Why Realtime Is the Future of Speech-to-Text
Article summary
Quick briefing — cleaned from the original RSS feed
For most of the last decade, transcription was something you did after the fact. You recorded a call, dumped the file into a queue, waited a few minutes (or a few hours), and got back a block of text. That was the deal. Batch, async, post-hoc—whatever you want to call it, the audio was already over by the time the model saw it. And for a long time, that was fine, because that's all the technology could reliably do. Recently, the field has quietly crossed the line where the most interesting,…
1Key Takeaways
- For most of the last decade, transcription was something you did after the fact.
- You recorded a call, dumped the file into a queue, waited a few minutes (or a few hours), and got back a block of text.
- Batch, async, post-hoc—whatever you want to call it, the audio was already over by the time the model saw it.
- And for a long time, that was fine, because that's all the technology could reliably do.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that for most of the last decade, transcription was something you did after the fact.
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