Author HubMaximilian Schreiner
Uber Eats now manipulates food images using generative AI.
Uber Eats is now using generative AI to identify and enhance low-quality food photos on its menus. The technology does more than just adjust lighting, resolution, or cropping. It can move food onto different plates or backgrounds, and even modify the food itself - making portions look bigger or digitally filling in gaps for a more polished look.
This approach goes further than traditional retouching or generic stock photos. The AI is capable of generating convincing images of dishes that, in some cases, never actually existed in this form.

Black Forest Labs and Krea AI have released FLUX.1 Krea [dev], an open text-to-image model designed to generate more realistic images with fewer of the exaggerated, AI-typical textures.
The model is based on FLUX.1 [dev] and remains fully compatible with its architecture. It was built for flexible customization and easy integration into downstream applications. Model weights are available on Hugging Face, with commercial licenses offered through the BFL Licensing Portal. Partners like FAL, Replicate, Runware, DataCrunch, and TogetherAI provide API access.
Today we are releasing FLUX.1 Krea [dev] - a new state-of-the-art open-weights FLUX model, built for photorealism.
Developed in collaboration with @krea_ai, this model is focused on images with unique aesthetics. No "AI look", no blown-out highlights, just natural detail. pic.twitter.com/0YCUyO6BbI-
Black Forest Labs (@bfl_ml) July 31, 2025
Google is rolling out Opal, a new experimental tool that lets users build AI-powered mini-apps with simple natural language prompts, no coding required.
Opal takes descriptions written in everyday language and automatically connects prompts, AI models, and other tools to turn them into working apps, displaying everything as a visual workflow.
Once an app is built, users can share it with others, who only need a Google account to use it. Opal is launching as a public beta in the US, with plans to develop the tool further based on feedback from the community.
YouTube is rolling out an AI-powered age estimation system in the US that will try to determine users' ages based on factors like account activity and account lifespan—regardless of what users claim.
The new system is designed to identify teens who have registered as adults and automatically apply protection measures such as ad restrictions, screen time reminders, and content filters. The move comes as lawmakers ramp up pressure on big tech: More than a dozen states, including Texas, Utah, and Florida, have introduced or passed laws requiring age verification or parental consent for social media use.
YouTube's approach relies on technical solutions rather than requiring users to actively provide proof of age. The result is a balancing act between privacy, child safety, and business interests—one that will also have to contend with Europe's Digital Services Act, GDPR, and the EU AI Act.