Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
How MetaCog Works with Jev and Other System One Models
Explains how MetaCog works under the hood: LLMs alone choose the wrong thoughts, while Jev and other System One models can decide for them, acting like a decision tree tool placed on top of agents.
How MetaCog works under the hood. LLMs alone choose the wrong thoughts to have. Jev and other System One models can decide for them. Like the classical 'decision tree' approach... MetaCog can be thought of as a decision tree tool you place on top of your agents. It saves both
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Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
