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Nearly all of the new camera features of Google’s Pixel 10 Pro lean on artificial intelligence. When you use Pro Res Zoom to zoom in at 100x, for example, the Pixel Camera uses generative AI to recreate a sharp, clear version. Or when you’re taking photos of people, the Auto Best Take feature melds multiple shots to create an image where everyone looks good.

But Google added another low-level feature to the Pixel 10 line, C2PA content credentials, that isn’t getting much attention. C2PA, or the Coalition for Content Provenance and Authenticity, is an effort to identify whether an image has been created or edited using AI and help weed out fake images. AI misinformation is a growing problem, especially as the systems used to create them have been rapidly improving — with Google among those advancing the technology. 

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Apple, however, is not part of the coalition of companies pledging to work with C2PA content credentials. But it sells millions of iPhones, some of the most popular image-making devices in the world. It’s time the company implemented the technology in its upcoming iPhone 17 cameras.

Identifying genuine photos from AI-edited ones

C2PA is an initiative founded by Adobe to tag media with content credentials that identify whether they’re AI-generated or AI-edited. Google is a member of the coalition. Starting with the Pixel 10 line, every image captured by the camera is embedded with C2PA information, and if you use AI tools to edit a photo in the Google Photos app, it will also get flagged as being AI-edited.

When viewing an image in Google Photos on a phone, swipe up to display information about it. In addition to data such as which camera settings were used to capture the image, at the bottom is a new “How this was made” section. It’s not incredibly detailed – a typical shot says it’s “Media captured with a camera” — but if an AI tool such as Pro Res Zoom was used, you’ll see “Edited with AI tools.” (I was able to view this on a Pixel 10 Pro XL and a Samsung Galaxy S25 Ultra, but it didn’t show up in the Google Photos app on an iPhone 16 Pro.)

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As another example, if you edit a photo after taking it using the Help me edit field to replace the background of an image, the generated version also includes “Edited with AI tools” in the information.

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To be fair, AI has a role in pretty much every photo you take with a smartphone, given that machine learning is used to identify objects and scenes to better merge bursts of exposures that are captured when you tap the shutter button. The Pixel 10 flags those as “Edited with non-AI tools,” so Google is specifically applying the AI tag to images where generative AI is at work. So far, the implementation is inconsistent: A short AI-generated clip I made using the Photo to Video feature in Google Photos on the Pixel 10 Pro XL shows no C2PA data at all, though it does include a “Veo” watermark in the corner of the video.

What’s important is that the C2PA info is there

But here’s the key point: What Google is doing is not just tagging pictures that have been touched by AI. The Camera app is adding the C2PA data to every photo it captures, even the ones you snap and do nothing with.

The goal is not to highlight AI-edited photos. It’s to let you look at any photo and see where it came from.

When I talked to Isaac Reynolds, group product manager for the Pixel cameras, before the Pixel 10 launch, C2PA was a prominent topic even though in practical terms the feature isn’t remotely as visible as Pro Res Zoom or the new Camera Coach.

“The reason we are so committed to saving this metadata in every Pixel camera picture is so people can start to be suspicious of pictures without any information,” said Reynolds. “We’re just trying to flood the market with this label so people start to expect the data to be there.”

This is why I think Apple needs to adopt C2PA and tag every photo made with an iPhone. It would represent a massive influx of tagged images and give weight to the idea that an image with no tag should be regarded as potentially not genuine. If an image looks off, particularly when it involves current events or is meant to imitate a business in order to scam you, looking at its information can help you make a better-informed choice.

Google isn’t an outlier here. Samsung Galaxy phones add an AI watermark and a content credential tag to images that incorporate AI-generated material. Unfortunately, since Apple is not even listed as one of the C2PA members, I admit it seems like a stretch to expect that the company would adopt the technology. But given Apple’s size and influence in the market, adding C2PA credentials to every image the iPhone makes would make a difference and hopefully encourage even more companies to get on board.

A team of researchers from the TechMed Center at the University of Twente has transformed real sperm cells into tiny, magnetically controlled microrobots. These sperm cells can now be tracked in real time using X-ray images, a breakthrough in medical microrobotics. According to the research group, this development could open new doors in reproductive medicine, drug delivery, and infertility diagnostics.

Sperm cells are naturally fast, flexible swimmers that can navigate the complex environment of the female reproductive tract. This makes them promising candidates for use in medical microrobotics. Sperm cells are almost impossible to see in the human body using traditional imaging methods such as X-rays. They are small, have a low density, and are almost transparent to radiation. “Until now, it has been almost impossible to visualize sperm cells in the body,” says UT researcher Islam Khalil, lead author of the study.

Coating sperm cells

Together with researchers and physicians from Radboud University Medical Center and the University of Waterloo (Canada), researchers at the University of Twente coated real sperm cells with magnetic nanoparticles. This made them visible under X-rays and responsive to external magnetic fields. For the first time, microrobots that utilize sperm cells have been tracked and controlled within a full-scale anatomical model.

Once inside, they can deliver drugs to hard-to-reach places such as the uterus or fallopian tubes. The drugs are delivered directly into the sperm cell bodies. “We are turning nature’s own cell donor systems into programmable microrobots,” says Khalil. This could be an important advance for targeted treatments of conditions such as uterine cancer, endometriosis, or fibroids, for which there are currently no precise options for administering drugs.

Safely observing the moment of fertilization

In addition to the precise delivery of drugs, the technology could also offer new insights into the mystery of what exactly happens in the body during fertilization. By tracking the movement of sperm cells in the reproductive system in a non-invasive manner, researchers aim to gain a deeper understanding of unexplained infertility, the transport mechanisms of sperm cells, and potentially improve IVF techniques.

Tests showed that the sperm nanoparticle clusters remained biocompatible and did not cause significant toxicity to human uterine cells even after 72 hours of exposure. This makes them suitable candidates for future in vivo applications.

Abid’s journey as a technophile began when he first assembled his PC. Since then, his insatiable curiosity has driven him to delve into every aspect of this rapidly evolving technological landscape. And as a tech reporter, he prioritizes transparency, accuracy, and unbiasedness.