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Recent activityA FIELD GUIDE TO JEV / VOL. 01
O melhor de Jev: projetos reais, guias práticos e ideias de toda a internet.
THE OFFICIAL SIGNAL 4 HIGHLIGHTS
Diogo Almeida@CompleteSkepticLAUNCH POSTDiogo Almeida apresenta o Jev, o modelo de decisão estruturado do TypeSafe. Assistir ao filme de lançamento e explorar o fio original para o abordagem do modelo, exemplos e desempenho relatado pelo autor.
TypeSafe AI@typesafeaiOFFICIALO anúncio oficial de lançamento do TypeSafe apresenta o laboratório e direciona os desenvolvedores ao Jev. Inclui o filme de lançamento de Diogo Almeida e a introdução original.
TypeSafe AI@typesafeaiOFFICIALTypeSafe anuncia acesso público ao Jev sem lista de espera. O console oficial é o ponto de partida para testar decisões tipadas em seu próprio aplicativo.
JEVLAB ARTTypeSafe AI@typesafeaiOFFICIALTypeSafe destaca a abordagem de saída tipada do Jev: aplicações fornecem estado e perguntas, depois atuam sobre probabilidades, escolhas ou pontuações. A anúncio vinculado também aborda a integração da API Venice.
JEVLAB ARTStart with the Launch Post. Explore four official signals.
114 recursos
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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Offline Obsidian search with optional Jev reranking of results, requiring user approval before reranking.
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ZachiA PostgreSQL extension enabling natural language queries across databases.
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A research project enabling SQL queries with real type responses.
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Tool for systematic reviewers to extract information from research articles efficiently.
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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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A research project featuring an English–Icelandic dictionary that uses Jev to rerank results for better accuracy.
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Jev AI performs quality checks on action labels for physical AI training data at high speed.
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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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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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Charts: TypeSafe Jev evaluated on Thai standardized exams vs 110 other models.
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Interactive explorer and Jev question workspace for Jev Board datasets.
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Nushell module for the TypeSafe System One API: typed decisions with calibrated probabilities.
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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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Reproducible benchmark for measuring Jev reranking quality, latency, and cost in RAG.
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Riley BrownA real-time tool to analyze and categorize tweets for viral potential.
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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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A stronger one-pass scorer over a variable list of text options: hashed n-gram encoder, rival-aware attention, gated head, temperature scaling, benchmarked against jevlike.
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A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
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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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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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Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.
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A collection of research papers and open reproductions supporting System One models.
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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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Independent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.
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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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Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev.
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Directory of Jev-based projects including repositories, SDKs, and benchmarks.
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Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.
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On-device iPhone visual decision tool using MLX and Qwen3-VL direct option logits.
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A research project evaluating the practical value of Jev's confidence scores for task execution.
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Never confidently wrong: a TLA+-verified consensus kernel around TypeSafe's Jev, run through 1,680 chaos-tested pharmacy decisions with zero wrong verdicts. Film, code, and every captured call.
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Vishesh BaghelA community project using Jev to customize Hacker News content preferences.
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Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results.
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Papers, open reproductions and independent evaluations behind System One models and 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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TypeSafe Jev demonstration for new analyzation — experimenting with Jev for fast analysis of news and tickers.
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A chatbot built on a model that cannot generate text (TypeSafe AI's Jev, driven autoregressively).
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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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A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval.
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Experiments with openjev, an open Jev-style option-logit runner, on local models.
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Small Python package that uses typesafe.ai to evaluate code comments on certain heuristics.
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Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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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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CLI for TypeSafe AI's Jev evaluation model — typed questions in, structured JSON answers out.
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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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I tortured Jev into being a RISC-V CPU.
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Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.
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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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If you're experimenting with jev it will be easier from here.
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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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Reproducible early-access evaluation of Jev on Korean understanding and medical text, with runtime and cost evidence.
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Jev 1.13 reward-model evaluation across 8 benchmark tracks, with an interactive report and 54-row SOTA comparison.
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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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Feedback on your paper in seconds.
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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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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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Jev vs Gemini 3.8 Flash: labelling 1,000 app reviews, 4.1× faster and 7× cheaper.
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Jev-compatible System 开源Jev.
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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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@ai-sdk/typesafe-ai plus experimental_evaluate; use jev-latest as an evaluation model.
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A research project auditing Jev's performance with the Spanish language.
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Find, design, and evaluate TypeSafe Jev decision loops.
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TypeScript experiments, evaluations, and latency benchmarks for TypeSafe's Jev model.
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A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.
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Ongoing Japanese research deck on Jev and System One models, maintained as Markdown slides.
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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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Batched single-token choice inference for open language models, compatible with TypeSafe.
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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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An observable raw-character chat experiment powered entirely by TypeSafe Jev Choice.
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Zero-shot spam filtering with TypeSafe Jev Noul questions, compared with TF-IDF baselines.
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4 HIGHLIGHTS
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