Jev 런치 포스트
Diogo Almeida가 TypeSafe의 구조화된 판단 모델 Jev를 소개합니다. 런치 영상과 원문 스레드에서 접근 방식, 활용 사례, 제작자가 발표한 성능을 확인하세요.
A FIELD GUIDE TO JEV / VOL. 01
인터넷 곳곳의 Jev 프로젝트, 실용적인 가이드와 놀라운 아이디어를 한곳에서.
Diogo Almeida가 TypeSafe의 구조화된 판단 모델 Jev를 소개합니다. 런치 영상과 원문 스레드에서 접근 방식, 활용 사례, 제작자가 발표한 성능을 확인하세요.
TypeSafe가 스텔스 모드를 마치고 Jev를 공개했습니다. Diogo Almeida의 런치 영상과 소개 스레드로 이어지는 공식 발표입니다.
TypeSafe가 대기 목록 없는 Jev 공개 접근을 발표했습니다. 공식 콘솔에서 앱에 사용할 구조화된 판단을 시작할 수 있습니다.
TypeSafe가 Jev의 구조화된 출력을 소개합니다. 앱의 상태와 질문을 전달하면 확률·선택지·점수로 응답하며, 연결된 발표에서 Venice API 통합도 확인할 수 있습니다.
Launch Post부터 시작하세요. 공식 원문 4편을 살펴볼 수 있어요.
95 개 자료
요약·번역에 AI를 활용합니다. 원문과 성능 주장은 출처에서 확인하세요.
Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results.
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Offline Obsidian search with optional Jev reranking of results, requiring user approval before reranking.
JEVLAB ARTSource-linked curation
A collection of research papers and open reproductions supporting System One models.
JEVLAB ARTSource-linked curation
A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
JEVLAB ARTSource-linked curation
Check whether each cited paper supports the sentence citing it. Claude proves the quote, TypeSafe's Jev scores it, a human decides.
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Measures how well TypeSafe's RLCD-Jev model spots real secret credentials in file snippets.
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Can a decision model beat dedicated rerankers? TypeSafe Jev vs Cohere Rerank 4 vs ZeroEntropy zerank-2 vs a chat-model baseline: 14 datasets, every raw API response, bootstrap ranges on every gap.
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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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A research project enabling SQL queries with real type responses.
JEVLAB ARTSource-linked curation
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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Open alternative to Jev: typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with benchmarks.
JEVLAB ARTSource-linked curation
A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.
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Type-safe one-decision-per-token decoding engine for autoregressive LLMs, inspired by Jev.
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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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Nushell module for the TypeSafe System One API: typed decisions with calibrated probabilities.
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Curated catalog of System One / Decision Models — contributions for modelsystem.one.
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A Jev-inspired decision interface for existing LLMs. Explicit choices, scores, calibration, and review thresholds.
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A research project featuring an English–Icelandic dictionary that uses Jev to rerank results for better accuracy.
JEVLAB ARTSource-linked curation
Reproducible benchmark for measuring Jev reranking quality, latency, and cost in RAG.
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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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If you're experimenting with jev it will be easier from here.
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Jev (TypeSafe System One) × ASReview SYNERGY abstract screening demo — Choice/Noul vs gold labels.
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A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
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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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Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go.
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An open-source project aiming to develop a Jev-class decision model for research purposes.
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Papers, open reproductions and independent evaluations behind System One models and Jev.
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PadFlow(부동산 개발 SaaS)의 타입 결정 기준 벤치마크: 스키마, 익명화된 라벨링된 행 및 TypeSafe Jev와 같은 신뢰도가 높은 모델을 위한 실행자.
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Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B.
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This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
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TypeSafe Jev demonstration for new analyzation — experimenting with Jev for fast analysis of news and tickers.
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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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See what Jev thinks about your SaaS website — powered by ReplyNodes web context and Vercel AI Gateway.
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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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Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.
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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。
JEVLAB ARTSource-linked curation
Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.
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A research project auditing Jev's performance with the Spanish language.
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A reproduction of Jev that turns any Qwen model into a fast decision model, serving the same /v1/systemone schema (Choice, Score, Noul) with no training and no generated answer text.
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Open-source BYOK arena for Jev and other AI judges. Find failures, compare quality, cost, and latency.
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CLI for TypeSafe AI's Jev evaluation model — typed questions in, structured JSON answers out.
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Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.
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Ongoing Japanese research deck on Jev and System One models, maintained as Markdown slides.
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Find, design, and evaluate TypeSafe Jev decision loops.
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Jev (TypeSafe) exploratory thread: claim audit, live demos, and runnable code.
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A research project evaluating the practical value of Jev's confidence scores for task execution.
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On-device iPhone visual decision tool using MLX and Qwen3-VL direct option logits.
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A chatbot built on a model that cannot generate text (TypeSafe AI's Jev, driven autoregressively).
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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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Vercel Labs terminal CLI that can run Jev as the evaluation model for its evaluate command.
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Sort by meaning: order lines along a plain-English dimension, from pairwise comparisons judged by TypeSafe's Jev model.
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Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results.
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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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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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Experiments with openjev, an open Jev-style option-logit runner, on local models.
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Batched single-token choice inference for open language models, compatible with TypeSafe.
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Interactive explorer and Jev question workspace for Jev Board datasets.
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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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Using Jev as an evaluator.
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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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The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
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Open, Jev-compatible System One decision server on DiffusionGemma.
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Charts: TypeSafe Jev evaluated on Thai standardized exams vs 110 other models.
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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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Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
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JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.
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Stop guessing confidence thresholds: calibrate, threshold, and drift-check typed decision models (TypeSafe Jev) against an LLM teacher.
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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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Decision harness for TypeSafe Jev — confidence gates, shadow mode, recipes, and evals. Claude CLI 48.9s → Jev 1.3s on the same row-filter job.
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I tortured Jev into being a RISC-V CPU.
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A show-and-tell capability study for Jev, TypeSafe's System One decision model.
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