A FIELD GUIDE TO JEV / VOL. 01
รวมโปรเจกต์จริง คู่มือใช้งาน และไอเดีย Jev จากทั่วอินเทอร์เน็ต
TypeSafe AI@typesafeaiOFFICIALTypeSafe highlights Jev’s typed-output approach: applications provide state and questions, then act on probabilities, choices or scores. The linked announcement also covers the Venice API integration.
x.comAnswers your code can useดูโปรเจกต์ ↗
Diogo Almeida@CompleteSkepticLAUNCH POSTDiogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
TypeSafe AI@typesafeaiOFFICIALTypeSafe’s official launch announcement introduces the lab and points builders to Jev. It includes Diogo Almeida’s launch film and original introduction.
TypeSafe AI@typesafeaiOFFICIALTypeSafe announces public access to Jev without a waiting list. The official console is the starting point for trying typed decisions in your own application.
x.comJev opens to everyoneดูโปรเจกต์ ↗Four official signals. A fresh starting point on each visit.
16 แหล่งข้อมูล
AI-assisted summaries and translations. Check original sources for context and performance claims.
Jev rapidly analyzed news articles to suggest relevant stories for brands at a low cost.
Source-linked curation
Orus uses Jev to review and approve trade strategies before execution, enhancing decision-making with structured answers.
Source-linked curation
Jev on Sol. A community post describing an experiment where Jev analyzes Solana blockchain data in real time.
Source-linked curation
An AI-driven hedge fund utilizing Jev for fast and cost-effective trading decisions.
Source-linked curation
Jev rapidly analyzes competitor ads with detailed classification and cost efficiency.
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EthanJev identifies and manages marketing messages in Android notifications without content deletion.
Source-linked curation
A community post describing an SEO audit using Jev to analyze website internal links in 45 seconds.
Source-linked curation
AbolA demonstration where Jev was given $10,000 to trade.
Source-linked curation
An experimental trading system using defined rules and Jev for decision-making.
Source-linked curation
AckermanJev rapidly analyzes 700 live ads in 40 seconds for marketing insights at low cost.
Source-linked curation
Jev conducts a sentiment-based stock market analysis for the Danish market in 2025, using diverse data sources with low cost.
Source-linked curation
AbolA community post describes using Jev to analyze news for stock investment opportunities.
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A stock evaluation tool using Jev for fast market analysis.
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A community tool leverages Jev to identify relevant X discussions for business outreach.
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Jarrod WattsA trading bot using Jev to decide buy/sell actions based on asset price feeds and executing real trades.
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Jev trades 15-minute and 1-hour BTC, ETH, and SOL markets on Kalshi.
x.comKalshi prediction-market botดูโปรเจกต์ ↗Source-linked curation
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4 HIGHLIGHTS
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