<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Transformers on Vadzim Belski — AI Research &amp; Engineering</title><link>https://belski.me/tags/transformers/</link><description>Recent content in Transformers on Vadzim Belski — AI Research &amp; Engineering</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://belski.me/tags/transformers/index.xml" rel="self" type="application/rss+xml"/><item><title>Transformer Architectures for HealthIT and Finance: An Architect's Field Guide</title><link>https://belski.me/blog/transformer_architectures_classical_modern_nlp_healthit_finance/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://belski.me/blog/transformer_architectures_classical_modern_nlp_healthit_finance/</guid><description>&lt;p&gt;A few months ago I was sitting in a client call with a hospital CTO who had just approved a budget to "deploy an LLM for everything." ICD-10 coding, PHI de-identification, discharge summaries, triage notes — all of it through one big decoder model. I asked him one question: "What's your inference budget per request?" He went quiet. That silence told me everything I needed to know about where this was going.&lt;/p&gt;</description></item></channel></rss>