Posting peluncuran Jev
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
A FIELD GUIDE TO JEV / VOL. 01
Yang terbaik dari Jev: proyek nyata, panduan praktis, dan ide dari seluruh internet.
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
Pengumuman peluncuran resmi TypeSafe memperkenalkan laboratorium dan mengarahkan pengembang ke Jev. Termasuk film peluncuran Diogo Almeida dan pengantar asli.
TypeSafe mengumumkan akses publik ke Jev tanpa daftar tunggu. Konsol resmi adalah titik awal untuk mencoba keputusan bertipe dalam aplikasi Anda sendiri.
TypeSafe menyoroti pendekatan Jev untuk output bertipe: aplikasi menyediakan state dan pertanyaan, lalu bertindak berdasarkan probabilitas, pilihan, atau skor. Pengumuman terkait juga mencakup integrasi API Venice.
Start with the Launch Post. Explore four official signals.
1.198 sumber
AI-assisted summaries and translations. Check original sources for context and performance claims.
A community reference describing real-time generation of game levels for game development.
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Moved hard-coded rules to Jev for faster AI processing and reduced costs in projects like aiseotracker and linkdr.
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A community project uses Jev to detect AI-generated text, providing real-time sentence-by-sentence analysis.
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Jev demonstrates potential for innovative UX/UI design through language model integration.
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Public examples of Jev used for robot control, 3D modeling and adjacent control tasks, with sources and archived media.
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Steve Krouse's playable 16-judgment demo and video.
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An experiment using Jev for real-time model selection in AI agents, collected for the agents shelf.
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A project using Jev to enable fast voice-controlled interactions with a Mac computer.
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Write Cucumber tests with just the .feature file. No step definitions — Jev (TypeSafe AI) resolves each Gherkin step and Playwright runs it.
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A system that quickly captures user interface flows on demand, enabled by Jev's fast processing capabilities.
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Keterampilan agen resmi untuk Claude Code, Codex, dan agen kompatibel: primitif, pola, dan cara mengatur evaluasi.
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A log analysis tool that groups 22.8M lines into patterns and uses Jev to review key patterns.
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Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
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Retriever AI evaluates Jev's performance on real browser tasks, identifying strengths and areas for improvement in integration with larger models.

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Integration of Jev into a game for fast and cost-effective performance.
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Open-source library converting Hugging Face models into Jev-style endpoints for broader accessibility.
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A system enabling rapid agent deployment on digital canvases without relying on slow LLM processes.
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A community post discussing Jev's use in enforcing coding rules that linters cannot handle.
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A focus group experiment using Jev to make scroll or stop decisions on ads.
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Pengganti TypeSafeClient resmi yang didukung oleh API LLM OpenAI, Anthropic, dan kompatibel, untuk membandingkan Jev dengan model chat.
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JevForm creates adaptive forms that change based on user input meaning rather than fixed if-then logic.
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Jev generates piano music by selecting notes and chords based on input sequences.
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A tool for monitoring Reddit threads to gather data cited by AI, offering free analysis of 4000 threads via email, Discord, or Slack.
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A system that generates text one character at a time using Jev, employing a classifier in an autoregressive loop.
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A project where Jev attempts to defeat the Pokémon League in Pokémon Gold, using basic controls to navigate and win.
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An experimental trading system using defined rules and Jev for decision-making.
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A developer project that selects applicable rules for Claude, ensuring only relevant information is shown.
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A system tested on 1,500 emails for classification effectiveness. Demonstrates potential for automated email management.
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Jev-browser enables agents to perform web tasks by automatically opening websites and making click decisions based on screen content.
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An image classifier using OCR and Jev processes 900 images in 40 seconds.
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A tool that analyzes Tetris board positions and selects optimal placements in under half a second.
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Jev successfully played and won a match in the game Clash Royale.
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An open-source model for form-filling tasks with low latency.
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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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Jev rapidly analyzes competitor ads with detailed classification and cost efficiency.
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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 community experiment using Jev to analyze social media posts and determine effective content strategies.
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Jev autonomously controls multiple characters in a video game with rapid decision-making.
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Everyday Stocks Status with Jev.
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A tool that uses Jev to detect AI-generated content on websites by analyzing specific indicators.
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Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay.
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Jev classifies emails for fraud detection, with uncertain cases handled by Kimi K3 for high accuracy.
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Jev is discussed with examples of Choice, Noul, and Score in a Python project.
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A tool built on Jev that identifies programming languages, colors code, and checks lint rules.
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A developer project featuring a small Jev-like model running on a MacBook, collected for the tools shelf.
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Jev controls both hands and fingers to play piano in real-time based on visual input.
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Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.
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Demonstration of Jev's capability for rapid variable generation in development workflows.
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Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev.
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Pokémon FireRed Elite Four run. A community post describing an experiment where Jev successfully completed a game with low-cost resources.
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A prototype that classifies symptoms and updates diagnoses using medical ontologies during live clinical consultations.
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Official TypeSafe reference: Skill suggestion.
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Vercel's open agent framework, which ships Jev as the default evaluation model in its experimental evaluate path.
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A tool that improves end-to-end testing efficiency, completing tasks faster and cheaper than other models.
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A challenge where 100 builders used Jev and Fable 5.1 to create a post scheduler, highlighting Jev's speed.
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Detects low-quality content in real-time as users scroll.
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A collection of notable Jev projects shared on X, highlighting various applications and experiments.
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A 30-minute internal session on Jev attended by over 50 engineers, generating more than 50 product ideas.
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Jev converts websites into native mobile apps by deciding the optimal build process and handling app store submissions.
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A 2-minute song composed by Jev-thoven using first principles.
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A community post about a virtual town where Jev makes all decisions, managing 120 people and various local structures.
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Jev plays Subway Surfers at superhuman speed and handles 50 games simultaneously for under a cent.
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A community post demonstrating Jev's ability to score 700 leads and predict outreach message performance in 40 seconds.
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An agent project that enforces policies by judging Claude Code tool calls.
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A YouTube guide explaining Jev's functionality, including browser use, classification, and code review without an LLM.

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A demonstration of Jev's capability to quickly categorize a large volume of Hacker News posts.
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Utilizes Jev for quick coaching support and detecting and fixing slop during sessions.
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A developer project for agent-native routing that selects models based on task complexity.
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A community post describes Jev attempting to play Resident Evil, testing its ability to handle 3D environments, objectives, and combat scenarios.
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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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A community tool allowing Jev to make decisions through command-line interactions for agent systems.
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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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