A and B examples are convincingly "human". It is complete nonsense to say otherwise. The AI versions are simply giving the music a kind of commercial streamline production treatment; treatment that many listeners need to accept the music as viable. Some will fight brutally to hide this need here. No offense, but both a and b are thoroughly cliché. The AI is not sucking away some grand uniqueness of expression here. I have heard both raw and produced countless times. Humans are generative AIs already -- fighting machines that do it is ironic and dishonest. Sure the AI process may be robbing some of the "honesty" of the performance. But you guys aren't unique like Daniel Johnston when you are unfiltered so I don't see a problem with either version. The studio is a place of magic and sonic makeup. If you want to wear makeup, go for it.
OpenAI offered ChatGPT to the world. A large, monied cross-section of the world had yet to throw its capital behind the Large Language Model technology that made the ChatBot possible. While it is fair to see AI development now as a global imposition, OpenAI did not have the agency as a 2022 startup to impose on the scale we see now.
I have flirted with the idea of returning to Slashdot, as I have noticed a few examples of suspect conflict-of-interest moderation occurring here on HN, given its y-combinator hosting; particularly with respect to posts related to prediction markets.
For typical listening (though humans can perceive bone-conducted vibrations up to 100 kHz or even 120 kHz) 16-bit-fixed/44.1kHz is a high-fidelity transport format. As a DSP researcher, I prefer 32-bit-float/44.1kHz as a transport format. I often upsample to 32-bit-float/188.2kHz or even 32-bit-float/192kHz for signal processing applications such as high-fidelity reverberation via direct and FFT convolution. While the author advocates for the transport to ear use case, I would argue that 24-bit/192kHz provides greater fidelity and resolution for sound processing. I found the pedantic arrogance of the author to be annoying. But yes, the sampling theory is an important consideration -- but so is the quality of the actual digital filters used in the DAC->ADC pipeline. They are much more forgiving and less lossy at 192kHz.
"An LLM predicts the next word based on all the words before it. That is the whole story. There is no idea sitting underneath." At most, and I will argue for less, that is half the story. This egregious over-simplification doesn't account for training and the massive dimensional space of thought it forms. Given that frontier models likely have trillions of parameters, the combinatorial space of ideas within approaches the infinite -- hardly zero.
This is a totally fascist musical bias -- I have been using spectral techniques in music since the late 1980s. It has been common for decades. "Unnatural" spectral packet distortion is a component of a wide-breadth of existing music that pre-dates modern generative AI. I am confident that the false positives will be overwhelming and unfair to many artists. Such a cowardly and lossy solution.
Given that Tidal will likely, and ironically, utilize AI to determine what music is considered AI, the decision to block monetization of AI categorized music is likely also unfair to artists who use spectral DSP and/or sample from AI generated sources though largely compose music in a manner similar to other common computer mediated music studio workflows. Such music may very well land in the realm of false positives. This is another step by streaming platforms which funnels and restricts musical creativity.
I don't understand how $180k was enough in San Francisco at any time in the last 15 years -- unless you were partnered with someone with a comparable salary.
I disagree with the trope -- (AI effects) "the slow dulling of our intellects". I am old enough to remember my career change, being a developer in the Apple ecosystem, confident with Objective-C and native system libraries in iOS and MacOS. I changed direction using a very different software stack in cloud services as a data engineer with deep utilization of Clojure. I have personal projects that I occasionally would return to in the former world -- often a decade or more later. I saw what I forgot immediately; but soon after, with engagement, I saw how quickly I was able to remember. Extended use of AI for me has exactly this footprint. Even "use it or lose it" is wrong -- "use it when you need to" is honestly more like it -- the brain is plastic. Some AI fears are warranted, this isn't one of them.
I hope some have already thought of this addition to the AI-inundated academic's bag of tricks -- in college and graduate school I was fortunate to have some important one-on-one conversations with professors, guests and peers where I had dialogues which meaningfully stimulated and advanced my thinking in a variety of subjects. It is clear that frontier models can provide similar opportunities on demand in nearly any subject. One assessment could be student sharing of raw chat logs on a course relevant topic where particular questions were engaged and discussed. The focus is not on the prose product, but the development, the grappling and the questions. There is intellectual value here in the depths of the nested questions, corrections, and unique additions made by the student during the exchange. If not a substitute for an essay, it could be required pre-planning for it.
"Yes, going back to paper and pencil strains our current resources, but is a likely necessity" -- When I reached this sad, arthritic point in the article it was clear that the author has no constructive idea about what happens next in education. There is no critical dialogue regarding assessment and its necessity. There is no critical understanding and projection for what intelligence as a service represents for society. Just a simple monastic shrug and a familiar scent of old world pencil lead.
Describing California as "the Europe of the United States" ignores its essential narcissism -- defining California in terms of Europe would be met with contemptuous pashaws, even if the balkanized ethnic enclaves found there, at a scale larger than anywhere in the U.S. -- not even New York, resemble Europe. The Asian communities will also wonder if you can find Vietnam on a map -- would guess you think it is in the Mediterranean.
I made a Wordle solver in Clojure a while back which is backed by an English word frequency database. My family believes it is cheating to use it. Much more fun to write that code than to play the game though :D
If attractive, cloud providers could develop open models with their own investment, and sell hosted access as a business model. While Google checks these boxes, I haven't seen a Google much marketing focus upon their open models (Gemma) coupled with hosting. groq could conceivably train its own models, but groq's business model hosts open models (GPT OSS, Qwen 3, Llama 4 are currently their prominently advertised models on their site... which seems out of date to me) trained by other organizations.
Even a used Nissan Leaf with degraded batteries is a viable vehicle in many U.S. cities. I would not call these markets "niche", there are many mid-large metropolitan population centers where they are practical. To use "niche", is either a political denial or ignorance of the population distribution of the United States. They are popular where I live, I drove one as a primary vehicle for 8.5 years, and I have purchased another used Leaf for my teenager. The empty pickup truck is also a "niche" vehicle with this usage -- it clearly isn't an appropriate choice for every driving need and locale.
I applaud this, particularly as I view Zig as a viable alternative to rust for many applications. Do I think rust is a positive addition to the Linux kernel. Absolutely. Would I reach for rust or Zig first when I was implementing a real-time audio synthesizer if I had to choose between the two? Unless Rusteze, a Clojure dialect hosted on rust existed, I would choose Zig. I sense a hegemonic power growing behind rust, and I think we need to support a breadth of alternatives in how we invoke computation.
I don't think Dario is completely evil, but he can't see his obvious naiveté that the rest of us see clearly (vis a vis the Trump administration), and his paternal hubris, only Anthropic should win and control AI, should be perceived as far worse than Bill Gate's desire to control the internet in the 90s. The fact that Microsoft invested so heavily in OpenAI blinded me to Anthropic's potential villainy for years.