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Years in the past Nicholas Carr argued that Google was making us silly, that ease of entry to info was shortening our consideration spans and usually making it exhausting for us to do “deep studying.” Others frightened that search engines like google had been siphoning away readership from newspapers, amassing the money that in any other case would fund journalism.
At present we’re seeing one thing comparable in software program growth with large language models (LLMs) like ChatGPT. Builders flip to LLM-driven coding assistants for code completion, solutions on methods to do issues, and extra. Alongside the way in which, issues are being raised that LLMs suck coaching information from sources reminiscent of Stack Overflow then divert enterprise away from them, at the same time as builders cede essential pondering to LLMs. Are LLMs making us silly?
Who trains the trainers?
Peter Nixey, founding father of Intentional.io and a high 2% contributor to Stack Overflow, calls out an existential question plaguing LLMs: “What occurs once we cease pooling our data with one another and as an alternative pour it straight into The Machine?” By “The Machine,” he’s referring to LLMs, and by “pooling our data” he’s referring to boards like Stack Overflow the place builders ask and reply technical questions. ChatGPT and different LLMs have turn out to be “good” by sucking in all that info from websites like Stack Overflow, however that supply is shortly drying up.
