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Will causality be an important ingredient in major commercial applications of AI by the end of 2025?
29
Ṁ1kṀ2.9k
resolved Dec 31
Resolved
NO

Causality as in Judea Pearl's do-calculus and the area of research building on it. Will major successful AI products (equivalent in importance in public discourse and potential economic impact to today's large language models) be shown to crucially rely on causality research, e.g. causal representation learning, by the end of 2025?

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Causality, sure. A specific research area of causality, no.
I'd bet on robust causal reasoning emerging informally from embodiment than from a specific research project or lineage.

bought Ṁ30 NO

Nah

predictedNO

https://manifold.markets/mariopasquato/will-pearls-causality-have-importan

Note that GFlowNets can be used for causal discovery, so this is tangentially related to this market: https://manifold.markets/mariopasquato/gflownet-becomes-mainstream-by-the?r=bWFyaW9wYXNxdWF0bw

Gflownet becomes mainstream by the end of 2025
30% chance. GFlowNet is a new architecture championed by Yoshua Bengio. This resolves yes if at least one AI company will deploy a GFlowNet in production to deliver an AI service considered state of the art by midnight Dec 31, 2025. The service may still be in beta but must be accessible to a reasonable number of people or businesses. It could be deployed in non customer facing roles as long as it has major impact (e.g. in robotics applied to some popular product). The company may be a new one, even a startup, but it must be clear that the product is really existing and outperforming traditional approaches.

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