Ịmụta Ihe n'Ụgbọ

This page is a translated version of the page Machine Learning and the translation is 64% complete.

Nnọọ na ibe mbụ nke otu Wikimedia Foundation's Machine Learning.

Our team oversees the development and management of machine learning models for end users, as well as the infrastructure required for designing, training, and deploying these models.

Current projects

For archived projects, see this list.

Contact us

Nwere ajụjụ? Chọrọ ịgwa ndị otu ma ọ bụ obodo ndị ọrụ afọ ofufo anyị gbasara mmụta igwe? Nke a bụ ụzọ kachasị mma iji jikọọ anyị.

Team Chat

Discuss machine learning and watch the team work joining our public IRC chatroom #wikimedia-ml connect on irc.libera.chat.

Active Work Board

Have a particular task you want to discuss or work on, join our public Phabricator board. Gaa na bọọdụ ọrụ anyị

Gịnị bụ ihe ọhụrụ?

    • GPU order is underway. We are in the process of ordering a series of servers to use for training and inference. Each server will have two MI210 AMD GPUs. Most will be reserved for model inference (specifically, larger models like LLMs), but we will use two servers (4 GPUs) to create a model training environment. This model training environment will start very small and scrappy but will hopefully grow into a place for automated retraining of models and the standardization of model training approaches. The next steps are a single server will on its way to our data center, once this is tested we will make the full order.
    • Work on caching for Lift Wing continues. We have in the process of making a large order of GPUs. However, to optimize our resource use, one of the best strategies we can do is conduct model inference using our existing CPUs. This is not always possible, for example cases when the set of possible model inputs is not finite. However, in cases where the possible inputs are finite we can cache the predictions for those inputs and then serve them to users rapidly with minimal compute used. This is a similar system to that which was originally used on ORES.
    • The pentesting of Lift Wing continues. The testing is being done by a third party contractor and is examining our vulnerability to malicious code.
    • Wikimedia's branding team has come out with some suggestions for the naming of machine learning tools and models. The hope is that our naming is more systematic and less ad-hoc.
    • Chris helped organize and attend an event in Bellagio, Italy to craft a research agenda for researchers interested in Wikipedia. That research agenda is avaliable here.