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    <lastBuildDate>Sun, 19 Apr 2026 03:15:17 GMT</lastBuildDate>
    
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      <title><![CDATA[Amazon vs. Perplexity: The Fight Over AI Shopping Bots Explained]]></title>
      <link>https://hackerthink.com/news/amazon-vs-perplexity-the-fight-over-ai-shopping-bots-explained</link>
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      <description><![CDATA[Amazon has fired the first legal shot against an AI company, threatening Perplexity over its AI shopping assistant, Comet. The issue? Perplexity's bot doesn't identify itself when browsing Amazon, violating the site's terms of service. But this fight is about more than rule-breaking—it's about control. Amazon claims Perplexity needs to follow the same rules as other automated services. Perplexity says Amazon just wants to block competitors and protect its ad revenue. The outcome could define how AI bots interact with the entire internet.]]></description>
      <pubDate>Wed, 05 Nov 2025 11:52:16 GMT</pubDate>
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      <title><![CDATA[OpenAI Just Spent $600 Billion on Computer Power—Here's What That Means]]></title>
      <link>https://hackerthink.com/news/openai-just-spent-600-billion-on-computer-powerheres-what-that-means</link>
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      <description><![CDATA[OpenAI just committed $600 billion across three cloud computing giants—$300 billion to Oracle, $250 billion to Microsoft, and $38 billion to Amazon. This massive spending spree reveals a harsh truth: the computer chips needed to power AI have become a scarce resource. Even with billions to spend, OpenAI won't have all its computing power until 2026. For other businesses, the message is clear: don't try to build your own AI infrastructure, don't rely on one cloud provider, and treat AI spending like a major capital investment.]]></description>
      <pubDate>Wed, 05 Nov 2025 11:31:04 GMT</pubDate>
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      <title><![CDATA[Companies Are Wasting Money on AI Because the Tests Are Broken]]></title>
      <link>https://hackerthink.com/news/companies-are-wasting-money-on-ai-because-the-tests-are-broken</link>
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      <description><![CDATA[Companies are pouring millions into AI systems based on test scores that don't actually work. A groundbreaking study of 445 AI benchmarks reveals that nearly all have serious flaws—they don't measure what they claim to measure. From vague definitions to memorized answers, these broken tests are leading businesses to make expensive mistakes. If you're evaluating AI for your organization, the public leaderboards you're relying on might be steering you wrong. Here's what's broken and how to fix it.]]></description>
      <pubDate>Wed, 05 Nov 2025 10:40:04 GMT</pubDate>
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