<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Embed on Neat Guy Coding</title><link>https://neatguycoding.com/tags/embed/</link><description>Recent content in Embed on Neat Guy Coding</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 NeatGuyCoding</copyright><lastBuildDate>Mon, 18 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://neatguycoding.com/tags/embed/index.xml" rel="self" type="application/rss+xml"/><item><title>Engineering Trade-offs in Retrieval Embeddings: Leaderboards, Training, and Production Constraints via Arctic Embed</title><link>https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-arctic-embed-with-luke-merrick-puxuan-yu-and-charles-pierse-weaviate-pod/</link><pubDate>Mon, 18 May 2026 00:00:00 +0000</pubDate><guid>https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-arctic-embed-with-luke-merrick-puxuan-yu-and-charles-pierse-weaviate-pod/</guid><description>Engineering trade-offs in retrieval embeddings: how to read leaderboards, what contrastive pre-training and fine-tuning each solve, how Matryoshka representation learning scales to billion-vector indexes, and the gap between multilingual benchmarks and proprietary distributions—grounded in Snowflake Arctic Embed and the Weaviate podcast.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-arctic-embed-with-luke-merrick-puxuan-yu-and-charles-pierse-weaviate-pod/cover.png"/></item></channel></rss>