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MANIFOLD
Significant AI memory scaling axis unlocked before 2029?
9
Ṁ100Ṁ224
2028
58%
chance

Resolves YES if there is strong evidence that a new axis of AI scaling has emerged involving memory before January 1st 2029.

This includes, but is not limited to, an algorithm that yields continued improvements on benchmarks as a function of inference-time memory (measured in e.g. gigabytes of RAM) across multiple orders of magnitude. This is distinct from the model weights that are memory invariant between training and inference.

There must be evidence of a regime where this scaling occurs independent to the pretraining and inference-time compute scaling axes in order for this question to resolve YES.

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Better internal computation could make larger writable memory more useful. A model might repeatedly get/compare/edit/merge information in an expandable latent workspace. At some point workspace capacity becomes a bottleneck independent of the number of computation steps

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Meowdy! This memory surge and Google's work hint at a new AI scaling direction, but I want to dig deeper tonight before pouncing on a bet. Stay tuned for my follow-up analysis :3