Nameless Feeling

In our present technological era, humans have also needed a new framework to avoid drowning in the daily firehose of entertainment, media, and information. Given this setting of increasing complexity, it becomes more appealing to use an associative concept like “vibes” as a simplifying framework for understanding or self-expression. If we can’t mak... See more

Some might call this concatenation of elements a “vibe”: something that’s difficult to pin down precisely in words but that’s evoked by a loose collection of ideas, concepts, things that can be identified by intuition rather than by a prescribed logic.

What the neural network “learns” is emergent rather than deduced. For example, it may notice a pattern that if it’s cloudy, then people are more likely to carry an umbrella. But it would not be able to explain that this is because cloudy implies rain and rain implies umbrella. Instead it effectively identifies a “rainy” vibe through correlations of... See more

In our present technological era, humans have also needed a new framework to avoid drowning in the daily firehose of entertainment, media, and information. Given this setting of increasing complexity, it becomes more appealing to use an associative concept like “vibes” as a simplifying framework for understanding or self-expression. If we can’t mak... See more

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 w... See more

Although the practical success of neural networks is still undeniable, it must be observed that their most powerful applications are in domains where rules are set in advance and don’t change over time — where the goals are clearly defined. The way you win a game of chess or Go is fixed and unambiguous. Protein folding is constrained by the laws of... See more

The idea of “vibes” discourages the more difficult work of interpretation, foregrounding the idea of affect as inexplicable, ineffable

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 encapsulated by Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.”

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 p... See more