Comment by tensor
1 day ago
Sorry, that's AI. So is OCR, so is voice recognition, and many other things you probably use and take for granted. I'd suggest you focus on use cases not trying to redefine definitions for an entire area of science and technology based on your own preferences.
Saying "I'm against fully AI generated music" is at least precise, and doesn't throw out detecting cancer along with the AI bandwagon term.
Not AI generated. The ML model isn’t coming up with anything novel^, it’s just converting from one format to another, or extracting data - similar to automatically cropping photos to faces.
It’s still AI, but it’s not the AI system generating something
> Sorry, that's AI. So is OCR, so is voice recognition, and many other things you probably use and take for granted
Have you heard of machine learning?
The current genAI trend is machine learning too so what's the point of this question?
I think the point is that to most people, “AI” has a different meaning than “machine learning”
AI and voice recognition were using "machine learning" for several decades, which is basically just brute force statistics.
ML voice recognition is still far superior to AI-based voice recognition. At its best, Gemini is still less accurate at parsing speech than Dragon Naturally Speaking circa 2000.