You can 'massively decreasing returns to complexity' in these domains.
Meaning that you can do 'pretty good' with some basic algorithms.
For the next 'bump in performance' you need some complex code.
After that - you really start to have 10x larger models, or crazy complex engineering just to move the needle.
It creates a completely different set of 'Product Management' rules. It's kind of fun, unless you're a struggling startup trying to figure this out on the fly :)
Usually, someone comes along with a new approach which changes the games.
As I understand it 'Neural Networks' i.e. 'Deep Learning' style AI has changed everything voice related quite a lot.
And also - different business approaches can change the game. Google has access to zillions of phrases for properly transcribed audio phrases. This is the 'golden asset' that can underpin a really great voice recognition engine. Google voice is even better than the old industry standard - Nuance - in many scenarios and my hunch is that it's the size of their training data that has given them an edge - at least that.
You can 'massively decreasing returns to complexity' in these domains.
Meaning that you can do 'pretty good' with some basic algorithms.
For the next 'bump in performance' you need some complex code.
After that - you really start to have 10x larger models, or crazy complex engineering just to move the needle.
It creates a completely different set of 'Product Management' rules. It's kind of fun, unless you're a struggling startup trying to figure this out on the fly :)
Usually, someone comes along with a new approach which changes the games.
As I understand it 'Neural Networks' i.e. 'Deep Learning' style AI has changed everything voice related quite a lot.
And also - different business approaches can change the game. Google has access to zillions of phrases for properly transcribed audio phrases. This is the 'golden asset' that can underpin a really great voice recognition engine. Google voice is even better than the old industry standard - Nuance - in many scenarios and my hunch is that it's the size of their training data that has given them an edge - at least that.