Current work

• Integration of MLFLow for ML experiment tracking

  We will allow users of SciLifeLab Serve to launch their own instances of the platform MLFlow that allows to keep track of models and artifacts in machine learning work. Users will be able to send data to their instance from anywhere where they are doing training or analyses.

  Released Q1 2025

• Support for model deployment with GPUs

  We will allow users to publish models with access to GPUs to run inferences. We will start with a few pilot projects before making it widely available. Get in touch with us if you are interested in being a pilot user.

  Planned Q2 2025

Near-term work

• Metadata and FAIR improvements

  We will be collecting additional information about applications and models published on SciLifeLab Serve (such as list of authors and source of funding). We will also be registering Digital Object Identifiers (DOIs) to allow tracking of metadata and citation of applications and models.

  Planned Q3 2025

• Improved web accessibility of the website

  We will review and update our webpages to meet the Web Content Accessibility Guidelines (WCAG) 2.2.

  Planned Q3 2025

• Access to an API endpoint to interact with LLM(s)

  We will provide an API endpoint for application developers that will allow their apps to interact with one or more LLMs. The apps will then need to be made available through SciLifeLab Serve.

  Planned Q3 2025

Long-term work

• LLM-empowered application creation

  We will integrate an interface allowing to build data science applications by interacting with an LLM through a chat interface. These applications can then be published on SciLifeLab Serve.

  Planned Q4 2025