https://blog.ast.moe/en/tags/probability/Recent posts: GorimuchuHugohttps://blog.ast.moe/en/blog/2026-10-01/Thu, 01 Oct 2026 11:33:14 +0900https://blog.ast.moe/en/blog/2026-10-01/<h2 id="overview">Overview</h2> <p>Even if you encounter the name “Jev,” it’s not immediately clear whether it’s an AI that answers questions in chat, a search model, or a scaled‑down version of an existing large language model. I myself built a MCP server that uses Jev, but knowing how to call its API and understanding its return values are separate issues.</p> <p> <span> <a target="_blank" href="https://docs.typesafe.ai/introduction"> Jev from TypeSafe AI </a> <img class="external-link-icon" src="https://blog.ast.moe/images/outer-link.png" width="12" height="12" alt="" aria-hidden="true" loading="lazy"> </span> is a model that, given input information, returns a judgment on predefined questions. Rather than producing free‑form explanatory text, it returns values suitable for programmatic handling—such as the probability of a “yes” answer, probabilities for each candidate, tiered ratings, and so on. For example, you feed it a query text and have it evaluate whether it concerns an invoice inquiry, a shipping inquiry, or whether it needs to be routed to a specific person. Rather than reading the answer and continuing the conversation, the usage is that the code receiving the answer decides the next action to take.</p>