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迪奧戈·阿梅達介紹 Jev,這是 TypeSafe 的結構化決策模型。觀看推出影片,並探索原始主題以了解模型的方法、範例和作者報告的效能。
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Recent activity迪奧戈·阿梅達介紹 Jev,這是 TypeSafe 的結構化決策模型。觀看推出影片,並探索原始主題以了解模型的方法、範例和作者報告的效能。
TypeSafe 的正式推出公告介紹了實驗室,並引導開發者使用 Jev。包含迪奧戈·阿梅達的推出影片和原始介紹。
TypeSafe 宣佈 Jev 無需等待名單即可公開使用。官方控制台是將類型化決策應用於自己應用程式的起點。
TypeSafe 強調 Jev 的類型輸出方法:應用程式提供狀態和問題,然後根據機率、選擇或分數進行操作。連結的公告也涵蓋了威尼斯 API 集成。
Start with the Launch Post. Explore four official signals.
13 項資源
AI-assisted summaries and translations. Check original sources for context and performance claims.
A real-time tool to analyze and categorize tweets for viral potential.
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A PostgreSQL extension enabling natural language queries across databases.
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A community project using Jev to customize Hacker News content preferences.
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Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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Jev AI performs quality checks on action labels for physical AI training data at high speed.
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Jev integrates into a recommendation engine, providing 70+ personalized suggestions per user at 0.0019$ per user.
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Tool for systematic reviewers to extract information from research articles efficiently.
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Jev enables fast search of physical library indexes.
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Jev versus a hand-built regex on 544 public data-protection resolutions: 98.2% agreement for about five cents.
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Utilizes Jev as a decision engine to manage and coordinate multiple bot agents for complex tasks.
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Eval of Jev turning free-text player intent into typed server actions: 96% agreement, 317 ms median.
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Jev monitors 25 WhatsApp customer groups in real time, alerting an LLM only when urgent issues arise.
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A free open-source search tool powered by Jev and a search API for plain language queries.
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