"title"=>"Daily Reading List – April 2, 2024 (#289)",
"summary"=>"Today's links look at which JavaScript web framework is best, how to correctly review a pull request, and what you should know about vector search.",
"content"=>"\nToday’s reading list has some depth to it, with many long articles. But, there’s a lot of wisdom in the items you’ll find here. Pick a couple to dig into.
\n\n\n\n[article] What’s the best JavaScript framework? “Best” is relative, but all these frameworks aren’t the same. I liked this evaluation and comparison. Read this for an understanding of the different approaches these frameworks take, and maybe take a new one for a spin.
\n\n\n\n[article] Leading a Company That Can Thrive in a Chaotic World. Most of you probably don’t feel like you’re in a predictable sector or environment. It’s wild out there. Here’s an article on ways you can set up a team/company to handle it better.
\n\n\n\n[blog] How to correctly review a pull request. This is helpful advice for engineering teams that want to be better at reviewing pull requests for code changes.
\n\n\n\n[docs] Build and deploy generative AI and machine learning models in an enterprise. Read through this for a rich MLOps reference blueprint. It includes links to a repo with Terraform scripts and notebooks.
\n\n\n\n[blog] On Developer Marketing. Very good take from Lee. Marketing to developers is different than the efforts towards other personas.
\n\n\n\n[article] Uncovering the Seams in Mainframes for Incremental Modernisation: Internal Interfaces. This article keeps getting updated with more content. The latest addition looks at internal data interfaces that you can shift from the mainframe.
\n\n\n\n[article] Vector Search: What You Need to Know Before Getting Started. We don’t all need to become experts on vector databases, but it’s useful to know some fundamentals.
\n\n\n\n[article] Survival Strategies for the Noisy Neighbor Apocalypse. Here’s a detailed look at detecting and mitigating a noisy neighbor in a multi-tenant environment at Netflix.
\n\n\n\n[article] How Should We Define ‘Open’ AI? Does it matter if AI models claiming to be “open source AI” don’t meet the definition? Many won’t care. It’s a blurry space at the moment.
\n\n\n\n##
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