<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>large language models &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/tag/large-language-models/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Sat, 25 Oct 2025 22:01:00 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.2</generator>
	<item>
		<title>Post-Training Generative Recommenders with Advantage-Weighted Supervised Finetuning</title>
		<link>https://noise.getoto.net/2025/10/26/post-training-generative-recommenders-with-advantage-weighted-supervised-finetuning/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Sat, 25 Oct 2025 21:32:37 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[Recommendations]]></category>
		<category><![CDATA[reinforcement-learning]]></category>
		<guid isPermaLink="false">https://medium.com/p/61a538d717a9</guid>

					<description><![CDATA[Author: Keertana Chidambaram, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya(*The work was done when Keertana interned at Netflix.)IntroductionThis blog focuses on post-training generative recommender systems. Generative recommenders (GRs) represent a ...]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Using generative AI to teach computing: Insights from research</title>
		<link>https://noise.getoto.net/2024/11/07/using-generative-ai-to-teach-computing-insights-from-research/</link>
		
		<dc:creator><![CDATA[Katharine Childs]]></dc:creator>
		<pubDate>Thu, 07 Nov 2024 11:27:57 +0000</pubDate>
				<category><![CDATA[generative ai tools]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[research]]></category>
		<category><![CDATA[research seminar]]></category>
		<guid isPermaLink="false">https://www.raspberrypi.org/?p=88838</guid>

					<description><![CDATA[<p>As computing technologies continue to rapidly evolve in today’s digital world, computing education is becoming increasingly essential. Arto Hellas and Juho Leinonen, researchers at Aalto University in Finland, are exploring how innovative teaching methods can equip students with the computing skills they need to stay ahead. In particular, they are looking at how generative AI…</p>
<p>The post <a href="https://www.raspberrypi.org/blog/using-generative-ai-to-teach-computing-insights-from-research/">Using generative AI to teach computing: Insights from research</a> appeared first on <a href="https://www.raspberrypi.org/">Raspberry Pi Foundation</a>.</p>]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How to build an enterprise LLM application: Lessons from GitHub Copilot</title>
		<link>https://noise.getoto.net/2023/09/06/how-to-build-an-enterprise-llm-application-lessons-from-github-copilot/</link>
		
		<dc:creator><![CDATA[Shuyin Zhao]]></dc:creator>
		<pubDate>Wed, 06 Sep 2023 19:04:19 +0000</pubDate>
				<category><![CDATA[Engineering]]></category>
		<category><![CDATA[GitHub Copilot]]></category>
		<category><![CDATA[How GitHub builds GitHub]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[LLM]]></category>
		<guid isPermaLink="false">https://github.blog/?p=73994</guid>

					<description><![CDATA[<p>The team behind GitHub Copilot shares its lessons for building an LLM app that delivers value to both individuals and enterprise users at scale. </p>
<p>The post <a rel="nofollow" href="https://github.blog/2023-09-06-how-to-build-an-enterprise-llm-application-lessons-from-github-copilot/">How to build an enterprise LLM application: Lessons from GitHub Copilot</a> appeared first on <a rel="nofollow" href="https://github.blog/">The GitHub Blog</a>.</p>]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>A developer’s guide to prompt engineering and LLMs</title>
		<link>https://noise.getoto.net/2023/07/17/a-developers-guide-to-prompt-engineering-and-llms/</link>
		
		<dc:creator><![CDATA[Albert Ziegler]]></dc:creator>
		<pubDate>Mon, 17 Jul 2023 14:27:15 +0000</pubDate>
				<category><![CDATA[Company]]></category>
		<category><![CDATA[Engineering]]></category>
		<category><![CDATA[GitHub Copilot]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[LLM]]></category>
		<category><![CDATA[Product]]></category>
		<category><![CDATA[prompt engineering]]></category>
		<guid isPermaLink="false">https://github.blog/?p=73105</guid>

					<description><![CDATA[Prompt engineering is the art of communicating with a generative AI model. In this article, we’ll cover how we approach prompt engineering at GitHub, and how you can use it to build your own LLM-based application.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How GitHub Copilot is getting better at understanding your code</title>
		<link>https://noise.getoto.net/2023/05/17/how-github-copilot-is-getting-better-at-understanding-your-code/</link>
		
		<dc:creator><![CDATA[Johan Rosenkilde]]></dc:creator>
		<pubDate>Wed, 17 May 2023 17:32:16 +0000</pubDate>
				<category><![CDATA[Engineering]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[GitHub Copilot]]></category>
		<category><![CDATA[How GitHub builds GitHub]]></category>
		<category><![CDATA[large language models]]></category>
		<category><![CDATA[LLM]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[Product]]></category>
		<guid isPermaLink="false">https://github.blog/?p=71978</guid>

					<description><![CDATA[With a new Fill-in-the-Middle paradigm, GitHub engineers improved the way GitHub Copilot contextualizes your code. By continuing to develop and test advanced retrieval algorithms, they’re working on making our AI tool even more advanced.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/

Object Caching 43/129 objects using Memcached
Page Caching using Disk: Enhanced 
Lazy Loading (feed)
Database Caching using Memcached

Served from: noise.getoto.net @ 2025-12-07 21:35:39 by W3 Total Cache
-->