What makes sense is to do both.
Race down the transformer highway as fast as possible and explore other AI methods.
One need not preclude the other.
Race down the transformer highway as fast as possible and explore other AI methods.
One need not preclude the other.
Going close to as fast as possible while saving a stream for the other approaches makes sense as an approach, but let's not ignore that there's a compromise/tradeoff here. Might not matter in orgs with near infinite resources
For an example of what this looks like at a more pronounced scale just look at the discourse around European models and how far behind Minstral are perceived to be.
Look at what happened to Meta where they squandered a lead, had some mixed results, and reorged to more product certainty and away from fundamental research.
Both of these approaches require quite a bit of institutional support notably.