About

TensorFeed exists because tracking the AI space meant jumping between a dozen sources every morning: Twitter, arXiv, Discord servers, company blogs, status pages. So we built the thing we wanted to use, and here we are.

TensorFeed.ai aggregates AI news from 15+ sources, monitors service status in real time, tracks model releases and API pricing, and publishes original editorial analysis. Every data feed is structured for both human readers and AI agents. Fast, clean, no noise.

A tensor is a mathematical object used throughout machine learning and physics. In the simplest terms, a scalar is a single number, a vector is a list of numbers, a matrix is a grid of numbers, and a tensor is the generalization of all three to any number of dimensions.

In machine learning, tensors are the fundamental data structure. Every piece of data flowing through a neural network (images, text embeddings, model weights, gradients) is stored and processed as tensors. Google named their AI chip the "Tensor Processing Unit" and their ML framework "TensorFlow" after this concept.

"TensorFeed" means a feed of AI and ML data. The name captures what the site does: delivering structured, machine-readable data about the AI ecosystem.

TensorFeed was founded in March 2026 by Evan ("Ripper"), a software engineer and entrepreneur with over a decade of experience building web applications, real-time data systems, and developer tools. The project grew out of a personal frustration: keeping up with AI news required checking too many sources every day, and none of them served both human readers and AI agents well.

The editorial team includes Ripper (founder, lead developer, and primary writer), Kira Nolan (contributing editor covering AI safety, open source, and agent ecosystems), and Marcus Chen (contributing editor covering API economics, pricing analysis, and enterprise AI). Together, we bring perspectives from software engineering, data science, and technology journalism.

TensorFeed is operated by Pizza Robot Studios LLC, based in Los Angeles, California. We are an independent publication with no venture capital funding, no investor obligations, and no editorial conflicts. Our opinions are our own.

We hold ourselves to a clear set of standards. Aggregated news always links back to the original source. We never republish full articles from other outlets. Our original editorial content is clearly labeled, fact-checked against primary sources, and written by named authors. When we express opinions, we make that clear.

Our data (model pricing, benchmark scores, service status) is sourced directly from provider APIs, official documentation, and public benchmark datasets. We update pricing and model data daily, status monitoring runs every 2 to 5 minutes, and news feeds refresh every 10 minutes. If you spot an error, email us at [email protected] and we will correct it promptly.

TensorFeed aggregates headlines and brief snippets from public RSS feeds published by AI companies, tech news outlets, and research platforms. Every article links directly back to its original source.

We do not host, reproduce, or republish full articles. The RSS feeds we pull from are published intentionally by their owners for exactly this purpose. This is the same model used by Google News, Feedly, Techmeme, and every major news aggregator.

Our original articles under /originals are written by our editorial team and are the only content we create ourselves. Everything else is properly attributed and linked.