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		<title>Document Scoring on AIBussin — AI applications, systems and books</title>
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				<title>Self-Improving AI: A System That Learns, Validates, and Retrains Itself</title>
				<link>https://aibussin.com/post/rivals/</link>
				<pubDate>Mon, 30 Jun 2025 10:13:03 +0100</pubDate>
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				<description>&lt;h2 id=&#34;-the-static-ai-trap&#34;&gt;🤖 &lt;strong&gt;The Static AI Trap&lt;/strong&gt;&lt;/h2&gt;&#xA;&lt;p&gt;Today’s AI systems are frozen in time: trained once, deployed forever. Yet the real world never stops evolving. Goals shift overnight. New research upends old truths. Context transforms without warning.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What if your AI could wake up?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;In this post, we engineer an intelligence that &lt;strong&gt;teaches itself&lt;/strong&gt;   a system that continuously learns from the web, audits its own judgments, and retrains itself when confidence wavers.&lt;/p&gt;</description>
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				<title>Document Intelligence: Turning Documents into Structured Knowledge</title>
				<link>https://aibussin.com/post/docs/</link>
				<pubDate>Tue, 17 Jun 2025 23:31:13 +0100</pubDate>
				<guid>https://aibussin.com/post/docs/</guid>
				<description>&lt;h2 id=&#34;-summary&#34;&gt;📖 Summary&lt;/h2&gt;&#xA;&lt;p&gt;Imagine drowning in a sea of research papers, each holding a fragment of the knowledge you need for your next breakthrough. How does an AI system, striving for self-improvement, navigate this information overload to find precisely what it needs? This is the core challenge our Document Intelligence pipeline addresses, transforming chaotic documents into organized, searchable knowledge.&lt;/p&gt;&#xA;&lt;p&gt;In this post we combine insights from &lt;a href=&#34;https://arxiv.org/pdf/2505.21497&#34; target=&#34;_blank&#34; class=&#34;paper-badge&#34;&#xA;    style=&#34;display: inline-block; padding: 6px 10px; background: #f3f4f6; border-left: 4px solid #3b82f6; border-radius: 4px; margin: 4px 0; text-decoration: none; color: #1f2937;&#34;&gt;&#xA;    &lt;strong&gt;Paper2Poster&lt;/strong&gt;: Towards Multimodal Poster Automation from Scientific Papers&#xA;&lt;/a&gt; and&#xA;&lt;a href=&#34;https://arxiv.org/abs/2506.10952&#34; target=&#34;_blank&#34; class=&#34;paper-badge&#34;&#xA;    style=&#34;display: inline-block; padding: 6px 10px; background: #f3f4f6; border-left: 4px solid #3b82f6; border-radius: 4px; margin: 4px 0; text-decoration: none; color: #1f2937;&#34;&gt;&#xA;    &lt;strong&gt;Domain2Vec&lt;/strong&gt;: Vectorizing Datasets to Find the Optimal Data Mixture without Training&#xA;&lt;/a&gt; to build an AI document profiler that transforms unstructured papers into structured, searchable knowledge graphs.&lt;/p&gt;</description>
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