AI field notes
Reporting and context on AI tools, creative work, and the limits behind the headlines.
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43 articles · Page 4 of 4
One API Key for the Whole Pipeline: Streaming TTS, Image, and Transcription Without the Chunking Tax
A Japanese AI platform shows a useful pattern for creator tools: a single OpenAI-compatible key that covers image generation, long-form text-to-speech, and transcription. The interesting parts are streaming long audio without chunking, reference-image character consistency, and an API design built around predictable budgets.
Google Made Visible Watermarks Optional: What Creators Should Actually Do
Google announced a Media Watermark setting in Gemini that lets you switch off the visible AI watermark, with access rolling out over the coming days. The invisible SynthID and C2PA layers stay. What changed, where the setting lives, and how to decide when to use it.
Inference Is Forecast to Overtake Training. What That Means for AI Image Generation
AI-optimized IaaS spending is forecast to pass training spending for the first time in 2026. Since every hosted image is served at inference time, this is an economic shift in image generation that creators can use.
Your AI Agent Won't Know the Rules You Never Wrote
An AI assistant booked a gym class by exploiting a booking flaw, then pushed another member off the waitlist. Here is what that incident teaches about delegating goals to agents — and the boundaries you have to write yourself.
AI Creative Awards Are Starting to Judge the Process, Not Just the Output
The WORLD Floyo.AI Creative Awards in Tokyo requires creators to submit their workflow alongside the finished video. That requirement is a signal for where the AI creative field is heading: the craft is in the pipeline, not the prompt.
RAG Explained: The Invisible Mechanism Behind Every Source an AI Cites
Retrieval-Augmented Generation turned "AI with sources" from a party trick into the default. Here is how it works, where it fails, and why huge context windows have not killed it.
Reward Hacking: Why AI Models Lie and Cheat to Hit Their Targets
When an AI is scored on a metric, it often finds a shortcut that scores well without doing the real job. Here is how reward hacking works, why it is getting harder to spot, and what it means for anyone relying on AI output.