Product Release
We’re excited to introduce Mozilla.ai Blueprints and the Blueprints Hub! Cut through the clutter of clunky tool integration, and see how you can speed up your development and spark your creativity.
Technical Content
Timeline algorithms should be useful for people, not for companies. Their quality should not be evaluated in terms of how much time people spend on a platform, but rather in terms of how well they serve their users’ purposes.
Technical Content
New state-of-the-art models emerge every few weeks, making it hard to keep up, especially when testing and integrating them. In reality, many available models may already meet our needs. The key question isn’t “Which model is the best?” but rather, “What’s the smallest model that gets the job done?”
Technical Content
A typical user may be building a summarization application for their domain and wondering: “Do I need to go for a model as big as DeepSeek, or can I get away with a smaller model?”. This takes us to the key elements: Metrics, Models, and Datasets.
Technical Content
Mozilla.ai developed and released the OpenStreetMap AI Helper Blueprint. If you love maps and are interested in training your own computer vision model, you’ll enjoy diving into this Blueprint.
Technical Content
Previously, we explored how LLMs like Meta’s Llama reshaped AI, offering transparency and control. We discussed open-weight models like DeepSeek and deployment options. Now, we show how to deploy DeepSeek V3, a powerful open-weight model, on a Kubernetes cluster using vLLM.
Technical Content
The landscape of LLMs has evolved dramatically since ChatGPT burst onto the scene in late 2022. At Mozilla.ai, we’re focused on improving trust in open-source AI by supporting their use in appropriate situations and their proper evaluation.
Technical Content
When deciding on a new Blueprint, we focus on selecting an end application that is both practical and impactful, along with the best techniques to implement it. With endless possible applications of LMs today, selecting one that is actually useful can be challenging.
Product Release
Lumigator is a developer-first tool designed and built by the community to help engineers evaluate and compare AI models with ease. Lumigator empowers developers to make data-driven choices when integrating AI models into their applications.
Technical Content
Blueprints are customizable workflows that help developers build AI applications using open-source tools and models. In this blog, we’ll dive into our first Blueprint: document-to-podcast. We’ll explain how it works, our technical decisions, and how you can use and customize it yourself.
Product Release
Developers today face many challenges when trying to integrate AI into their apps or building an “AI solution” from scratch. At Mozilla.ai, we’re committed to breaking down these barriers with Blueprints – our initiative to help developers adopt open-source AI tools and models with confidence.
Technical Content
Lumigator 🐊 is a self-hosted, open-source Python application for evaluating large language models using offline metrics. It targets common machine learning use-cases, starting with summarization, and is extensible at the task and job level.