The website notes that one big distinction is that unlike some other image compression techniques like WebP and WebM, these new JPEGs are compatible with the current JPEG standard and also current devices, browsers and photo editing apps.
There is a slight downside (of sorts) for the new algorithm: it takes a little more time to compress, but the benefits outweigh the processing costs, as users are on the receiving end of the image - and needn't foot the CPU bill. This is to advance its efforts in getting webpages to load faster while using less data. These zoomed-in images show the original at left, Guetzli compression in the middle, and an alternative called libjpeg at right. This will enable webmasters to develop webpages that can load faster while using comparatively less data.
Google has developed a new open-source JPEG compression algorithm, dubbed Guetzli (apparently that means "cookie" in Swiss German).
For Google's Guetzli speed boost, researchers developed a test called Butteraugli created to model human vision. "The visual quality of JPEG images is directly correlated to its multi-stage compression process: colour space transform, discrete cosine transform, and quantization". You can view Guetzli's repository on GitHub here. "However, while Guetzli creates smaller image file sizes, the tradeoff is that these search algorithms take significantly longer to create compressed images than now available methods".
To accomplish this, Guetzli is using psychovisual research based on HVS or the human visual system model. Alternatively, it's now possible to significantly improve the image quality of a file without raising its size. Other factors can also be involved, such as the speed of the server the site is hosted on, the code that's used to make and design the page and the file sizes for any images that are used in the site. The time between shots might be reduced if Guetzli compression is used. The company performed experiments where images of equal file size were shown to study participants who consistently prefered the imaged compressed using Guetzli.
The downside to this methodology is that compression takes significantly longer than now available methods. "Guetzli is rather slow to encode", the researchers said, suggesting it's most likely useful on image-heavy websites.