Will the most capable, public multimodal model at the end of 2027 in my judgement use a transformer-like architecture?
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Actualizado hace 45 minutos
Retrasado17 nov 23, 9:50 UTC1 ene 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: