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> Transformers are the dominant architecture in AI, yet why they work remains poorly understood. This paper offers a precise answer: a transformer is a Bayesian network.

Why would being a Bayesian network explain why transformers work? Bayesian networks existed long before transformers and never achieved their performance.

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Bayesian network is a really general concept. It applies to all multidimensional probability distribution. It's a graph that encodes independence between variables. Ish.

I have not taken the time to review the paper, but if the claim stands, it means we might have another tool to our toolbox to better understand transformers.

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