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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Лучшее о Jev: реальные проекты, практические руководства и идеи со всего интернета.
THE OFFICIAL SIGNAL 4 HIGHLIGHTS
Diogo Almeida@CompleteSkepticLAUNCH POSTДиогу Алмейда представляет Jev, структурированную модель принятия решений TypeSafe. Посмотрите фильм о запуске и изучите оригинальный тред для подхода модели, примеров и отчетов автора о производительности.
TypeSafe AI@typesafeaiOFFICIALОфициальное объявление запуска TypeSafe знакомит с лабораторией и направляет разработчиков к Jev. Включает фильм о запуске Диогу Алмейды и оригинальное введение.
TypeSafe AI@typesafeaiOFFICIALTypeSafe объявляет о публичном доступе к Jev без списка ожидания. Официальный консоль — это отправная точка для тестирования типизированных решений в собственном приложении.
JEVLAB ARTTypeSafe AI@typesafeaiOFFICIALTypeSafe подчеркивает подход Jev с типизированным выводом: приложения предоставляют состояние и вопросы, затем действуют на основе вероятностей, выборов или оценок. Связанное объявление также касается интеграции API Venice.
JEVLAB ARTStart with the Launch Post. Explore four official signals.
114 материалов
AI-assisted summaries and translations. Check original sources for context and performance claims.
Jev enables fast search of physical library indexes.
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Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results.
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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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Open alternative to Jev: typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with benchmarks.
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A research project enabling SQL queries with real type responses.
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Offline Obsidian search with optional Jev reranking of results, requiring user approval before reranking.
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Milind SUtilizes Jev as a decision engine to manage and coordinate multiple bot agents for complex tasks.
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ZachiA PostgreSQL extension enabling natural language queries across databases.
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Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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A collection of research papers and open reproductions supporting System One models.
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An observable raw-character chat experiment powered entirely by TypeSafe Jev Choice.
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A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval.
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High-throughput synthetic & pretraining dataset sifter powered by TypeSafe AI Jev (api.typesafe.ai). Stream, filter, and score Parquet & JSONL datasets at 1,500+ rows/sec using System One typed decisions (Choice, Score, Noul).
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Zero-shot spam filtering with TypeSafe Jev Noul questions, compared with TF-IDF baselines.
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Papers, open reproductions and independent evaluations behind System One models and Jev.
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Can Jev pick the winner of a real headline A/B test? 64.5% across 10,984 Upworthy randomized experiments, 74.7% when the difference was decisive.
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TypeSafe AI System One (Jev) task plugin for QuantumNous/new-api — native /v1/systemone, synchronous evaluation, token billing.
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Interactive explorer and Jev question workspace for Jev Board datasets.
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Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B.
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Dev.to walkthrough of the Vercel AI SDK evaluate integration.
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Jev (TypeSafe) vs. Gemini 3.8 Flash vs. GPT-5.6 Luna na anotação estruturada de sentenças do TJSP: qualidade, tempo e custo.
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Catch breaking API behavior hidden in OpenAPI prose with deterministic checks and TypeSafe JEV System One semantic review.
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Vishesh BaghelA community project using Jev to customize Hacker News content preferences.
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An open-source project aiming to develop a Jev-class decision model for research purposes.
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Reproducible early-access evaluation of Jev on Korean understanding and medical text, with runtime and cost evidence.
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See what Jev thinks about your SaaS website — powered by ReplyNodes web context and Vercel AI Gateway.
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This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
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One-pass typed decisions with calibrated probabilities (System One style model), fine-tuned from Qwen3.5-2B.
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A chatbot from typed Jev decisions: hierarchical speculative decoding over System One probabilities.
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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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Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev.
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Jev AI performs quality checks on action labels for physical AI training data at high speed.
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Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results.
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Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.
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A research project featuring an English–Icelandic dictionary that uses Jev to rerank results for better accuracy.
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A research project on GitHub conducting nine experiments and 28 predictions with fixed parameters, focusing on Jev's performance metrics.
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Directory of Jev-based projects including repositories, SDKs, and benchmarks.
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TypeScript experiments, evaluations, and latency benchmarks for TypeSafe's Jev model.
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Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE).
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Jev (TypeSafe System One) × ASReview SYNERGY abstract screening demo — Choice/Noul vs gold labels.
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Curated catalog of System One / Decision Models — contributions for modelsystem.one.
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Measures how well TypeSafe's RLCD-Jev model spots real secret credentials in file snippets.
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A small second eval for shadcn-ui/lint that uses TypeSafe's Jev to judge the linter's own output.
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@ai-sdk/typesafe-ai plus experimental_evaluate; use jev-latest as an evaluation model.
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A show-and-tell capability study for Jev, TypeSafe's System One decision model.
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End-to-end Jev-style structured-decision stack for auditable data construction, Qwen3.5-0.8B training, fixed Mind2Web and OOD evaluation, preliminary RLCD, local serving, and interactive replay.
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Semantic test matchers for Vitest and Jest, powered by TypeSafe's Jev model. Write expectations in plain English, get calibrated probabilities back.
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Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go.
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Ongoing Japanese research deck on Jev and System One models, maintained as Markdown slides.
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Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
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Openvons (open-Jev): 有限選択肢に確率で答える判断層 — テキスト / 画像 / 日本語音声コマンド.
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Local bilingual probability decisions from context, questions, and candidate answers. Independent research preview inspired by TypeSafe Jev.
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Jev (TypeSafe) exploratory thread: claim audit, live demos, and runnable code.
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Riley BrownA real-time tool to analyze and categorize tweets for viral potential.
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Jev-compatible System 开源Jev.
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A YouTube guide discussing Jev's functionality, pricing, and performance comparisons with Astra, including benchmarking and parallel decision analysis.
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Release-week technical roundup: API, evals, adapter, and skill.
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JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.
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A research project on GitHub uses Jev with Qwen3 models on an NVIDIA DGX Spark system.
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Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.
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A small reproducible MuJoCo pilot comparing Jev, Claude Haiku, and reactive rules for pick-and-place.
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Vercel Labs terminal CLI that can run Jev as the evaluation model for its evaluate command.
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AI benchmark on Japan's 2026 Common Test: Jev vs luna-none vs luna-low (static dashboard).
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Independent, evidence-based map of when TypeSafe's Jev actually holds up vs. breaks down — real API-call receipts, not a leaderboard. 中文為主的雙語 repo。
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TypeSafe Jev demonstration for new analyzation — experimenting with Jev for fast analysis of news and tickers.
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Independent calibration test of TypeSafe's Jev on a task it cannot have seen: 900 rule-generated support tickets (choice / score / boolean) plus 3 public benchmarks via Vercel AI Gateway. Raw responses, ECE with noise floor, temperature refit, per-type sign of miscalibration. Reproducible for ~$0.06.
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Type-safe one-decision-per-token decoding engine for autoregressive LLMs, inspired by Jev.
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看看 Jev 能做什么：用中英文讲清热门应用、工作原理和各自优缺点。Explore Jev apps with plain-language examples, explanations, and comparisons.
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Tool for systematic reviewers to extract information from research articles efficiently.
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Jev vs Gemini 3.8 Flash: labelling 1,000 app reviews, 4.1× faster and 7× cheaper.
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A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
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发明 RLHF 的人，这次做了个不会说话的模型：Jev 独立研究报告。52 页 PDF + 50 条中文实测复现包 + 143 条可回溯数据表.
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