Google+ adds auto enhancement feature for videos
Google Plus's Auto Awesome feature has been improving its users' images for a while now, and we've seen different updates related to it roll out over the months. Back in December of last year, Google added its year-in-review videos …
Context & Ripple Effects
In late 2014, Google extended Auto Awesome, the machine-learning layer that had been touching up Google+ photos since the prior year's year-in-review videos, to enhance video clips on its own — no editing skill required. At the time it read as a social-network nicety; the related coverage shows it was actually the first step in a twelve-year migration of automated media enhancement into Google Photos.
The throughline runs from that early auto-enhancement through Photos learning to cut GIFs from video clips in 2016, the AI-preset mobile editor added in 2024, the Veo 2-powered photo-to-video and Remix styling tools of 2025, and finally the global AI Enhance button rolled out for Android in April 2026. Each release kept the same bargain — the platform edits by default so the user doesn't have to — while moving it off a declining social network onto Google's durable media vault.
First-order effects
- Google+ users get improved video quality with zero manual work, making Auto Awesome a differentiator for posting on the network at a moment when Google was still investing in it.
- Google establishes the pattern of applying machine-learning edits to user media server-side, decoupling output quality from the camera or the user's editing ability.
Second-order effects
- As the feature family matures inside Google Photos — culminating in the 2026 AI Enhance rollout — every rival photo service is pushed toward shipping comparable one-tap automation just to meet baseline expectations.
- Automatically enhanced, memory-ready media gives Google more compelling content to surface elsewhere, including the curated-memories experience it later brings to Samsung TizenOS TVs.
Third-order effects
- If the arc from Auto Awesome to the Veo 2-era tools holds, default-on computational editing becomes table stakes for any platform holding user media, with differentiation shifting from filters to generative transforms like photo-to-video.
- The long-term effect is consolidation of the 'edit my media' job into the cloud vault itself, leaving standalone editing tools to compete only where they offer control the automation does not — the direction Google's own Vids update points.
The trend: Automated media enhancement has evolved from a social-network gimmick into the default editing layer of cloud photo platforms, with each Google release raising the floor for what users expect their archives to do unprompted.