When people think about hackathons, they often imagine coding sessions, project demos, and late nights spent debugging. For me, Wikimedia Hackathon 2026 in Milan was something much more meaningful: a reminder that some of the most impactful ideas begin as simple conversations between passionate people.

Like many Wikimedia Commons contributors, I have often found it difficult to discover media through traditional search. Commons hosts millions of images, videos, and audio files, but today’s search relies mostly on filenames, categories, descriptions, and structured data not on what is actually visible or audible in the file itself. Hundreds of campaigns, contests and content initiatives add new media every year, which only makes the problem bigger. I kept wondering, half as a joke and half seriously: what if we could search Commons based on what an image or video actually shows, rather than what someone happened to type into its metadata?

It felt like a wild idea at the time, so I shared it with the Wikimedia technical community mostly to see if anyone else found it interesting.

A researcher and developer named David, who had recently joined the Wikimedia community, came across the discussion. David had been working on a technology called WISE.. at the University of Oxford research focused on semantic understanding of visual and multimedia content, enabling people to search images, videos, and audio using natural language. What started as a random online exchange quickly turned into a collaboration. David hadn’t originally planned to attend the hackathon in Milan, but as we kept talking, we both got excited about bringing this kind of search to the Wikimedia ecosystem, and decided to meet in person and try to build it.

Looking back, that decision changed everything.

For two intense days at the hackathon, we worked side by side to integrate and demonstrate WISE for Wikimedia Commons — architecture, datasets, search quality, the usual string of small technical fires. One moment that stuck with me: the first time we typed “horse in an airplane” into the prototype, half-expecting nothing, and watched it actually return the right video. That was the point it stopped feeling like a demo and started feeling like a real tool.

What inspired me as much as the technology was David’s approach to problem-solving. In an era where most developers reach for an AI assistant the moment something breaks, David would just as often dive into technical documentation, research papers, and manuals first. Watching him methodically work through a problem rather than skip to an answer was a good reminder that strong engineering fundamentals haven’t gone anywhere.

What we built

The result of those two days is WISE, a new experimental search experience for Wikimedia Commons. It currently indexes Media of the Day content around 5,000 videos and is built to understand the actual visual and audio content of a file rather than its metadata.

Semantic search. Search using natural language and find media based on what appears in the image or video itself. A few examples that worked surprisingly well:

• “man at a train station”
• “horse in an airplane”
• “man with a flower”
• “pirate with a pistol”

Audio search. Search within audio content to find relevant recordings and segments.

Face search. Upload a photo of a face, and WISE can locate that person across images and videos… for video, it can even surface the timestamps where they appear.

Multilingual search. Queries work in multiple languages, including Hindi and Telugu. This matters more than it might first appear: most of Commons’ existing search tooling is built around English-language metadata, which quietly shuts out a large share of Wikimedia’s global, non-English-speaking contributor and reader base. A search experience that understands a query in Hindi or Telugu as well as it understands one in English is a small but real step toward making Commons more usable for the movement it actually serves.

You can try WISE yourself here: wise.wmcloud.org
Commons Project page: commons.wikimedia.org/wiki/Commons:Wise

What’s next

This is only the beginning. We’re already discussing:

• Expanding indexing beyond Media of the Day to cover Commons at a much larger scale.
• Finding visually similar images after an upload.
• Suggesting categories, filenames, and metadata based on visual similarity.
• Improving search quality and broadening multilingual support further.

Most of all, this experience reminded me why I love being part of the Wikimedia movement. A passing idea shared on a community forum connected two people from different backgrounds and different parts of the world. An online discussion became an in-person collaboration. A concept became a working prototype. And a hackathon became the place that vision came to life.

Sometimes the most valuable outcome of sharing an idea isn’t the idea itself it’s the people who find it, connect with it and decide to build something together. For me, WISE for Commons is more than a search tool. It’s proof of that.