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New System One decision model shows rapid learning on MacBook

By PulseAugur Editorial · [1 sources] ·

A new decision model called System One, developed by the author of Laya and VegaML, has been tested on a MacBook. This model utilizes a frozen Qwen3.5-0.8B model and a 14M-parameter "physics engine" to determine answers by outputting probabilities rather than generating text. Initial tests showed a 51% topic accuracy in zero-shot mode, which improved to 65% after fitting with 40 labeled prompts, demonstrating a quick learning capability from a small dataset. AI

IMPACT Demonstrates potential for efficient, on-device AI model learning with limited labeled data.

RANK_REASON The cluster describes a new model release and its performance on benchmarks, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New System One decision model shows rapid learning on MacBook

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16 / 100
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The cluster describes a new model release and its performance on benchmarks, fitting the research category. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    New "System One" decision model from the author of Laya: VegaML. Into the benchmark it went, on my M4 16 GB MacBook. How it works: a frozen Qwen3.5-0.8B reads t

    New "System One" decision model from the author of Laya: VegaML. Into the benchmark it went, on my M4 16 GB MacBook. How it works: a frozen Qwen3.5-0.8B reads the question, then a 14M-parameter "physics engine" lets a ball roll into the valley of the right answer. No text is gene…

    LINKS blog.mornati.net/laya-0-4-2-and-vegaml-a-…

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