Evvery
Product Hunt 1 month ago 30
Evvery is launching an Everyday AI product that organizes a user’s chats into separate Spaces for different parts of life and keeps them private.
321 summarised stories about Data Privacy, each linking back to the original source. Browse all topics →
Product Hunt 1 month ago 30
Evvery is launching an Everyday AI product that organizes a user’s chats into separate Spaces for different parts of life and keeps them private.
BBC News 1 month ago 48 ● 125 sources
The article explains what artificial intelligence is and describes how it is used, while outlining major concerns about bias, errors, data use, schooling/workplace misuse, and creator consent. It says some researchers estimate the AI industry could consume as much energy as the Netherlands. It points to emerging regulation such as the EU’s Artificial Intelligence Act and the UK’s measures, plus calls to slow development and tighten oversight as AI expands into daily life.
404 Media 1 month ago 41 ● 2 sources
OpenAI is hiring hundreds of contractors to read real ChatGPT users’ prompts and rate chatbot responses, with some prompts containing sensitive personal information. The contractors are paid more than $50 an hour. This expands the privacy risk for users and adds a largely undisclosed human-review layer to how ChatGPT is improved, while OpenAI still does not acknowledge this human-reading of prompts in its disclosures.
The New Stack 1 month ago 29
OpenRouter enabled US in-region routing for business and enterprise customers, aiming to control where prompts are processed when using open-weight AI models. The service decrypts and serves requests entirely inside the US, or rejects them with a 404 if it cannot. As a result, the main impact is restricting routing to approved US provider endpoints—so companies can use Chinese open-weight models while keeping their own request handling in the country.
The Verge 1 month ago 17
Local governments across the US are canceling contracts with Flock after public outcry over AI-enabled license plate readers.
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NVIDIA’s decision to open-source Run:ai under Apache 2.0 is the day’s most consequential signal: AI compute is getting treated less like proprietary infrastructure and more like inspectable, forkable plumbing. The release puts Run:ai’s Kubernetes GPU orchestration code on GitHub and, in the local build, spins up a five-node Kind cluster pinned to Kubernetes v1.32.5 with eight simulated Tesla-A10 GPUs. That means teams can now audit scheduling behavior, adapt deployment patterns, and self-host without a paid subscription—though the community edition still stops short of NVIDIA enterprise support. In practice, it moves GPU fleet management closer to the software engineers who already live inside CI/CD pipelines, rather than keeping it behind enterprise procurement gates.
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