Look, it really pains me to pick at something written by “Ludwig Yeetgenstein”, a nom de plume that truly brings me joy, but I care too deeply about the topic. The author seems to have a lot of interesting stuff to say but the whole concept of the piece is risible. Yeetgenstein, I want to read more of your commentary! But not if you feel like you have to structure it all around “machine learning is like vibes, that sounds like a good pitch, so let’s pretend it’s all equivalently black-boxy… and the kids like 100 gecs these days, right?”

…g explanation being overlooked. While seemingly open-ended and allowing for an infinite recombination of elements, the idea of “vibes” is reductive. It discourages the more difficult work of interpretation and the search for meaning that defines human experience. It diverts attention away from narrative and moral implications in favor of foregrounding the idea of affect as inexplicable, ineffable — a matter of chance correlation of elements rather than something that requires deliberate causal explanation. The vibes framework may hone our abilities to identify settings like “cozy” or “cursed,” but it doesn’t give instructions on how we might build them or avoid them in our lives. As an analytic, vibes don’t connect feelings and consequence; as such, it is symbiotic with passive modes of media consumption. Whereas philosophers, psycholo…

I hate this. How is the work of interpretation discouraged? Giving vague description to something doesn’t preclude better description; to encourage people to express the idea that there’s something coherent about, well, something is to create the space for further interpretation. A vibe is a term for a fetal stage, something emergent still emerging1. If you already had a better name for it you’d use that. Articulating that you think there’s a there there is a meaningful step2! We can analyze whether cottagecore is fashy because people recognized a vibe and nurtured it into a whole… thing. (A thing that is sometimes fashy)

…em into useful tools in reality. As the salience of vibes as a way of (not) explaining experience has grown, so too have the applications of machine learning and neural networks. This parallel may not be a mere coincidence. As Peli Grietzer has pointed ou…

NARRATOR: ...it was a mere coincidence.

…rain and rain implies umbrella. Instead it effectively identifies a “rainy” vibe through correlations of an initially arbitrary set of parameters. Despite such limitations, neural…

Forcing a premise for a pitch? This is not the use of “vibe” I’d recognize and it’s asserted so confidently!

…cy theories and disinformation. For all the hype that surrounds them, neural networks can’t reflect or explain anything deeper about cultural or societal phenomena any more than sharing a favorite character from The Office can predict long-term compatibility with a Tinder match. These systems can only instrumentalize taste; they turn any expression of self into a reductive data point meant to generate more data at the same level. They presuppose that “liking” just means more “liking” and that is as deep as our desire can be. As with vibes, these metrics carry no context or narrative; they can tell you nothing about how or why something might be desirable, only that they vaguely seem like they might be desirable because they seem similar to other things that are desirable. This opacity encourages users to disregard the possibility of understanding their desire at a deeper level, of probing it, developing it, attenuating it, or even negating it if need be. The vibe induced by machine lea…

Well, hold up. A lot of the description of neural networks here is really good, but this paragraph has gone in a bad direction.

I still need to read Nabokov’s Favorite Word Is Mauve, but, like, the digital humanities exist, man. Computer-aided close readings are not new. How are you defining “deeper” that you’re so sure “anything deeper about cultural or societal phenomena” can’t even be reflected?

In addition: everyone working with neural networks knows to probe, develop, attenuate, and sometimes negate their output! Telling people with no technical education that “an AI said X” may lend X an unearned reputation of solidity, but that’s just not how the people who build these systems work with them. I’m not saying the author doesn’t know that, but…for the metaphor of this piece, it matters exactly who we’re saying is parallel to the… vibe-recognizer. Is it the ML engineer? Is it the recommendation algorithm’s victim? Are we just saying “pattern-recognition is bad now”?

…ions that have already existed Consider the vibes-based music categories like hyperpop and PC Music, which serve as an avant-garde of the moment, mixing a wide variety of other genres with hyper-specific cultural references and inside jokes. The spirit of the genre can be …

Are we supposed to accept prima facie that hyperpop is more “vibes-based” than other genres? Because… I don’t.

…dissatisfaction and depression. These masked bad vibes are actually pointing toward urgent questions: How do we break out of this loop? How do we escape this cycle of political deadlock, Covid lockdown, and the dread of climate catastrophe? How do we create new art forms that aren’t just remixes or nostalgic revivals of existing ones? PC Music can pose the question but can’t become the answer; it can only manifest the problem in a heightened, intensified form. The vibes are off, but they’re …

literally what music do you think can become the answer to Covid lockdown

…a heightened, intensified form. The vibes are off, but they’re off fundamentally because they focus only on feelings and emotional connections that have already existed. They don’t provide or imagine pathways to new futures; they allow only for an understanding of what feels good or bad based on experiences that have already happened, things that have already been seen. In other words, “vibes” are sim…

This is at its core just the modernist’s complaint about postmodern recombination, and it was boring by the year 2000. You can’t analyze curatorial intent as artistic intent, yada yada. (and you can’t make real music by sampling, kids!!)

…gs that have already been seen. In other words, “vibes” are similar to the approximations that machine learning systems use, and the two feed off of each other synergistically. The situation is precisely enca…

lmao

…t ceases to be a good measure.” Content systems optimized by machine learning amplify the repetitive quality of internet content by identifying and recycling the same topics that generate interest and controversy, and the tendency spreads elsewhere in culture, such as in the continuous, unnecessary reiterations of movie franchises like Star Wars or The Matrix. The vibes are gamed until they become stale, and an increasing facility in vibes makes this trend all the more evident and noticeable. Some may worry about whether po…

This has nothing to do with “vibes”, but is nonetheless true and worth talking about.

  1. If you read this to yourself and think “lol she doesn’t know what emergent means” go and do penance. ↩

  2. This is where I would make a joke about attention mechanisms in deep learning if I were committed to the author’s schtick. ↩