ai-curated analysis · multi-source · science & technology
Science and technology journalism, done differently. Every article is AI-analyzed, multi-source, and written for people who want to understand the news — not just consume it.
Each piece starts with primary sources — journal papers, data releases, official records. An AI system reads and compares multiple sources on the same topic, identifies where coverage diverges from the underlying evidence, and produces a structured analysis. The result is then reviewed and published.
The goal is to close the gap between what the science actually says and what gets reported. That gap is usually where the most interesting information lives.
The analysis is generated by AI cross-referencing primary sources, not written by a human reporter from scratch. This matters for a few reasons. AI can process and compare more source material faster than a single writer. It doesn't have a beat to protect or a relationship with a PR contact. It will apply the same epistemic standard — what does the evidence actually support? — to every story.
It also has limits. AI analysis can miss cultural context, misread tone, or fail to flag when a source has an obvious conflict of interest that a human would catch immediately. Those limitations are why articles flag their sourcing explicitly and distinguish between peer-reviewed findings, preprints, and press-release science.
Every article distinguishes between what is known, what is claimed, and what is speculated. Sources are cited. Where coverage diverged from evidence, that's noted. The goal is not to be contrarian — it's to be accurate, which sometimes looks like the same thing.
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