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Imagine finding out your old bookshelf is suddenly valuable to AI.

That's the kind of strange place the AI race is taking us. And once you start looking around, the stories get even more unexpected.

Here's what else happened in AI while you were busy.

— Oren Etzioni

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Amazon started by selling books. Now some rare books are reportedly being bought, stripped apart, scanned, and destroyed so their contents can help train AI. An investigation tracked one such book to an Amazon facility, turning a very old-school source of knowledge into surprisingly disposable AI training data.

You won't see it, but Claude's newest text can now carry an invisible watermark. Anthropic says the system subtly changes word-selection probabilities so generated text can later be detected, adding a new layer to the growing fight over how we identify AI-written content.

The AI race needs an absurd amount of computing power, and Nvidia is putting serious money behind it. The chip giant is backing up to $105 billion in financing for an OpenAI data-center project in Ohio, showing just how enormous the infrastructure bill behind frontier AI is becoming.

OpenAI isn't only building AI anymore. It's also funding 14 independent projects exploring how governments and society should deal with an AI-driven economy, from economic opportunity to resilience. The bigger question is who gets to shape the rules before AI changes them for us.

Discover how you can leverage ChatGPT to boost efficiency, streamline tasks, and stay ahead in your industry. Supercharge your productivity with HubSpot's comprehensive guide.

That sounds futuristic until you hear researchers describe children treating Alexa and smart toys like friends with their own minds and personalities. One MIT researcher found that kids often interact with these systems as if they're social beings, which makes it even more important to help them understand what is actually happening behind the friendly voice.

The goal isn't to keep kids away from AI. It's to teach them to poke at it, question its answers, test its limits, and understand that the machine doesn't always know best.

Google just published its developer guide for Gemini 3.7 Flash, showing how developers can use the model for coding, debugging, web apps, design workflows, and AI agents. It also breaks down when to use low, medium, or high thinking levels depending on how much reasoning a task needs.

The guide gives developers a practical look at where Gemini 3.7 Flash fits, from everyday coding to autonomous agent workflows, with introductory API pricing starting at $0.75 per million input tokens.

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