80+ sources. 15 minutes. What matters in AI today. Here is exactly how each episode is built.


01 · How episodes are structured

Six sections, one continuous narrative

Each daily episode runs 14 to 18 minutes as a single continuous narrative across the six editorial sections. No segments, no jingles between sections, no filler. The pillars themselves are listed on the home page.

Saturday weekly recap.The Saturday episode steps back from the daily news to identify the five trends that defined the week and flag what is likely to matter next week.


02 · How sources are selected and weighted

80+ sources, weighted by editorial standards

40+ is a minimum threshold, not a target. Each episode draws from 80+ monitored global sources. A minimum of 40 articles — scored and filtered — are selected per episode. Sources are not treated equally. Each carries a weight score based on editorial standards, domain authority, and primary-source proximity.

TierWeightWhat it covers
Primary / Official2.0×Official announcements from AI labs and companies; peer-reviewed research and academic preprint archives.
Tier-1 Press1.5×Major international newswires, financial press, and peer-reviewed science journals with original reporting.
Specialist Tech Press1.0×Dedicated industry and technology publications with editorial oversight.

Each episode's source manifest, with the actual domains and articles used, is published alongside the episode page.


03 · What we exclude, and why

04 · About the host
David PerronDP

David Perron

Senior global trade solutions professional · AI practitioner · Paris

Twenty years in front-office banking and trade finance at JPMorgan, Barclays and HSBC. Executive Master in Artificial Intelligence, Institut Mines-Télécom (2025). AI Press Review extends my daily professional practice of monitoring AI developments across finance, enterprise and research. The result is a format I would actually want to listen to. I am responsible for the editorial decisions, source weighting, and quality of every episode.


05 · Feedback

Feedback is welcome

If you spot a factual error, a source that should be excluded, or a domain underrepresented in coverage, write to david.perron@aequitus.net.

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