Will the most capable, public multimodal model at the end of 2027 in my judgement use a transformer-like architecture?

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17 nov. 23, 09:50 UTC1 janv. 28, 22:59 UTC

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This question will resolve positively if the multimodal ML model that I personally think is most capable at the end of 2027 — as indicated by benchmark performance, personal experience, and task generality — uses a transformer-like architecture.

The model must be publicly available, and is chosen according to my sole judgement.
The model must at its core utilize an architecture that meets the following requirements, including any combination of the modifications and alterations listed:
Core architecture components: The architecture must consist of an encoder, or a decoder, or both, with multi-head self-attention mechanisms, position-wise feed-forward networks, and positional encoding.
Self-attention mechanism: The architecture must use a self-attention mechanism or a close approximation thereof.
This includes:

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Will the most capable, public multimodal model at the end of 2027 in my judgement use a transformer-like architecture?

Will the most capable, public multimodal model at the end of 2027 in my judgement use a transformer-like architecture?

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