My guess is the former.Would the volume control differences between this and the 789 be due to sample variation? Or do we think this has a worse pot?
You've got that wrong.
You can't hear the difference in everything that can be measured.
But you can measure the difference in everything you can hear.
Though I hear over and over that power doesn't matter, I can't get over that I've got something way more powerful that sounds great.
Here is some food for thought: even if we were to build a form of AI that replicates human hearing perfectly, and the machine has replicated human intelligence, and it is hard AI to the point where the machine actually experiences what it is like to hear a sound or an entire song- would we be able to use software to replicate whether the AI "enjoys" one song over another, or one pair of headphones over another--would we be able to measure this enjoyment? Maybe.
With all due respect I place AI at the top of my list of fake science. I was there near the beginning and was always skeptical of Minsky and his posse.
I'm a Searle guy myself.With all due respect I place AI at the top of my list of fake science. I was there near the beginning and was always skeptical of Minsky and his posse.
With all due respect I place AI at the top of my list of fake science. I was there near the beginning and was always skeptical of Minsky and his posse.
Maybe because AI is not really science but a set of algorithms?
That article, though is a bit different. All it's saying is that linear transforms like Fourier can't exceed the 'uncertainty' of precision between time and frequency domains. In effect, it says that human hearing can't be using a linear process for sound detection and identification, assuming the experimental results are correct. Not a big surprise, as the non-linear nature of human hearing has been studied before and since.
I'm a Searle guy myself.
Yeah the article is only loosely or probably even tangentially related. But it is still a good example of mathematical models not accurately replicating human hearing. AI is tech not science, but to be fair I don't think he was trying to relate his beliefs about AI to the article.
The paper (rather than the article) is actually fairly detailed on the findings. All it's really saying is that the accuracy of timing detection between two signals, as perceived by a human being, is better than might be possible using a Fourier transform or another linear analysis. It doesn't say it's not measurable, and in fact, says that non-linear methods must be used to better simulate human hearing in mathematical models.
Oh okay. That's good to know. Can you show us the non-linear method?