Where AI Actually Helps Video Teams (and Where It Doesn't)
A practical split: the video tasks machine learning genuinely improves, and the ones where it reliably produces work nobody wants.
Articles from Minute.ly on publishing.
A practical split: the video tasks machine learning genuinely improves, and the ones where it reliably produces work nobody wants.
An embedded player that slows the page costs you the very viewers it was added to attract. What to measure, and what to defer.
The video ad supply chain in plain terms — who the parties are, where the money goes, and which levers a publisher genuinely controls.
Most video dashboards are full of numbers nobody can act on. A short list of the metrics that actually change a decision.
Most publishers sit on more video than they actively use. Indexing the archive turns a storage cost into something you can keep publishing from.
Most publishers treat short-form as new production and quietly abandon it. The ones that sustain it treat it as a format for work they already do.
Audiences raised on streaming will not sit through advertising designed for broadcast. Publishers moving to OTT need a different approach.
Captions are an accessibility obligation, a legal requirement and an SEO asset at once — and auto-generated ones satisfy fewer of those than teams assume.
Machine learning moved from the edge of video production to its centre. A look at what genuinely changed — and what was oversold.
Video revenue is a function of impressions, fill and rate. Most teams push on the one with the least headroom.