Summary
Researchers accidentally created a powerful A.I. called the transformer, which can generate and understand language. This technology, initially aimed at improving machine translation, has surprised many by performing various linguistic tasks. As A.I. continues to evolve, it challenges our understanding of language and how machines relate to human communication.
Highlights
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What’s mainly certain, right now, is that linguistic A.I. is changing the relationship between human beings and language. In an age of machine-generated text, terms like “writing,” “understanding,” “meaning,” and “thinking” need to be reconsidered.
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A.I. that can create and comprehend language carries the shock of a category violation; it allows machines to do what we thought only people could.
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For many years, A.I. researchers had experimented with a mechanism called attention, which they hoped might be capable of bridging the divide between efficiency and coherence. Attention allows a neural network to dodge sequentiality by seeking relevance. Instead of looking at each word in order, attention looks at all the words in a piece of text together, evaluating how they are interrelated and which are most important to each of the other words, as it captures the over-all meaning. This is closer to the way people remember a text than the way they read it. If you try to recall the opening paragraph of this article, you might articulate a vaguely connected constellation: Aidan Gomez, couldn’t drink, intern, Google, the uncertain potential of a new technology. Those terms, in any order, might amount to the sense you have retained.
Una descripción clara y sencilla del mecanismo de “atención” que desarrollaron para incorporar en las redes neurales.