The internet has become a visual place—with companies like Snapchat, Facebook, and Google reinventing their services around your phone’s camera. As a result, the need to relay visual information with less data is becoming increasingly important.
Artificial intelligence may solve that problem. Rather than using traditional file formats like JPEG, which apply the same kind of data-saving rules to every image, AI could look at what’s in a photo and find a way to represent it that uses less data. This idea has been explored by tech companies such as Google and Twitter, which could deploy these systems on massive scale, as well as startups like WaveOne.
Twitter and WaveOne have both taken a similar approach, in which one algorithm tries to generate an image, and then a second algorithm determines whether it looks good. Think of it like a player and a coach: If the player messes up, the coach tells them. The algorithms compare the generated image to the original, learning what blurring and pixelation look like by subtracting the generated photo from the original.
If the generated image doesn’t make the cut, the first algorithm tries again, and the algorithms repeat the process until a good image is generated. It’s like having a quality assurance worker for every image AI generates. WaveOne, which published new research this week, says this second algorithm, the coach, is what sets it apart from previous work. It’s able to identify and focus on multiple aspects of the image—not just finding pixelated or blurry bits, but also analyze the structure of the image, ensuring that a face has two eyes and a mouth, the cofounders said in an email.
However, this technique usually has a downside. The algorithms learn to simplify patterns and shapes based on what they’ve seen before. If they’re given an image to reduce that they don’t recognize, the systems have been shown to “hallucinate” things that aren’t there. If you’ve only seen grass with…