<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Azure AI on Cyril's Cloud &amp; AI Daily</title><link>https://cyrilbouharb.github.io/tags/azure-ai/</link><description>Recent content in Azure AI on Cyril's Cloud &amp; AI Daily</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Tue, 29 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://cyrilbouharb.github.io/tags/azure-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>Why content extraction still matters in the GenAI era</title><link>https://cyrilbouharb.github.io/posts/2026-09-29-why-content-extraction-still-matters-in-the-genai-era/</link><pubDate>Tue, 29 Sep 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-09-29-why-content-extraction-still-matters-in-the-genai-era/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;Microsoft Foundry&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;p&gt;The future of enterprise AI is not determined by the model you choose. It isdetermined by whether your agents can trust the content they act on.&lt;/p&gt;&#10;&lt;p&gt;Five years into the era of large language models, that thesis still holds. If&#10;anything, it is truer today than when we started. The models are stronger. The&#10;content is messier. Most of the real engineering lies in turning a raw PDF,&#10;image, or audio file into grounded, verifiable information an agent can act on.&lt;/p&gt;</description></item><item><title>Announcing Azure AI Speech LLM 2607: Better Multilingual Accuracy, Easier Customization</title><link>https://cyrilbouharb.github.io/posts/2026-09-10-announcing-azure-ai-speech-llm-2607-better-multilingual-accu/</link><pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-09-10-announcing-azure-ai-speech-llm-2607-better-multilingual-accu/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;Microsoft Foundry&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;p&gt;Azure AI Speech continues to deliver regular improvements to LLM Speech throughout the year, helping developers build more accurate and capable voice experiences. We’re announcingLLM Speech 2607, our latest model update, which brings improvements in multilingual recognition and mixed-language audio inputs, along with an enhanced experience for the phrase list feature.&lt;/p&gt;</description></item><item><title>Expanding the Reach of Document Translation – New Capabilities Announced at Microsoft Build</title><link>https://cyrilbouharb.github.io/posts/2026-06-03-expanding-the-reach-of-document-translation-new-capabilities/</link><pubDate>Wed, 03 Jun 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-06-03-expanding-the-reach-of-document-translation-new-capabilities/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;Microsoft Foundry&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;p&gt;Our commitment to advancing cross-language communication takes another major step forward at Microsoft Build. Azure Translator in Foundry Tools is expanding Document Translation with a set of new capabilities designed to meet enterprises where their content lives today — across formats, modalities, and languages. From large language model–powered translations to native image translation and expanded structured content support, these updates help organizations translate more of what they produce, with higher fidelity and less friction.&lt;/p&gt;</description></item><item><title>Azure Translator: Improving Translation Quality with Adaptive Datasets and Few‑Shot Learning</title><link>https://cyrilbouharb.github.io/posts/2026-06-02-azure-translator-improving-translation-quality-with-adaptive/</link><pubDate>Tue, 02 Jun 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-06-02-azure-translator-improving-translation-quality-with-adaptive/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;Microsoft Foundry&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;p&gt;Your healthcare app needs “La médica” not “El médico.” Your legal documents need precise terminology, not generic translations. When domain-specific language matters, generic LLM translation falls short.&lt;/p&gt;&#10;&lt;p&gt;Azure Translator’s adaptive translation lets you teach the model your terminology with just a handful of examples—no model training required. In this walkthrough, you’ll create an adaptive dataset, compare baseline vs. adapted translations side-by-side, and see exactly how much difference domain context makes.&lt;/p&gt;</description></item><item><title>Chat History Storage Patterns in Microsoft Agent Framework</title><link>https://cyrilbouharb.github.io/posts/2026-04-24-chat-history-storage-patterns-in-microsoft-agent-framework/</link><pubDate>Fri, 24 Apr 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-04-24-chat-history-storage-patterns-in-microsoft-agent-framework/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;Azure OpenAI &amp;amp; GPT Models&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;p&gt;When people talk about building AI agents, they usually focus on models, tools, and prompts. In practice, one of the most important architectural decisions is much simpler:where does the conversation history live?&lt;/p&gt;</description></item><item><title>Introducing Toolboxes in Foundry</title><link>https://cyrilbouharb.github.io/posts/2026-04-22-introducing-toolboxes-in-foundry/</link><pubDate>Wed, 22 Apr 2026 00:00:00 +0000</pubDate><guid>https://cyrilbouharb.github.io/posts/2026-04-22-introducing-toolboxes-in-foundry/</guid><description>&lt;p&gt;There&amp;rsquo;s been an important development in the &lt;strong&gt;GitHub Copilot&lt;/strong&gt; space that caught my attention, and I wanted to break it down — not just what was announced, but why it matters and how it fits into the bigger picture.&lt;/p&gt;&#10;&lt;h2 id="whats-new"&gt;What&amp;rsquo;s New&lt;/h2&gt;&#10;&lt;h3 id="available-in-public-preview-today"&gt;Available in Public Preview Today&lt;/h3&gt;&#10;&lt;p&gt;Toolbox is a new way tocurate, configure, and reusetools across all of your AI agents without rewiring them every time from Foundry.&lt;/p&gt;&#10;&lt;p&gt;Today, teams build agents across different frameworks and runtimes. Each agent often wires tools directly, with its own authentication, credentials, and integration code. As organizations scale agent usage, this leads to duplicated work, inconsistent behavior, and fragile production deployments.&lt;/p&gt;</description></item></channel></rss>