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    <loc>https://www.exavoice.eu/blog-1/qualia-intel-featured-piece-wkmbw</loc>
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      <image:title>Blog - QUALIA INTEL LAST FEATURED PIECE.</image:title>
      <image:caption>AGI: Power without Definition. A short visual dossier, June 2026. The starting point was The AI Con (2025) by Emily Bender and Alex Hanna — a computational linguist and a sociologist, two of the most prominent critics of contemporary AI narratives. One of the book's strongest contributions, in my view (I take the idea, not the whole position), is its critique of AGI as a vague and rhetorically productive concept. So I pulled the thread and updated it with current information. What follows is the dossier as published on Instagram: the polyphony of clashing positions around AGI — from "already here" to industry pivot — and the question underneath them all: what decisions are taken in the term's name?</image:caption>
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    <loc>https://www.exavoice.eu/blog-1/thegeodiaries</loc>
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    <lastmod>2026-05-30</lastmod>
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      <image:title>Blog - The GEO Diaries - On the GEO front:</image:title>
      <image:caption>This is where I work on Generative Engine Optimization questions, one idea at a time, dropping notes “every some time”. And I call it “the GEO front” because the term and related practices are in the painful process of getting defined (or rejected, and refined) through power plays between platforms and SEO practitioners, while academia is overshadowed by the industry. Beyond best practices, I’m watching the weird basement where knowledge now gets processed: how AI is changing the path information takes before it reaches us, and what gets … well, lost in translation.</image:caption>
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    <loc>https://www.exavoice.eu/blog-1/content-authentication</loc>
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    <lastmod>2026-06-10</lastmod>
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      <image:title>Blog - SHOULD WE AUTHENTICATE CONTENT?</image:title>
      <image:caption>Qualia’s featured carousel attempts to map a problem far bigger than any slide can hold: how AI-generated images collide with memory, trust, and visual evidence. It grew out of a Leica-organized discussion I attended on the role of the photographer in the face of risks posed by AI-generated fake images, with photographers Álvaro Ybarra and Rodrigo Rivas (Madrid, 18–19 September 2025).</image:caption>
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    <loc>https://www.exavoice.eu/blog-1/ai-more-original</loc>
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    <lastmod>2026-04-13</lastmod>
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      <image:caption>Generated with Midjourney.</image:caption>
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      <image:title>Blog - AI, MORE ORIGINAL - Here’s where RAG (Retrieval Augmented Generation) came into play. Think of RAG as a key to fixing so-called “AI’s hallucinations”. RAG makes generative AI accurate and more reliable. Instead of letting an AI rely on what it already knows (or better said, what it probabilistically can predict based on its training), the process known as RAG consists in actively pulling in external, fresh, relevant data. First, RAG fetches facts from an authoritative knowledge base (like Semantic Scholar). Then, it uses those facts to generate something new, ensuring the ideas are both grounded and compelling in their form. This makes it perfect for tasks where up-to-date or highly specific information is critical—like summarizing new research papers, answering niche technical questions, or brainstorming ideas in fields where the landscape is always changing.</image:title>
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      <image:title>Blog - AI, MORE ORIGINAL - AI Ideas win on novelty: AI ideas were rated significantly more novel than human ones (5.64 vs. 4.84, p &lt; 0.05). Feasibility—a near draw?: Humans edged out AI slightly (6.61 vs. 6.34), but the difference wasn’t statistically significant. Excitement and overall scores: AI ideas scored higher on excitement (5.19 vs. 4.55) and overall performance (4.85 vs. 4.68) in some tests. Human-AI teamwork FTW: When humans reranked AI ideas, scores improved even further—novelty hit 5.81, and overall score rose to 5.34.</image:title>
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