Bài đăng ra mắt Jev
Diogo Almeida giới thiệu Jev, mô hình ra quyết định có cấu trúc của TypeSafe. Xem bộ phim giới thiệu và khám phá chuỗi gốc để tìm hiểu cách tiếp cận, ví dụ và hiệu năng được báo cáo bởi tác giả.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Tinh hoa Jev: dự án thực tế, hướng dẫn hữu ích và ý tưởng từ khắp internet.
Diogo Almeida giới thiệu Jev, mô hình ra quyết định có cấu trúc của TypeSafe. Xem bộ phim giới thiệu và khám phá chuỗi gốc để tìm hiểu cách tiếp cận, ví dụ và hiệu năng được báo cáo bởi tác giả.
Thông báo chính thức ra mắt TypeSafe giới thiệu phòng thí nghiệm và hướng người phát triển đến Jev. Bao gồm bộ phim giới thiệu của Diogo Almeida và lời giới thiệu ban đầu.
TypeSafe thông báo truy cập công khai vào Jev mà không cần danh sách chờ. Bảng điều khiển chính thức là điểm bắt đầu để thử nghiệm các quyết định có kiểu trong ứng dụng của bạn.
TypeSafe nhấn mạnh cách tiếp cận đầu ra có kiểu của Jev: các ứng dụng cung cấp trạng thái và câu hỏi, sau đó thực hiện hành động dựa trên xác suất, lựa chọn hoặc điểm số. Thông báo liên quan cũng đề cập đến tích hợp API Venice.
Start with the Launch Post. Explore four official signals.
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AI-assisted summaries and translations. Check original sources for context and performance claims.
Bộ phân loại đánh giá độ khó câu lệnh theo thời gian thực, cho phép chế độ nhanh cho các câu lệnh đơn giản để cải thiện tương tác người dùng.
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Bản demo cho thấy Jev chọn mô hình AI phù hợp nhất cho các nhiệm vụ tạo video và hình ảnh trên Higgsfield.
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GitHub project for content moderation with category-specific probability thresholds. Enables automated content filtering.
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A community example demonstrating how Jev can classify company invoices into accounting categories rapidly.
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Jev demonstrated over 5x faster performance than other models in testing.
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Jev enables flexible, type-safe classification as a fundamental programming primitive.
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A community post about using Jev for incident triage in Box, returning boolean results with probabilities.
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SuperX tích hợp với Jev cho phép đánh giá bài đăng nhanh chóng, phân tích 61 câu hỏi mỗi bài đăng trong vòng một giây với độ chính xác cao trong việc dự đoán tiềm năng lan truyền.
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A guide explaining Jev's approach to making typed decisions rather than processing text.
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A demonstration of Jev's capability to quickly categorize a large volume of Hacker News posts.
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A prototype that classifies symptoms and updates diagnoses using medical ontologies during live clinical consultations.
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A tool that scores video ad shots in 1.5 seconds using Maxfusion and Jev, processing over 450 ads in under three minutes.
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A project classifying 1,018 AI research papers using Jev, achieving low cost and fast processing for organizing academic work.
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A Jev-powered system that analyzes PDFs page by page to determine which require OCR processing.
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Pre-alpha PostgreSQL extension for TypeSafe AI (Jev) categorical classification.
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Uses Jev to decide which AI model to use before generating output, based on prompt and quality requirements.
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A GitHub project routing tasks by selecting model tier, tools, skill, and effort.
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A demo showing how to make open source models behave like Jev using inference engineering and scoring endpoints for decision-making.
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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.
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Real-time Discord moderation bot: Jev evaluates messages and metadata in parallel to catch phishing, spam, and social engineering with a progressive escalation ladder.
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A GitHub project that uses Jev to triage and route posts from the live Bluesky firehose with human oversight.
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A LangChain package with TypeSafeClassifier for integrating Jev into applications.
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A developer project exploring decisions using a classifier as a next-token predictor.
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Marketing analytics platform whose feature flag routes brand-visibility classifiers off an LLM and onto Jev boolean decisions.
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A GitHub project for a Pareto-optimal OpenRouter router for Pi, decided by Jev.
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A community post presents a codebase complexity classifier using Jev, aiming to address overengineered code.
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An optimized inference engine to turn LLMs into Jev-like machines: optimized for quick, lightweight, and accurate decision-making, classification, and scoring.
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Not every coding task needs your best model. Experimental Jev-powered model routing for Claude Code — V3 prototype runs today, V4 routes at the task boundary.
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A GitHub Action using Jev for automated PR triage and classification.
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Eight minimal working examples of TypeSafe's Jev (a System One model) applied to mechanical and electrical engineering: CAD/CAE/CAM routing, FEM result triage, DFM screening, BOM alignment, hallucination-proof extraction. Zero dependencies.
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DuckDB extension that classifies rows in CSV, Parquet, or DuckDB tables with Jev, about 10 seconds per 1,000 rows.
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A guide on using Jev to route between models and block risky tool calls.
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Jev classifies 500 emails quickly and inexpensively, demonstrating its efficiency in processing tasks.
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GitHub Action for issue triage that abstains: label, spam, needs-info and duplicate in one call, each applied only above a threshold you set, and nothing at all below it.
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Turn any open model into a classifier/jev endpoint.
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Open-source Jev-style System One decision model. Gemma 3 270M with a scoring head — fast, calibrated decisions in a single forward pass. No text generation. Inspired by TypeSafe.ai's Jev.
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Typed, policy-driven decision workflows on top of TypeSafe AI Jev: confidence routing, fallbacks, evaluation, and RAG patterns for TypeScript apps.
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A community post detailing a dashboard that classifies X posts across eight dimensions using Jev for content research.
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A .NET 10 and React 19 application for fast, structured AI-powered ticket triage using TypeSafe Jev.
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Experimental semantic line search with TypeSafe Jev via OpenRouter. Python CLI with no runtime dependencies.
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Open-source AI email triage for Gmail. Sorts your inbox into Needs reply, Updates, Promos, Sales and Spam with Jev, TypeSafe AI's decision model, via Vercel AI Gateway. Read-only, runs locally, 1,000 emails in about a minute for 3 cents.
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An open-source project that helps select relevant Claude Code skills by prioritizing frequently used ones through Jev integration.
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Classifies tax documents using an LLM pipeline for efficient processing.
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A setup where Jev selects between different AI models for specific tasks, streamlining model usage in a single terminal.

