Course of Jev and System One models: Practical uses

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Detecting spam comments, classifying a review, or prioritizing customer support requests are tasks where we need a specific decision. Turning to an LLM for each one can add costs and response times that we could avoid.

System One models offer us another way to approach these cases. But to get the most out of them, we need to understand when to use them, which model to choose, and how to integrate them into our applications.

In this course you will learn to:

• ⚖️ Understand what System One models are and choose between Jev, Laya, Kev, and Clef depending on your use case.
• 🧩 Integrate them following best practices, with examples of spam detection with Noul, review classification with Choice, and request prioritization with Score.
• 🤝 Distribute an integration as a Skill to make it easier to use across your team.
• 🛡️ Decide when it makes sense to use System One instead of an LLM and combine both to optimize costs and speed.
• 🔎 Tell decision models apart from Embeddings and combine search and reranking.
• 👀 Explore other uses: controlling the browser, playing video games, and classifying images on your computer.

All with practical examples and the code available on GitHub so you can try it out and bring it to your own projects.

The idea is that you have the judgment to choose the right tool for each task and can integrate it into maintainable, scalable, and testable code. 🤟