Does Scaling Toward AGI Depend on What System-1 Lets System-2 Execute?
READ THE ORIGINAL SOURCEOpen original sourcehuggingface.co · Opens in a new tabThe paper asks whether progress toward AGI, which has largely relied on scaling a resource-intensive executive (System-2) through larger models, more data and compute, longer reasoning, and more agents, might instead come from co-designing System-2 with System-1, described as a lightweight, semantically aware predictor that evaluates candidate actions. The supplied text is truncated before any methods, results, or conclusions appear.
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- Primary sourceHugging Face Daily Papers
- Discovery linkHugging Face
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The paper asks whether progress toward AGI, which has largely relied on scaling a resource-intensive executive (System-2) through larger models, more data and compute, longer reasoning, and more agents, might instead come from co-designing System-2 with System-1, described as a lightweight, semantically aware predictor that evaluates candidate actions. The supplied text is truncated before any methods, results, or conclusions appear.
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- 03Where are the sources?
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- 06What would change the view?
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Key findings from the stored brief
- The paper frames current AGI progress as mainly driven by scaling System-2 via larger models, data, compute, longer reasoning, and more agents.
- It proposes co-designing System-2 with System-1, a lightweight, semantically aware predictor.
- The excerpt describes System-1 as evaluating candidate options but does not report any experimental findings.
Source claims not independently checked; the supplied text is truncated and contains no empirical results.
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Evidence & sources
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Timeline & updates
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Why this may matter
If a lightweight predictor can guide the executive component, the field's dominant reliance on scaling the expensive reasoning component could be reconsidered, with implications for efficiency and architecture.
Limits and open questions
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