I’m not a Sound Engineer, I’m an Electronics Engineer - we’re the ones who had to find the right balance between fidelity, bit error rates, data rates and even circuit price when designing the digital audio sampling systems that capture from the analog world the digital data which the Sound Engineers use to work their magic: so I’m quite familiar with the limits of analog to digital conversion and that’s what I’m pointing out.
As it so happens I also took Compression and Cryptography in my degree and am quite familiar with where the term “lossless” comes from, especially since I took that elective at the time when the first lossy compression algorithms were starting to come out (specifically wavelet encoding as used in JPEG and MPEG) so people had to start talking about “lossless” compression algorithms with regards to the kind of algorithms what until then had just been called compression algorithms (because until then there were no compression algorithms with loss since the idea of losing anything when compressing data was considered crazy until it turns out you could do it and save tons of space if it was for stuff like image and audio because of the limitations of human senses - essentially in the specific case of things meant to be received by human senses, if you could deceive the human senses then the loss was acceptable, whilst in a general data sense losing data in compression was unacceptable).
My expertise is even higher up the Tech stack than the people who to me sound like Junior Devs making fun of lusers because they were using technical terms to mean something else, even while the Junior Devs themselves have yet to learn enough to understand the scope of usage and full implications for those technical terms (or the simple reality that non-Techies don’t have the same interpretation of technical terms as domain experts and instead interprete those things by analogy)
Fake it 'till you make it is not applicable to scientific or technical discussions.
Nice content-free slogan.
I’m not a Sound Engineer, I’m an Electronics Engineer - we’re the ones who had to find the right balance between fidelity, bit error rates, data rates and even circuit price when designing the digital audio sampling systems that capture from the analog world the digital data which the Sound Engineers use to work their magic: so I’m quite familiar with the limits of analog to digital conversion and that’s what I’m pointing out.
As it so happens I also took Compression and Cryptography in my degree and am quite familiar with where the term “lossless” comes from, especially since I took that elective at the time when the first lossy compression algorithms were starting to come out (specifically wavelet encoding as used in JPEG and MPEG) so people had to start talking about “lossless” compression algorithms with regards to the kind of algorithms what until then had just been called compression algorithms (because until then there were no compression algorithms with loss since the idea of losing anything when compressing data was considered crazy until it turns out you could do it and save tons of space if it was for stuff like image and audio because of the limitations of human senses - essentially in the specific case of things meant to be received by human senses, if you could deceive the human senses then the loss was acceptable, whilst in a general data sense losing data in compression was unacceptable).
My expertise is even higher up the Tech stack than the people who to me sound like Junior Devs making fun of lusers because they were using technical terms to mean something else, even while the Junior Devs themselves have yet to learn enough to understand the scope of usage and full implications for those technical terms (or the simple reality that non-Techies don’t have the same interpretation of technical terms as domain experts and instead interprete those things by analogy)