Publicación de lanzamiento de Jev
Diogo Almeida presenta Jev, el modelo de decisión estructurado de TypeSafe. Vea el film de lanzamiento y explore el hilo original para el enfoque del modelo, ejemplos y rendimiento informado por el autor.
A FIELD GUIDE TO JEV / VOL. 01
Lo mejor de Jev: proyectos reales, guías prácticas e ideas de toda la web.
Diogo Almeida presenta Jev, el modelo de decisión estructurado de TypeSafe. Vea el film de lanzamiento y explore el hilo original para el enfoque del modelo, ejemplos y rendimiento informado por el autor.
El anuncio oficial de lanzamiento de TypeSafe presenta el laboratorio y orienta a los desarrolladores a Jev. Incluye el film de lanzamiento de Diogo Almeida y su introducción original.
TypeSafe anuncia el acceso público a Jev sin lista de espera. La consola oficial es el punto de partida para probar decisiones tipadas en su propia aplicación.
TypeSafe destaca el enfoque de salida tipada de Jev: las aplicaciones proporcionan estado y preguntas, luego actúan sobre probabilidades, elecciones o puntajes. La anunciación vinculada también cubre la integración de la API de Venice.
Start with the Launch Post. Explore four official signals.
35 recursos
AI-assisted summaries and translations. Check original sources for context and performance claims.
Clasificador que evalúa en tiempo real la dificultad de las instrucciones, permitiendo un modo rápido para instrucciones simples para mejorar la interacción del usuario.
Source-linked curation
Demostración donde Jev selecciona los modelos de IA más adecuados para tareas de generación de video e imagen en Higgsfield.
Source-linked curation
SuperX integrado con Jev permite una puntuación rápida de publicaciones, analizando 61 preguntas por publicación en menos de un segundo con alta precisión en la predicción del potencial viral.
Source-linked curation
A project using Jev for skill routing in an agent system, based on community development.
Source-linked curation
A real-time computer assistant using Jev and local Whisper to process voice input, classify actions, and interact with the screen through a Swift app for accessibility.
Source-linked curation
A 26-sheet construction plan set was classified in 2.9 seconds using Jev with an LLM pipeline, costing $0.0052 and matching GPT-4.1 and GPT-6 Astra performance.
Source-linked curation
Classifies tax documents using an LLM pipeline for efficient processing.
Source-linked curation
An ad blocker extension using AI for real-time classification and removal of ads.
Source-linked curation
DuckDB extension that classifies rows in CSV, Parquet, or DuckDB tables with Jev, about 10 seconds per 1,000 rows.
Source-linked curation
A community post detailing a dashboard that classifies X posts across eight dimensions using Jev for content research.
Source-linked curation
A tool that scores video ad shots in 1.5 seconds using Maxfusion and Jev, processing over 450 ads in under three minutes.
Source-linked curation
Analyzes 100,000 X posts in 20.4 seconds using 14 yes/no questions per post for viral potential assessment.
Source-linked curation
A community post presents a codebase complexity classifier using Jev, aiming to address overengineered code.
Source-linked curation
An open-source project that helps select relevant Claude Code skills by prioritizing frequently used ones through Jev integration.
Source-linked curation
Jev offers structured decision-making for security workflows with high speed.
Source-linked curation
A system tested on 1,500 emails for classification effectiveness. Demonstrates potential for automated email management.
Source-linked curation
An image classifier using OCR and Jev processes 900 images in 40 seconds.
Source-linked curation
Matched-precision comparison against a private fine-tuned classifier.
Source-linked curation
Jev demonstrated over 5x faster performance than other models in testing.
Source-linked curation
A Jev-powered system that analyzes PDFs page by page to determine which require OCR processing.
Source-linked curation
Jev enables Grok Bot to control real Chrome for faster, automated tasks instead of slow look-and-click methods.
Source-linked curation
Jev classifies 500 emails quickly and inexpensively, demonstrating its efficiency in processing tasks.
Source-linked curation
A demo showing how to make open source models behave like Jev using inference engineering and scoring endpoints for decision-making.
Source-linked curation
A community example demonstrating how Jev can classify company invoices into accounting categories rapidly.
Source-linked curation
A demonstration of Jev's capability to quickly categorize a large volume of Hacker News posts.
Source-linked curation
A project classifying 1,018 AI research papers using Jev, achieving low cost and fast processing for organizing academic work.
Source-linked curation
Jev enables flexible, type-safe classification as a fundamental programming primitive.
Source-linked curation
Jev evaluates the pacing of a frontier-AI essay written by @DarioAmodei.
Source-linked curation
A prototype that classifies symptoms and updates diagnoses using medical ontologies during live clinical consultations.
Source-linked curation
Uses Jev to decide which AI model to use before generating output, based on prompt and quality requirements.
Source-linked curation
Jev is a System One model on OpenRouter that provides decisions with probabilities.
Source-linked curation
Near-real-time scoring of TikTok and Instagram hooks against about 100 personas.
Source-linked curation
A task using Jev to score 3,000 kids' snacks with multiple criteria in 28 seconds.
Source-linked curation
A community post about using Jev for incident triage in Box, returning boolean results with probabilities.
Source-linked curation
Jev enables natural language search for Zillow listings, classifying properties by non-standard filters.
Source-linked curation