Generative AI is being pitched as the solution for everything from boosting productivity to replacing an aging population of workers. But so far, it's best when there's less on the line.
isn't 100 percent accurate — and it's prone to confidently asserting fiction as fact. So in many ways it's better suited for tasks where there isn't one right answer than for many of the fact-based uses where it's being applied, like search.
earlier this week: "A 20% error rate in a text generator is 'this thing is telling lies and making stuff up' - but a 20% error rate in an image generator is 'I’m not quite sure where the door is, but honestly who cares when it looks like that.' "to Evans. "The more the focus is on creativity for generative technology the better," Sinofsky said. "Until sourcing and verification are addressed, using it for fact-based works is like using AutoCorrect without backspace/undo in that the errors will just pile up."Being able to describe a scene and have it come to life will fundamentally shift how movies, video games and other works are created. Programs like Dall-E 2, Stable Diffusion and Adobe's new Firefly are already quite good at creating powerful images from a few words of text. Generative AI doesn't have to deliver a finished product to be useful. Artists and writers who have embraced the technology praise its ability to spark new ideas and serve as a launchpad for human creativity. Of course, plenty of legal and ethical issues remain, from copyright issues over how the engines were trained to the propensity for the output to perpetuate bias and stereotypes included in training data. The art world, for example, has been divided, with
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