An anonymous reader quotes a report fro SFGATE: From "rizz" to "meat proxy," words and phrases have fallen in and out of favor for centuries. Culture, politics and technological development have long influenced these trends, and now, new research shows that ChatGPT is beginning to influence how humans communicate. The findings from a team at the Pew Research Center show how, in a short time since OpenAI released ChatGPT in November 2022 and other chatbots followed, the use of certain words and phrases has spiked on the web. The researchers, led by data scientist Samuel Bestvater, studied nearly half a million English language webpage texts in snapshots over the past five years. Not only has AI-written text become more common, but it could also be influencing how people write, such as trying to avoid using the "tells" that have become associated with AI-generated text. Bestvater and his team detected double the number of em dashes, double the frequency of particular words -- such as "delve," "testament" and "interplay" -- and nearly triple the use of a phrasing known as negative parallelisms ("it's not X, it's Y"), as well as a 63% increase in Oxford commas. But while AI labs continually try to tweak their models to generate more humanlike text, the people they're mimicking aren't staying the same. "Human writers might also be changing the way that they write in response to AI. I've seen some anecdotal evidence of people saying, 'Now I avoid em dashes,'" Bestvater said. "If human writers are adjusting their choices of words and phrases and punctuation to try to differentiate their writing from AI-generated text, then you would see a pattern that looks sort of like that in the chart." "You can see changes in people's speech. People are tending to more commonly use these low-frequency words in their speech because they're spending a lot of time listening to or reading AI-generated content," said Roger Kreuz, a cognitive psychologist at the University of Memphis who recently wrote about how difficult it is for people to identify bot-written text.

Read more of this story at Slashdot.

Google is imposing new memory-use limits on Android apps as the AI data center boom contributes to a broader memory chip shortage that could leave lower-cost phones with less RAM. Developers will have until February 2027 to meet new thresholds for memory and bitmap usage. To aid developers, Google is adding tools to flag apps that exceed the limits and help prevent slowdowns and crashes. TechCrunch reports: The company explains that the mobile industry is now facing "significant hardware supply constraints that are altering device memory availability," which can then, in turn, affect the consumer's experience with their devices. To address this, Google is now establishing new performance thresholds across several areas, like dynamic memory usage and bitmap usage. In addition, Google is adding code optimization requirements designed to prevent things like app slowdowns and crashes related to performance.

Read more of this story at Slashdot.

Wired reports that OpenAI is testing a new "Persistent mode" for Codex that would let the agent keep working until explicitly "put to sleep," proactively creating follow-up tasks for itself across sessions and using prior interactions and knowledge of the user to decide what to do next. Code alluding to the feature was spotted in the product's code base, though it has not been rolled out or officially announced yet. From the report: Persistent mode appears in Codex's "reasoning effort" menu, in which users can select the level of computing power, tokens, and time they want to allow for an AI model to "think" before answering a prompt. It seems to be one of OpenAI's most computationally intensive settings. When users have selected Persistent mode, OpenAI's code base reads that Codex will "continue working until put to sleep." That's a stark contrast to currently available modes, which will stop working on a task after a few minutes or hours, even if it's not complete. In another file in the code base, OpenAI describes a feature within Persistent mode called "proactivity." This appears to be a type of system prompt for agents in Persistent mode, which are told that their work is not done when they finish answering a user's request. Instead, the agent is instructed to proactively create follow-up tasks for itself. The agent is capable of working on those tasks across sessions and using past user interactions and "knowledge of the user" to decide what to work on. It also has a tool to message the user without being asked but is told to send these sparingly. The instructions also set limits for the agent, according to the file. The agent is told that Persistent mode does not expand what it is allowed to do and that altering anything outside the user's own system requires the user's approval first -- seemingly intended to limit how dangerous a persistent AI agent could be. The file sits in the shared core of Codex rather than in the code specific to the terminal, seeming to suggest the proactivity feature is intended for more than the command line tool.

Read more of this story at Slashdot.

An anonymous reader quotes a report from Ars Technica: Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents [including Claude, OpenAI's Codex, and Nous Research's Hermes]. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware. The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site's content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site's content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here. "The trust model is broken," Alon Hertz, one of the researchers, wrote in an interview. "Agents treat vendor docs as ground truth and don't question them -- and neither do the humans supervising them. Agentic AI usage is exploding, and agents are spreading across every layer -- SaaS, cloud, endpoint. As they multiply, so does the supply-chain surface, and today's guards don't cover it." "An agent doesn't distinguish between a page and a command," the researchers wrote Thursday. "Everything it reads is input, and every input is a potential instruction. Which means the entire corpus of published data that agents are now wired to consume has silently become an execution surface -- and almost none of it carries the integrity guarantees we apply to actual code."

Read more of this story at Slashdot.