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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Das Beste von Jev: echte Projekte, praktische Anleitungen und Ideen aus dem Netz.
THE OFFICIAL SIGNAL 4 HIGHLIGHTS
Diogo Almeida@CompleteSkepticLAUNCH POSTDiogo Almeida stellt Jev vor, das strukturierte Entscheidungsmodell von TypeSafe. Schauen Sie sich den Launch-Film an und erkunden Sie den ursprünglichen Thread für den Ansatz des Modells, Beispiele und die vom Autor gemeldeten Leistungen.
TypeSafe AI@typesafeaiOFFICIALDie offizielle Launch-Ankündigung von TypeSafe stellt das Labor vor und verweist Entwickler auf Jev. Sie enthält Diogos Almeidas Launch-Film und die ursprüngliche Einführung.
TypeSafe AI@typesafeaiOFFICIALTypeSafe kündigt die öffentliche Zugänglichkeit von Jev ohne Warteliste an. Die offizielle Konsole ist der Ausgangspunkt, um typisierte Entscheidungen in Ihrer eigenen Anwendung zu testen.
JEVLAB ARTTypeSafe AI@typesafeaiOFFICIALTypeSafe betont den typisierten Ausgabeansatz von Jev: Anwendungen geben Zustand und Fragen an, dann handeln sie auf Wahrscheinlichkeiten, Auswahl oder Bewertungen. Der verknüpfte Ankündigungstext behandelt auch die Venice API-Integration.
JEVLAB ARTStart with the Launch Post. Explore four official signals.
28 Ressourcen
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.
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An experimental trading system using defined rules and Jev for decision-making.
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A community tool leverages Jev to identify relevant X discussions for business outreach.
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A project comparing Jev's performance against chat models in analyzing Fed press conferences.
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Jev conducts a sentiment-based stock market analysis for the Danish market in 2025, using diverse data sources with low cost.
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A stock evaluation tool using Jev for fast market analysis.
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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.
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Experimental multi-horizon BTC signal generator using TypeSafe Jev probabilities and Binance market data.
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Backtest Jev (TypeSafe) as a BUY/SELL/HOLD trader on NQ L10 order-book data.
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AckermanJev rapidly analyzes 700 live ads in 40 seconds for marketing insights at low cost.
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Trading bot with the all new TypeSafe AI's first system one model named as Jev.
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AbolA demonstration where Jev was given $10,000 to trade.
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A community post describing an SEO audit using Jev to analyze website internal links in 45 seconds.
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An AI-driven hedge fund utilizing Jev for fast and cost-effective trading decisions.
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Orus uses Jev to review and approve trade strategies before execution, enhancing decision-making with structured answers.
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AbolA community post describes using Jev to analyze news for stock investment opportunities.
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An experimental JEV-powered framework for forecasting short-term stock price direction from structured market data.
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Live Jev trader on Hyperliquid.
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Jev on Sol. A community post describing an experiment where Jev analyzes Solana blockchain data in real time.
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Everyday Stocks Status with Jev.
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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.
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One AI trade decision every Monad block. Jev on Kuru MON-USDC.
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A developer project related to market analysis using Jev, collected for the markets shelf.
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Using Jev to test how well it predicts financial markets(just like most llms as of september 2026, it doesnt do that good).
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Probably: live BTC, ETH, and XRP prices with a shared TypeSafe buy-or-wait demonstration. No trades placed.
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Does Jev predict stock returns from news? It reads the news well; there is no tradeable alpha. Three arms separate reading from recall.
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4 HIGHLIGHTS
Markets & experiments
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