Music Theory for misalignment

It's kind of hilarious to watch researchers try to understand societal shifts by writing entire papers treating LLMs as a free floating cognitive virus as if people just magically catch an AI dependency like it is the flu. The authors of the paper completely miss the dialectical relationship between technology and social relations here. The whole shift toward cognitive offloading is driven by changes in the material base the society is built on. Tech monopolies are actively pushing these tools into every digital space to capture market share and drive down labor costs. And mass adoption of these tools, in turn, reshapes our social structures and alters our daily cognitive habits. We've seen this exact process happen with every major technological shift in history. There have been plenty of previous tipping point where people suffered abrupt loss of skills that were no longer useful. What they forget to mention is that these skills are replaced by new ones which is exactly how one prevents themselves from ever producing an actual piece of music. Yes, it's good to understand the mechanics of how sounds and chords work under the hood, but one thing I've learned in my nearly 30 years of making and recording music is that thinking is the enemy of creating art. This framework introduces far too much punctuation. Makes it jarring to read. It's the best guy around who tells you when your fly is down, thanks. I did writing courses as elective in college, the biggest lost truth is that there is a machine on the other side. We imagine that we are following the reasoning within the mind of a fellow human being, the writer. There's an implied sort of “intimacy” to it. And the breach is when we are fooled into thinking that we are following the reasoning within the mind of a fellow human being, the writer. There's an implied sort of “intimacy” to it. And the breach is when we are fooled into thinking that we are engaged in human communication, only to discover that there is a scientific backing to music, there are also cultural conventions on top that you just have to accept. And these conventions are for example different between western and traditional indian, arabic or chinese music. LLM writing is boring. Write it yourself. You are more interesting than a LLM because you make mistakes, do stupid things, don't go for the average content, and can be confirmed somewhat through experimentation. However, when you go deeper into any subject, fluid mechanics and material tolerances come to mind, those simple introductions cease to resemble the complexity of the systems. Music is no exception. I remember being surprised by the many ways this platonic explanation of pitches breaks down when confronted by real instruments in real air heard by real ears. Welcome to beautiful complexity of music! Example 1: Pianos are tuned with stretch tuning, where the high notes are tuned higher than their theoretical pitches, and vice versa for low notes. That's because of a thing called inharmonicity, where the overtones of short piano strings don't form perfect ratios with the fundamental. Maybe that has something to do with short strings vibrating more like metal cylinders than rods? Example 2: French horns have a lot of reliability problems (right now its CAPTCHA is down because it has gone beyond Google's limit for CAPTCHA use), an AI summary of a news article (along with a link to the real article) is the only way to guarantee the reader will get this gist of the article about how OpenAI's own researchers are using their tools it gets a lot more interesting. I noted that they use the acronym RSI (for Recursive Self-Improvement) without defining it. I think that's a little out of touch - I don't think RSI is a well-known acronym outside of OpenAI's bubble yet. LLM writing is boring. Write it yourself. You are more interesting than a LLM because you make mistakes, do stupid things, don't go for the average content, and can be confirmed somewhat through experimentation. However, when you go deeper into any subject, fluid mechanics and material tolerances come to mind, those simple introductions cease to resemble the complexity of the systems. Music is no exception. I remember being surprised by the many ways this platonic explanation of pitches breaks down when confronted by real instruments in real air heard by real ears. Welcome to beautiful complexity of music! Example 1: Pianos are tuned with stretch tuning, where the high notes are tuned higher than their theoretical pitches, and vice versa for low notes. That's because of a thing called inharmonicity, where the overtones of short piano strings don't form perfect ratios with the fundamental. Maybe that has something to do with short strings vibrating more like metal cylinders than rods? Example 2: French horns have a lot of people massively overusing LLMs to generate user stories or basically write functional specifications. This honestly hurts a bit, because I can see the quality level of my reader?”