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AI & Content Creation

559 summarised stories about AI & Content Creation, each linking back to the original source. Browse all topics →

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Friday, 4 September 2026

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

Amazon Web Services 1 month ago 35

Amazon Bedrock was integrated with Amazon Textract to let teams preprocess utility bills and query them instead of feeding raw documents directly into a RAG system. The setup deploys an AWS CloudFormation stack via bash custom_kb_deployment_setup.sh that creates 2 Lambda functions and an OpenSearch Serverless cluster. The pipeline now automatically converts uploaded multi-format files into a knowledge base format for more reliable LLM answers, with post-deployment configuration steps including syncing an Amazon Bedrock Knowledge Base and testing with an Amazon Nova Micro model.

Every.to vibe check: GPT-6 Astra’s writing, software use, and visuals improve—but product judgment depends on the task

Every 1 month ago 7

GPT-6 Astra improved Every’s Vibe Check writing, software use, and visuals when used from a single prompt, but the report says product judgment depends on the specific task. The Builder Pack includes $9,000+ in credits for tools Every builds. The change is that Every’s evaluation distinguishes stronger output from task-by-task usefulness while placing parts of the full report behind paid membership.

Why AI food looks like that

The Verge 1 month ago 15 ● 4 sources

Food brands are using AI-generated images to promote menu items, producing surreal and often unappetizing visuals (including clearly weird dishes). One notable concrete detail is the repeated mention of “holes” in the described burger image. As a result, the marketing imagery shifts from recognizable food photos to distorted, uncanny illustrations that can undermine audience trust and appetites, which the article treats as trivial but notable.

The sameness problem behind those unappetizing AI-generated menus

TechCrunch 1 month ago 29 ● 4 sources

AI-generated restaurant menus have produced oddly symmetrical, overly smooth food illustrations that people find unsettling because the models learn a narrow, “pleasing” aesthetic from similar training data. The article describes an X experiment where a menu image made in ChatGPT was edited 100 times, after which the food increasingly looked wrong. Restaurants are responding by revising these menus—often repeatedly changing small details like item names or prices—while verification and detection tools have gained a role because this homogenization can degrade output quality.

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