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.
Máy chủ chính thức của TypeSafe. Các demo builder được trình bày trong kênh Show and Tell.
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Bài đăng ra mắt: kiến trúc, huấn luyện RLCD, giá cả, các demo Doom và Wikiracing, FAQ.
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Phương pháp đánh giá và kết quả theo mô hình cho quy trình System One.
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Dán trạng thái, thêm câu hỏi và xem câu trả lời có kiểu trong trình duyệt.
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Lý do cho trí tuệ tự nhiên của máy tính được xây dựng cho phần mềm, không phải trò chuyện.
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A resource explaining Jev's capabilities, limitations, and applications as a System One model.
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Jev is utilized for decision-making processes on Cloudflare, including support routing and risk management.
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A guide explaining how to integrate Jev with Pydantic AI agents for type-safe operations.
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A practical guide explaining the use of TypeSafe’s System One model, providing technical insights for developers.
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A guide explaining Jev's approach to making typed decisions rather than processing text.
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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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Independent walkthrough separating TypeSafe's published claims from public evidence.
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Dev.to walkthrough of the Vercel AI SDK evaluate integration.
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Trang chủ công ty, danh sách chờ và tổng quan sản phẩm.
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Jev integrates with Netlify's AI Gateway for zero-configuration use.
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Directory listing systems using Jev for Noul, Score, and Choice questions.
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Hugging Face Space exploring open-source parallel constrained decoding as an alternative to Jev.
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3D chess where Jev plays both sides, or you jump in.
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Practical guide: playground, Python and JS SDKs, raw HTTP, and the agent skill.
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Jev is discussed with examples of Choice, Noul, and Score in a Python project.
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A resource explaining Jev Engineering methodology for AI agent development.
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A resource explaining Jev's functions, costs, and evaluation metrics as TypeSafe's System One model.
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A tech publication highlights Jev as an AI model offering a cost-effective and efficient approach to software intelligence.
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Jev selects legal moves in a game of chess, compared to reasoning models.
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A guide exploring Jev's architecture through 10,000 API calls.
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Browser-based request builder for the System One API: compose state plus typed Noul, Choice, and Score questions. Mock mode runs locally without an API key; Live mode requires your TypeSafe key and calls api.typesafe.ai directly. Generates typesafe_sdk Python. Includes companion Jev Suitability Test.
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Latent Space's launch-day roundup: over 100x faster and 200x cheaper than small frontier LLMs.
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1,800-point thread debating whether typed decisions replace LLM calls for classification, routing, and scoring.
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Free, no-signup Noul demo. Ask a question, get yes, no, or maybe, with web search when needed.
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A report detailing all public Jev builds in the first week, including cost, time, and repository metadata for research use.
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The maze as JSON; Jev picks the turn at each junction in real time.
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Release-week technical roundup: API, evals, adapter, and skill.
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A LangChain package with TypeSafeClassifier for integrating Jev into applications.
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Guía del creador Fazt sobre el uso de Jev para decisiones tipadas, con una introducción y ejemplos de aplicaciones.
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Directory of Jev-based projects including repositories, SDKs, and benchmarks.
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A directory of Jev-related demos with categorization and submission options.
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A guide on integrating Jev with LiteLLM for simplified model calls through an existing proxy.
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One sentence becomes six room settings. Jev chooses, the app renders.
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Short practical intro with a Python ticket-triage example.
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A tool for tracking decisions made by Jev, using Arize's instrumentation for detailed analysis.
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One direct Jev question per row against 12–14 Jev-scored dimensions with locally fitted weights on three classification tasks: 5,477 test rows, 25,174 Jev calls, $1.43. Decomposition wins on Japanese NLI (0.9076 vs 0.8373) but flags about 25× more hard benign rows as attacks (37.2% vs 1.5%).
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Página do criador Leonardo Bissoli com seu vídeo, capítulos e referências sobre decisões estruturadas com Jev.
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Village NPCs that judge you each tick, deciding what to do and how they feel, instead of chatting.
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Work-in-progress demo of Jev driving Minecraft, including fleeing zombies at night.
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Head-to-head test at validating local event listings, with cost and latency.
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Third-party write-up of the System One primitives, pricing, and vendor workflow evals.
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A guide on using Jev to route between models and block risky tool calls.
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Anthony Maio's essay on what a model that cannot generate text is for.
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The Neuron's explainer on AI decisions without a chatbot.
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Jev vs Jev gomoku with source and timing logs.
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X client with Jev smart rules that filter the timeline by usefulness, type, and topic.
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Talk nicely or nastily over time; structured state tracks the mood.
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Technical SEO audit cost study from Boring Tools Kit where Jev ranks striking-distance fixes and content gaps by calibrated probability.
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Local Telegram channel JSON analyzer for intent, quality, sentiment, and speaker tone.
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Small game that tests how Jev handles unknown input.
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@ai-sdk/typesafe-ai plus experimental_evaluate; use jev-latest as an evaluation model.
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Every's Mike Taylor runs his whole archive through Jev.
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Hosted typesafe-ai/jev for AI SDK evaluate calls, no TypeSafe waitlist required.
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Krunker-style 1v1 FPS where Jev decides move, aim, ADS, fire, and jump at about 9 Hz.
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Val Town demo where 16 typed judgments update live as you type.
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Japanese walkthrough of what Jev is and is not.
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Jev picks rotation and column from holes, stack height, and bumpiness.
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Playable board games driven by Jev decisions.
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The Register on the launch, the Doom demo, and the $40M seed round.
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Test a post against 10,000 synthetic personas before you publish it.
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