That’s right, they’re solving the same problem, although metric/semantic layers have traditionally lived within BI tools. Looker’s LookML is a great example of a metric layer.

There you define the relationships between tables, which dimensions to expose to your users, and how measures are to be aggregated along which dimensions and at what roll ups. Filters, formatting, and other semantic information rounds out what’s possible, making it easier to build complex reporting without having to pre-build large joined tables in the warehouse.

In theory a semantic layer decoupled from BI can be useful too, as downstream systems can all query a metric. Maybe an operational workflow needs access to revenue numbers or a spreadsheet wants a feed of some fresh aggregates.

The real question is will BI tools adopt a semantic layer they don’t own, giving up control over a key part of their input into their visualizations? Time will tell.

Oracle BI has this separation in the RDP layer. So there is some history of BI tools separating out that layer but the separation doesn't have to result in giving up control. It's more of an organizational decision. Although it's probably not advisable to have wide open access to the semantic layer to the same users creating dashboards, as things can quickly get overcomplicated and hard to maintain.