We Don't Know What We're Doing

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You can take the kids out of Caerphilly, in other words, but Caerphilly will do its best to pull them back in. In How Sad, How Lovely another lonely narrator finds solace in a friendship with a neighbour, the grotesque humour of his worms affliction highlighting his marginalised role.

We Don’t Know What We’re Doing by Thomas Morris review – an

They are mostly young – teenagers to twentysomethings – and their listlessness says much about a society that has lost direction. After her husband remortgages their home and absconds to Australia to find himself, Amy is caught between the demands of her ailing mother and her three children. Some of these systems' abilities go far beyond what they were trained to do—and even their inventors are baffled as to why. This ability to infer the structure of the outside world is not limited to simple game-playing moves; it also shows up in dialogue. Here, though, we prefer to identify with thrusting metropolises or chocolate-box villages, and small towns are consigned to a dreary no man’s land between the two.They exist in the popular imagination as drab, deindustrialised zones of dead-end jobs and boarded-up high streets, where the schools are on the slide and the young people either get out or give up. All of which creates an unmistakable whiff of social Darwinism; the suggestion that birthplace is somehow fate. Hopkins of the Massachusetts Institute of Technology; David Bau of Northeastern University; and Fernanda Viégas, Hanspeter Pfister and Martin Wattenberg, all at Harvard—spun up their own smaller copy of the GPT neural network so they could study its inner workings. In 17 a teenager mourns his first love: "I'll put it this way: when we broke up, it felt like I lost thirty pints of blood.

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In the final story, Nos Da (the Welsh for "good night"), Morris envisions an alternative world where a father watches his family through a camera as he contemplates his mediocre relationship with his new girlfriend.If you are given a whole lot of game scripts, trying to figure out the rule behind it is the best way to compress,” he adds. Li says he thinks the system learns this skill because it is the most parsimonious description of its training data. In fact, Morris uses his small-town setting to flag up a universal truth: that most of us, wherever we come from, will live ordinary lives, and that it’s at the moment when youth fades out that we come face to face with it. So it came as a surprise that LLMs do, in fact, learn from their users' prompts—an ability known as in-context learning.