OpenAI’s GPT-3 and Other Neural Nets Can Now Write Original Prose with Mind-Boggling Fluency
May 29th, 2022Via: New York Times Magazine:
So far, the experiments with large language models have been mostly that: experiments probing the model for signs of true intelligence, exploring its creative uses, exposing its biases. But the ultimate commercial potential is enormous. If the existing trajectory continues, software like GPT-3 could revolutionize how we search for information in the next few years. Today, if you have a complicated question about something — how to set up your home theater system, say, or what the options are for creating a 529 education fund for your children — you most likely type a few keywords into Google and then scan through a list of links or suggested videos on YouTube, skimming through everything to get to the exact information you seek. (Needless to say, you wouldn’t even think of asking Siri or Alexa to walk you through something this complex.) But if the GPT-3 true believers are correct, in the near future you’ll just ask an L.L.M. the question and get the answer fed back to you, cogently and accurately. Customer service could be utterly transformed: Any company with a product that currently requires a human tech-support team might be able to train an L.L.M. to replace them.
And those jobs might not be the only ones lost. For decades now, prognosticators have worried about the threat that A.I. and robotics pose to assembly-line workers, but GPT-3’s recent track record suggests that other, more elite professions may be ripe for disruption. A few months after GPT-3 went online, the OpenAI team discovered that the neural net had developed surprisingly effective skills at writing computer software, even though the training data had not deliberately included examples of code. It turned out that the web is filled with countless pages that include examples of computer programming, accompanied by descriptions of what the code is designed to do; from those elemental clues, GPT-3 effectively taught itself how to program. (OpenAI refined those embryonic coding skills with more targeted training, and now offers an interface called Codex that generates structured code in a dozen programming languages in response to natural-language instructions.) The same principle applies to other fields that involve highly structured documents. For instance, even without the kind of targeted training that OpenAI employed to create Codex, GPT-3 can already generate sophisticated legal documents, like licensing agreements or leases.
