Google open-sources new JPEG encoder that reduces file sizes by around 35%, and is compatible with existing browsers, photo editing apps, and the JPEG standard
New algorithm is based on human psychovisual system. Images look better, too. — Google has developed and open-sourced …
Context & Ripple Effects
This is the second time Google has attacked file size by open-sourcing the compressor itself: Brotli did it for text in 2015 with claimed 20-26% gains over Zopfli, and this encoder does it for photos, cutting JPEG sizes around 35% by modeling the human psychovisual system.
The strategic difference from past image-format efforts is compatibility — because output stays within the JPEG standard, every existing browser and editing app benefits immediately, no adoption cycle required. It also slots into a broader Google research push on media efficiency, alongside RAISR's machine-learning enhancement that shrinks images up to 75% and Google Brain's work reconstructing detail in pixelated images.
First-order effects
- Web publishers and photo-heavy sites can drop page weight by roughly a third on their existing JPEG assets simply by re-encoding — no browser support, plugin, or format migration needed.
Second-order effects
- Newer image formats whose pitch was smaller files at equal quality lose much of their switching incentive when a standards-compliant JPEG gets 35% lighter for free; tools like Chrome Lab's Squoosh, released the following year, bundle exactly these re-encoding options into one workflow.
Third-order effects
- If the pattern holds, image efficiency becomes an encoder-software race driven by perceptual models and machine learning rather than a standards-body format war — with Google setting the pace by giving the algorithms away.
The trend: Google is turning file-size reduction from a format-standardization problem into an open-source algorithm problem, shipping psychovisual and ML-driven compressors that work inside existing standards.