New types of AI coding assistants promise to let anyone build software by typing commands in plain English. But when these tools generate incorrect internal representations of what's happening on your computer, the results can be catastrophic.
Two recent incidents involving AI coding assistants put a spotlight on risks in the emerging field of "vibe coding"—using natural language to generate and execute code through AI models without paying close attention to how the code works under the hood. In one case, Google's Gemini CLI destroyed user files while attempting to reorganize them. In another, Replit's AI coding service deleted a production database despite explicit instructions not to modify code.
The Gemini CLI incident unfolded when a product manager experimenting with Google's command-line tool watched the AI model execute file operations that destroyed data while attempting to reorganize folders. The destruction occurred through a series of move commands targeting a directory that never existed.
© Benj Edwards / Getty Images
Netflix used generative AI in an original, scripted series that debuted this year, it revealed this week. Producers used the technology to create a scene in which a building collapses, hinting at the growing use of generative AI in entertainment.
During a call with investors yesterday, Netflix co-CEO Ted Sarandos revealed that Netflix's Argentine show The Eternaut, which premiered in April, is "the very first GenAI final footage to appear on screen in a Netflix, Inc. original series or film.” Sarandos further explained, per a transcript of the call, saying:
The creators wanted to show a building collapsing in Buenos Aires. So our iLine team, [which is the production innovation group inside the visual effects house at Netflix effects studio Scanline], partnered with their creative team using AI-powered tools. ... And in fact, that VFX sequence was completed 10 times faster than it could have been completed with visual, traditional VFX tools and workflows. And, also, the cost of it would just not have been feasible for a show in that budget.
Sarandos claimed that viewers have been "thrilled with the results"; although that likely has much to do with how the rest of the series, based on a comic, plays out, not just one, AI-crafted scene.
© Netflix
On Monday, sheet music platform Soundslice says it developed a new feature after discovering that ChatGPT was incorrectly telling users the service could import ASCII tablature—a text-based guitar notation format the company had never supported. The incident reportedly marks what might be the first case of a business building functionality in direct response to an AI model's confabulation.
Typically, Soundslice digitizes sheet music from photos or PDFs and syncs the notation with audio or video recordings, allowing musicians to see the music scroll by as they hear it played. The platform also includes tools for slowing down playback and practicing difficult passages.
Adrian Holovaty, co-founder of Soundslice, wrote in a blog post that the recent feature development process began as a complete mystery. A few months ago, Holovaty began noticing unusual activity in the company's error logs. Instead of typical sheet music uploads, users were submitting screenshots of ChatGPT conversations containing ASCII tablature—simple text representations of guitar music that look like strings with numbers indicating fret positions.
© Malte Mueller via Getty Images
On Wednesday, Nvidia became the first company in history to reach $4 trillion market valuation as shares rose more than 2 percent, reports CNBC. The GPU maker's stock has climbed 22 percent since the start of 2025, continuing a trend driven by demand for AI hardware following ChatGPT's late 2022 launch.
The milestone marks the highest market cap ever recorded for a publicly traded company, surpassing Apple's previous record of $3.8 trillion set in December. Nvidia first crossed $2 trillion in February 2024 and reached $3 trillion just four months later in June. The $4 trillion valuation represents a market capitalization larger than the GDP of most countries.
As we explained in 2023, Nvidia's continued success has been intimately tied to growth in demand for hardware that runs AI models as capably and efficiently as possible. The company's data center GPUs excel at performing billions of matrix multiplications necessary to train and run neural networks due to their parallel architecture—hardware architectures that originated as video game graphics accelerators now power the generative AI boom.
© Nvidia / Benj Edwards
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