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Dedicated Mobile Apps For Vibe Coding Have So Far Failed To Gain Traction

4 weeks ago
An anonymous reader quotes a report from TechCrunch: While many vibe-coding startups have become unicorns, with valuations in the billions, one area where AI-assisted coding has not yet taken off is on mobile devices. Despite the numerous apps now available that offer vibe-coding tools on mobile platforms, none are gaining noticeable downloads, and few are generating any revenue at all. According to an analysis of global app store trends by the app intelligence provider Appfigures, only a small handful of mobile apps offering vibe-coding tools have seen any downloads, let alone generated revenue. The largest of these is Instance: AI App Builder, which has seen only 16,000 downloads and $1,000 in consumer spending. The next largest app, Vibe Studio, has pulled in just 4,000 downloads but has made no money. This situation could still change, of course. The market is young, and vibe-coding apps continue to improve and work out the bugs. New apps in this space are arriving all the time, too. This year, a startup called Vibecode launched with $9.4 million in seed funding from Reddit co-founder Alexis Ohanian's Seven Seven Six. The company's service allows users to create mobile apps using AI within its own iOS app. Vibecode is so new, Appfigures doesn't yet have data on it. For now, most people who want to toy around with vibe-coding technology are doing so on the desktop.

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Journals Infiltrated With 'Copycat' Papers That Can Be Written By AI

4 weeks ago
An analysis of a literature database finds that text-generating AI tools -- including ChatGPT and Gemini -- can be used to rewrite scientific papers and produce 'copycat' versions that are then passed off as new research. Nature: In a preprint posted on medRxiv on 12 September, researchers identified more than 400 such papers published in 112 journals over the past 4.5 years, and demonstrated that AI-generated biomedicine studies could evade publishers' anti-plagiarism checks. The study's authors warn that individuals and paper mills -- companies that produce fake papers to order and sell authorships -- might be exploiting publicly available health data sets and using large language models (LLMs) to mass-produce low-quality papers that lack scientific value. "If left unaddressed, this AI-based approach can be applied to all sorts of open-access databases, generating far more papers than anyone can imagine," says Csaba Szabo, a pharmacologist at the University of Fribourg in Switzerland, who was not involved in the work. "This could open up Pandora's box [and] the literature may be flooded with synthetic papers."

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