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    <title>Ki-Modelle on VikoTool - AI Tools in Focus</title>
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    <description>Recent content in Ki-Modelle on VikoTool - AI Tools in Focus</description>
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      <title>Claude &#34;Kairos&#34; Agent, Opus 4.7 &amp; Ultraplan Leaked — Plus a Gemma-4 Breakthrough</title>
      <link>https://vikotool.com/en/posts/claude-opus-4-leak-kairos-agent-ultraplan/</link>
      <pubDate>Tue, 07 Apr 2026 13:33:08 +0100</pubDate>
      <guid>https://vikotool.com/en/posts/claude-opus-4-leak-kairos-agent-ultraplan/</guid>
      <description>&lt;h1 id=&#34;claude-kairos-agent-opus-47--ultraplan-leaked--plus-a-gemma-4-breakthrough&#34;&gt;Claude &amp;ldquo;Kairos&amp;rdquo; Agent, Opus 4.7 &amp;amp; Ultraplan Leaked — Plus a Gemma-4 Breakthrough&lt;/h1&gt;
&lt;h2 id=&#34;tldr&#34;&gt;TL;DR&lt;/h2&gt;
&lt;p&gt;A massive leak has surfaced revealing major upcoming Anthropic developments, including a new agent codenamed &amp;ldquo;Kairos,&amp;rdquo; a next-generation Opus 4.7 model, and a feature called &amp;ldquo;Ultraplan.&amp;rdquo; At the same time, Google&amp;rsquo;s Gemma-4 is making waves in the open-source AI space. According to the YouTube channel behind the latest breakdown video, these leaks point to an accelerating AI arms race that&amp;rsquo;s moving faster than most people expected heading into mid-2026.&lt;/p&gt;</description>
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    <item>
      <title>Xiaomi&#39;s MiMo AI Models Are Making the Pricing Conversation Very Uncomfortable</title>
      <link>https://vikotool.com/en/posts/xiaomi-mimo-ki-preiskampf-open-source-modelle/</link>
      <pubDate>Tue, 24 Mar 2026 09:05:10 +0100</pubDate>
      <guid>https://vikotool.com/en/posts/xiaomi-mimo-ki-preiskampf-open-source-modelle/</guid>
      <description>&lt;h1 id=&#34;xiaomis-mimo-ai-models-are-making-the-pricing-conversation-very-uncomfortable&#34;&gt;Xiaomi&amp;rsquo;s MiMo AI Models Are Making the Pricing Conversation Very Uncomfortable&lt;/h1&gt;
&lt;h2 id=&#34;tldr&#34;&gt;TL;DR&lt;/h2&gt;
&lt;p&gt;Xiaomi has entered the AI model race with two models — MiMo-V2-Flash and MiMo-V2-Pro — and they&amp;rsquo;re undercutting Western competitors on price by a significant margin. MiMo-V2-Flash claims the #1 spot among open-source models on SWE-Bench, a key coding benchmark, starting at just $0.10 per million input tokens. The community on Reddit is noticing, and the conversation is getting uncomfortable for established players. If Xiaomi&amp;rsquo;s pricing holds, it could reshape how developers and businesses think about AI API costs.&lt;/p&gt;</description>
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      <title>Switching AI Models Mid-Conversation: What Actually Happens to Your Context?</title>
      <link>https://vikotool.com/en/posts/zwischen-ki-modellen-wechseln-kontext-verlust/</link>
      <pubDate>Fri, 20 Mar 2026 14:36:49 +0100</pubDate>
      <guid>https://vikotool.com/en/posts/zwischen-ki-modellen-wechseln-kontext-verlust/</guid>
      <description>&lt;h1 id=&#34;switching-ai-models-mid-conversation-what-actually-happens-to-your-context&#34;&gt;Switching AI Models Mid-Conversation: What Actually Happens to Your Context?&lt;/h1&gt;
&lt;h2 id=&#34;tldr&#34;&gt;TL;DR&lt;/h2&gt;
&lt;p&gt;Switching between AI models mid-conversation is something users are actively experimenting with, but it comes with a significant catch: most platforms don&amp;rsquo;t preserve your context when you jump from one model to another. The Reddit community at r/artificial has been actively debating whether this workflow is actually practical or just a theoretical nice-to-have. A handful of tools — like Venice AI, Open WebUI, and OpenCraft AI — are specifically designed to solve this problem. Whether context loss is a dealbreaker depends entirely on what you&amp;rsquo;re trying to accomplish.&lt;/p&gt;</description>
    </item>
    <item>
      <title>Why LLMs Forget Your Instructions — And Why It Looks Exactly Like ADHD</title>
      <link>https://vikotool.com/en/posts/llm-vergisst-anweisungen-adhd-forschung/</link>
      <pubDate>Wed, 18 Mar 2026 09:05:48 +0100</pubDate>
      <guid>https://vikotool.com/en/posts/llm-vergisst-anweisungen-adhd-forschung/</guid>
      <description>&lt;h1 id=&#34;why-llms-forget-your-instructions--and-why-it-looks-exactly-like-adhd&#34;&gt;Why LLMs Forget Your Instructions — And Why It Looks Exactly Like ADHD&lt;/h1&gt;
&lt;h2 id=&#34;tldr&#34;&gt;TL;DR&lt;/h2&gt;
&lt;p&gt;A Reddit discussion in r/artificial is getting traction around a fascinating parallel: large language models forget instructions the same way ADHD brains do, and there&amp;rsquo;s actual research explaining why. The &amp;ldquo;Lost in the Middle&amp;rdquo; problem — where AI assistants like Claude drop earlier instructions during long sessions — isn&amp;rsquo;t a random glitch, it&amp;rsquo;s a structural feature of how these models process information. Understanding the neuroscience and ML research behind this could change how you prompt, how you build, and how you think about AI reliability. Tools like Agently are already trying to solve this at the enterprise level.&lt;/p&gt;</description>
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      <title>Six Months of Blind AI Model Reviews: What One Redditor Didn&#39;t Expect</title>
      <link>https://vikotool.com/en/posts/ai-modelle-blind-test-vergleich-ergebnisse/</link>
      <pubDate>Wed, 25 Feb 2026 09:11:06 +0100</pubDate>
      <guid>https://vikotool.com/en/posts/ai-modelle-blind-test-vergleich-ergebnisse/</guid>
      <description>&lt;p&gt;The Reddit source wasn&amp;rsquo;t fetched, so I&amp;rsquo;ll work strictly with the metadata and title available in the source package.&lt;/p&gt;
&lt;hr&gt;
&lt;h1 id=&#34;six-months-of-blind-ai-model-reviews-what-one-redditor-didnt-expect&#34;&gt;Six Months of Blind AI Model Reviews: What One Redditor Didn&amp;rsquo;t Expect&lt;/h1&gt;
&lt;h2 id=&#34;tldr&#34;&gt;TL;DR&lt;/h2&gt;
&lt;p&gt;A Reddit user in r/artificial spent six months running blind side-by-side comparisons between today&amp;rsquo;s leading AI models — Claude, GPT, and Gemini — without knowing which output came from which system. The experiment surfaced surprises that challenge how most people pick their AI tools. With 17 community comments and active discussion, the methodology itself has become as interesting as the results. If you&amp;rsquo;re still choosing AI tools based on brand loyalty or benchmark screenshots, this is worth a read.&lt;/p&gt;</description>
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