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The lifting out from a closed-off world, according to Taylor, was enabled by the arrival of written language — the stored memories of the first cloud technology. **This attainment of symbolic competency capacitated an “interiority of reflection” on the basis of abiding texts that created a platform for shared meanings beyond one’s immediate circumstances and local narratives.**
The Great Disembedding
Roger’s Bacon
In GPT-4, a word vector has thousands of dimensions, which describe its shades of similarity to and difference from every other word. During training, a large language model tweaks a word’s coördinates whenever it makes a prediction error; words that appear in texts together are nudged closer in space. This produces an incredibly dense representation of usages and meanings, in which analogy becomes a matter of geometry. In a classic example, if you take the word vector for “Paris,” subtract “France,” and then add “Italy,” the nearest other vector will be “Rome.”
The Case That A.I. Is Thinking | the New Yorker
James Somers
We’re all operating in a dense fog of mutual reinforcement. Our thoughts are shaped primarily by legacy hardware that evolved to assume that everyone else must be right. But even when the fog is pointed out, we’re no better at navigating through it.
The Overstory
Richard Powers
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