Applied to hobbyists’ alt-history cars, this works plenty well. Drawing on the established design languages of specific eras and existing model lineups makes creations credible and recognizable. Wood’s 1979 BMW X5 looks believable because it mostly draws on recognizable E12-generation design cues and stretches them in the way that BMW translates today’s sedan styles onto complimentary SUVs.
To be sure, this reassurance isn’t entirely rosy. Stock photographers and producers of simple graphics will soon see competition from vendors using these tools to pump out dozens more images to order — images which may well have been trained on their own web-scraped work.Article content Professional calculations are changing too: “If a new [artist] comes to the scene,” Arellano asks himself ”what I can do to improve, to match.” It’s a healthily competitive game with some fairness to the rules, but one that plays differently with AI. There’s little projecting what’s next for the technology, and it’s not unreasonable to wonder whether a more specialized future tool might be developed for CAD or 3D rendering.
Arellano takes similar comfort in the knowledge that his clients value his ability to tailor fine adjustments to their needs, and to nail particularly fine details for precise projects. In the meantime, all three creatives envision any such tool — 2D or 3D — more as a stepping-stone to help give shape to or sketch out vague ideas.
Comfortable with AI’s eventual but seemingly limited role alongside so many other automotive design tools, Hubers has bigger automotive starches to fry.Article content1979 Porsche Cayenne AI renderIt’s taken less than a year for AI imaging to advance from comical academic curiosity to paradigm shift, and the maturation of language models like ChatGPT points to a similar trajectories for the written word.
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