<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic From General Intelligence to Specific Intelligence: Context, Ontology, and the Enterprise AI Layer in MVP Articles</title>
    <link>https://community.databricks.com/t5/mvp-articles/from-general-intelligence-to-specific-intelligence-context/m-p/157446#M197</link>
    <description>&lt;P&gt;I watched Databricks CEO, Ali Ghodsi’s interview on Mad Money, with Jim Cramer, and was inspired by a point that aligns closely with what we hear from clients every day:&amp;nbsp;“AI doesn’t have an intelligence problem. It has a context problem.”&lt;/P&gt;&lt;P&gt;That is exactly the enterprise challenge: how do we make AI understand the specific context of our business?&lt;/P&gt;&lt;P&gt;A foundation model may understand the word revenue, but does it know how your company defines it? Does it know the certified source, the metric logic, the fiscal calendar, the region hierarchy, and the governance rules?&lt;/P&gt;&lt;P&gt;That is where ontology and semantic layers become critical.&lt;/P&gt;&lt;P&gt;In my latest &lt;A href="https://medium.com/@sudhir.gajre/from-general-intelligence-to-specific-intelligence-context-ontology-and-the-enterprise-ai-layer-ffce5c719260" target="_self"&gt;blog&lt;/A&gt;, I explore how context turns general intelligence into specific intelligence, and why technologies like Databricks Genie, Agent Bricks, DSPy, and Recursive Language Models matter for enterprise AI.&lt;/P&gt;&lt;P&gt;The future of AI is not just better models.&amp;nbsp;It is better context.&lt;/P&gt;</description>
    <pubDate>Thu, 21 May 2026 20:01:11 GMT</pubDate>
    <dc:creator>Sudhir_G</dc:creator>
    <dc:date>2026-05-21T20:01:11Z</dc:date>
    <item>
      <title>From General Intelligence to Specific Intelligence: Context, Ontology, and the Enterprise AI Layer</title>
      <link>https://community.databricks.com/t5/mvp-articles/from-general-intelligence-to-specific-intelligence-context/m-p/157446#M197</link>
      <description>&lt;P&gt;I watched Databricks CEO, Ali Ghodsi’s interview on Mad Money, with Jim Cramer, and was inspired by a point that aligns closely with what we hear from clients every day:&amp;nbsp;“AI doesn’t have an intelligence problem. It has a context problem.”&lt;/P&gt;&lt;P&gt;That is exactly the enterprise challenge: how do we make AI understand the specific context of our business?&lt;/P&gt;&lt;P&gt;A foundation model may understand the word revenue, but does it know how your company defines it? Does it know the certified source, the metric logic, the fiscal calendar, the region hierarchy, and the governance rules?&lt;/P&gt;&lt;P&gt;That is where ontology and semantic layers become critical.&lt;/P&gt;&lt;P&gt;In my latest &lt;A href="https://medium.com/@sudhir.gajre/from-general-intelligence-to-specific-intelligence-context-ontology-and-the-enterprise-ai-layer-ffce5c719260" target="_self"&gt;blog&lt;/A&gt;, I explore how context turns general intelligence into specific intelligence, and why technologies like Databricks Genie, Agent Bricks, DSPy, and Recursive Language Models matter for enterprise AI.&lt;/P&gt;&lt;P&gt;The future of AI is not just better models.&amp;nbsp;It is better context.&lt;/P&gt;</description>
      <pubDate>Thu, 21 May 2026 20:01:11 GMT</pubDate>
      <guid>https://community.databricks.com/t5/mvp-articles/from-general-intelligence-to-specific-intelligence-context/m-p/157446#M197</guid>
      <dc:creator>Sudhir_G</dc:creator>
      <dc:date>2026-05-21T20:01:11Z</dc:date>
    </item>
  </channel>
</rss>