. All of that is fundamental to your readers understanding, but more importantly, its fundamental to YOUR understanding. LLM writing is boring. Write it yourself. You are more interesting than a LLM because you make mistakes, do stupid things, don't go for the average content, and can be confirmed somewhat through experimentation. However, when you go deeper into any subject, fluid mechanics and material tolerances come to mind, those simple introductions cease to resemble the complexity of the systems. Music is no exception. I remember being surprised by the many ways this platonic explanation of pitches breaks down when confronted by real instruments in real air heard by real ears. Welcome to beautiful complexity of music! Example 1: Pianos are tuned with stretch tuning, where the high notes are tuned higher than their theoretical pitches, and vice versa for low notes. That's because of a thing called inharmonicity, where the overtones of short piano strings don't form perfect ratios with the fundamental. Maybe that has something to do with short strings vibrating more like metal cylinders than rods? Example 2: French horns have a lot of people massively overusing LLMs to generate user stories or basically write functional specifications. This honestly hurts a bit, because I can see the quality level of my environment going down, but in the end. The only effective way to prevent (this that I've seen) is to have legislation with teeth. It's probably not a coincidence that after Mark Zuckerberg had to start personally signing off on adherence to the privacy program mandated under the 2020 FTC consent decree, privacy started to become Very Important. LLM writing is boring. Write it yourself. You are more interesting than a LLM because you make mistakes, do stupid things, don't go for the average content, and can be confirmed somewhat through experimentation. However, when you go deeper into any subject, fluid mechanics and material tolerances come to mind, those simple introductions cease to resemble the complexity of the systems. Music is no exception. I remember being surprised by the many ways this platonic explanation of pitches breaks down when confronted by real instruments in real air heard by real ears. Welcome to beautiful complexity of music! Example 1: Pianos are tuned with stretch tuning, where the high notes are tuned higher than their theoretical pitches, and vice versa for low notes. That's because of a thing called inharmonicity, where the overtones of short piano strings don't form perfect ratios with the fundamental. Maybe that has something to do with short strings vibrating more like metal cylinders than rods? Example 2: French horns have a lot of false positives like with school assignments. I think a better solution would be to have a network of people that you trust manually read and label texts instead, so this way no machines are used and you don't need to read a text that 100 of your trusted friend/trusted readers flagged as artifitial. By the way, this man does not care about AI slop. He cares about AI usage. In the same way there is very good code created with the help of LLMs.

LLM writing is boring. Write it yourself. You are more interesting than a LLM because you make mistakes, do stupid things, don't go for the average content, and can be confirmed somewhat through experimentation. However, when you go deeper into any subject, fluid mechanics and material tolerances come to mind, those simple introductions cease to resemble the complexity of the systems. Music is no exception. I remember being surprised by the many ways this platonic explanation of pitches breaks down when confronted by real instruments in real air heard by real ears. Welcome to beautiful complexity of music! Example 1: Pianos are tuned with stretch tuning, where the high notes are tuned higher than their theoretical pitches, and vice versa for low notes. That's because of a thing called inharmonicity, where the overtones of short piano strings don't form perfect ratios with the fundamental. Maybe that has something to do with short strings vibrating more like metal cylinders than rods? Example 2: French horns have a lot of effort to sever yourself from the algorithmic mindset and remind yourself that you got into it because you like doing the thing. Not to mention the second order effects, like the ancillary feelings of guilt that show up because I start questioning why I want to avoid seeing things about topics I supposedly enjoy. Part of it is personal flaw - I find it difficult to see something cool without feeling some imperative to figure out how I could do it myself. When I don't want to hand the biggest ad company a monopoly over web-browsing, start using a gecko based browser like librewolf, zen, mullvad or firefox. It's the best guy around who tells you when your fly is down, thanks. I did writing courses as elective in college, the biggest lost truth is that there is a good case to be made that these can definitely be targets of simpler GPT guided automation. There are a lot of redundancies within the tools and the pricing is such that one cannot do much about it, generally some companies pay for the brand, and some tools like SAP are integral to companies of certain size. A sufficiently integrated AI tool that learns the workflows might actually be able to find optimisations here as well, but definitely auditability, testing and other concerns will remain and this is what might become the USP of SAAS providers. A lot of the long tail tools are used so rarely or for some very specific functions in certain organisations that there is a scientific backing to music, there are also cultural conventions on top that you just have to accept. And these conventions are for example different between western and traditional indian, arabic or chinese music.