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Open-source Jev log triage for OpenTelemetry. Score the signal before expensive LLM analysis.
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Jev is utilized for decision-making processes on Cloudflare, including support routing and risk management.
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Screen a folder of CVs with the TypeSafe Jev decision model: typed judgments, an editable policy, free re-scoring.
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A project using Jev for skill routing in an agent system, based on community development.
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Jev evaluates the pacing of a frontier-AI essay written by @DarioAmodei.
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Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships.
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Runnable Jev examples through OpenRouter for immediate implementation.
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An image classifier using OCR and Jev processes 900 images in 40 seconds.
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Jev enables natural language search for Zillow listings, classifying properties by non-standard filters.
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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.
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Three composable judgment pipelines on TypeSafe's Jev: support-ticket triage, observability alert triage, and a deploy-risk gate.
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An ad blocker extension using AI for real-time classification and removal of ads.
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JEV Document Classification enables the rapid and cost-effective classification of text-based documents using AI, leveraging TypeSafe's "System One" model.
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Near-real-time scoring of TikTok and Instagram hooks against about 100 personas.
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Jev is a System One model on OpenRouter that provides decisions with probabilities.
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LlamaIndex reranker + router powered by TypeSafe Jev — typed scores/choices, cheaper than LLM-as-judge.
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Diffusion-style pixel art out of a classifier: 256 parallel per-pixel Jev questions plus refinement passes.
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A resource detailing a test of Jev on 12 real-world scenarios, including speed, cost, and practical applications.

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Classify Git commit diffs and messages with Jev. Bug fixes, security fixes/CWEs, and change types.
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Jev is demonstrated as a classification model with practical examples.

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SQL with natural-language predicates, powered by TypeSafe's Jev. Filter, rank, classify and score rows by meaning — batched, cached and cost-guarded.
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A developer project integrating Home Assistant with Jev for processing user input without an LLM.
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Analyzes 100,000 X posts in 20.4 seconds using 14 yes/no questions per post for viral potential assessment.
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TypeSafe (Jev) vs DeepSeek-flash: side-by-side speed/token/cost/accuracy comparison across invoice extraction, email classification, and reranking.
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A developer project for model routing with caching and failover.
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Fast CVSS scoring from vulnerability descriptions using Typesafe Jev.
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A task using Jev to score 3,000 kids' snacks with multiple criteria in 28 seconds.
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A system tested on 1,500 emails for classification effectiveness. Demonstrates potential for automated email management.
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