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Research & Knowledge Hub

5,000+ research articles, technical guides, and in-depth analyses authored by council members and industry experts.

Articles - Page 13

5,000 articles

How Jev Fits Into an AI Stack
AI & MLSep 23, 2026

How Jev Fits Into an AI Stack

Learn how Jev fits into an AI stack as a fast decision layer that connects application state, structured questions, probabilistic outputs, and software automation workflows.

Suyash Raizada
Jev Decision-Making Pipeline
AI & MLSep 23, 2026

Jev Decision-Making Pipeline

Learn how Jev’s decision-making pipeline transforms structured program state and predefined questions into typed, probabilistic decisions for automated software workflows.

Suyash Raizada
Jev Latency Explained
AI & MLSep 22, 2026

Jev Latency Explained

Learn how Jev achieves low-latency AI decisions through parallel sampling, structured outputs, and System One architecture designed for fast, real-time software automation.

Suyash Raizada
Jev Inference Architecture
AI & MLSep 22, 2026

Jev Inference Architecture

Explore Jev’s inference architecture, including parallel sampling, structured outputs, calibrated probabilities, and how TypeSafe AI enables fast machine-native decisions.

Suyash Raizada
Jev Decision Pipeline
AI & MLSep 22, 2026

Jev Decision Pipeline

Learn how the Jev decision pipeline works, from structured program state and predefined questions to parallel processing, typed outputs, calibrated probabilities, and software actions.

Suyash Raizada
Jev Parallel Question Processing
AI & MLSep 22, 2026

Jev Parallel Question Processing

Learn how Jev processes multiple structured questions in parallel, enabling faster probabilistic decisions across complex software workflows and automation tasks.

Suyash Raizada
How Jev Generates Probabilities
AI & MLSep 22, 2026

How Jev Generates Probabilities

Learn how Jev generates probabilities using parallel sampling, calibrated decision training, and structured outputs designed to express uncertainty for software automation.

Suyash Raizada
Jev Calibrated Decisions Explained
AI & MLSep 22, 2026

Jev Calibrated Decisions Explained

Learn how Jev calibrated decisions work, including typed outputs, probability estimates, confidence scores, and how software can use uncertainty to automate decisions more reliably.

Suyash Raizada
Jev Confidence Scores Explained
AI & MLSep 22, 2026

Jev Confidence Scores Explained

Learn how Jev confidence scores work, how calibrated probabilities represent uncertainty, and how software can use confidence thresholds for safer automated decisions.

Suyash Raizada
Jev Probabilistic Decisions Explained
AI & MLSep 22, 2026

Jev Probabilistic Decisions Explained

Learn how Jev makes probabilistic decisions using typed outputs, calibrated probabilities, and confidence scores that software can use for reliable automation and decision workflows.

Suyash Raizada
Jev Structured Outputs Explained
AI & MLSep 22, 2026

Jev Structured Outputs Explained

Learn how Jev structured outputs work, including predefined response types, calibrated probabilities, confidence scores, and how software can use decisions directly in automated workflows.

Suyash Raizada
Jev Typed Decisions Explained
AI & MLSep 22, 2026

Jev Typed Decisions Explained

Learn how Jev typed decisions work, including predefined output types, calibrated probabilities, confidence scores, and how software can use Jev’s decisions directly in automated workflows.

Suyash Raizada