Fair point. I was trying to focus on the broader topic rather than lead with the project, but I can see why that might come across as marketing-style framing.

That's a fair point. A good user experience usually comes from the engineering around the model, not just the model itself.

The AI gets most of the attention, but things like latency, workflow design, context handling, and reliability often make the difference between something people try once and something they actually use.

That's a fair point. I think convenience will continue to win for a lot of people.

What interests me is having the option. For some use cases, a cloud service is perfectly fine. For others, whether it's privacy, compliance, reliability, or simply wanting control over your own infrastructure, self-hosted alternatives can be valuable even if they never become the default choice.

Also, the quality of open-source speech and translation tools has improved so much that they're becoming realistic options for far more people than they were a few years ago.

That's really interesting. Sometimes it feels like local AI is a new idea, but a lot of the foundations were already there years ago.

The difference now is that the models have become good enough that these kinds of workflows are practical for everyday users, not just research projects.

That's exactly the kind of use case that makes translation technology so interesting to me. It's not always about business meetings or travel, sometimes it's reading a news article from another country, understanding a product manual, or simply helping someone find their way.

It's great to see more translation tools moving toward on-device and privacy-friendly approaches. A few years ago, many of these workflows would have required sending everything to external services.