Just a week after a report suggested that Samsung is scrapping plans for a second-gen Galaxy “Edge” phone due to low sales of the Galaxy S25 Edge, it looks like Apple may be scaling back production of its ultrathin iPhone Air for similar re…
Just a week after a report suggested that Samsung is scrapping plans for a second-gen Galaxy “Edge” phone due to low sales of the Galaxy S25 Edge, it looks like Apple may be scaling back production of its ultrathin iPhone Air for similar reasons. Maybe people aren’t as happy to trade battery life and features for […]
The post Lilbits: Playable LEGO Game Boy kits, AI web browsers, and the short life of ultrathin smartphones appeared first on Liliputing.
The acquired firm was working on a tool to control macOS directly with AI.
OpenAI has acquired Software Applications Incorporated (SAI), perhaps best known for the core team that produced what became Shortcuts on Apple platforms. More recently, the team has been working on Sky, a context-aware AI interface layer on top of macOS. The financial terms of the acquisition have not been publicly disclosed.
“AI progress isn’t only about advancing intelligence—it’s about unlocking it through interfaces that understand context, adapt to your intent, and work seamlessly,” an OpenAI rep wrote in the company’s blog post about the acquisition. The post goes on to specify that OpenAI plans to “bring Sky’s deep macOS integration and product craft into ChatGPT, and all members of the team will join OpenAI.”
That includes SAI co-founders Ari Weinstein (CEO), Conrad Kramer (CTO), and Kim Beverett (Product Lead)—all of whom worked together for several years at Apple after Apple acquired Weinstein and Kramer’s previous company, which produced an automation tool called Workflows, to integrate Shortcuts across Apple’s software platforms.
Scraper accused of stealing Reddit content “shocked” by lawsuit.
In a lawsuit filed on Wednesday, Reddit accused an AI search engine, Perplexity, of conspiring with several companies to illegally scrape Reddit content from Google search results, allegedly dodging anti-scraping methods that require substantial investments from both Google and Reddit.
Reddit alleged that Perplexity feeds off Reddit and Google, claiming to be “the world’s first answer engine” but really doing “nothing groundbreaking.”
“Its answer engine simply uses a different company’s” large language model “to parse through a massive number of Google search results to see if it can answer a user’s question based on those results,” the lawsuit said. “But Perplexity can only run its ‘answer engine’ by wrongfully accessing and scraping Reddit content appearing in Google’s own search results from Google’s own search engine.”
Models trained on short, popular, and/or “superficial” tweets perform worse on benchmarks.
On the surface, it seems obvious that training an LLM with “high quality” data will lead to better performance than feeding it any old “low quality” junk you can find. Now, a group of researchers is attempting to quantify just how much this kind of low quality data can cause an LLM to experience effects akin to human “brain rot.”
For a pre-print paper published this month, the researchers from Texas A&M, the University of Texas, and Purdue University drew inspiration from existing research showing how humans who consume “large volumes of trivial and unchallenging online content” can develop problems with attention, memory, and social cognition. That led them to what they’re calling the “LLM brain rot hypothesis,” summed up as the idea that “continual pre-training on junk web text induces lasting cognitive decline in LLMs.”
Figuring out what counts as “junk web text” and what counts as “quality content” is far from a simple or fully objective process, of course. But the researchers used a few different metrics to tease a “junk dataset” and “control dataset” from HuggingFace’s corpus of 100 million tweets.
From scanning emails to building fansites, Atlas can ably automate some web-based tasks.
On Tuesday, OpenAI announced Atlas, a new web browser with ChatGPT integration, to let you “chat with a page,” as the company puts it. But Atlas also goes beyond the usual LLM back-and-forth with Agent Mode, a “preview mode” feature the company says can “get work done for you” by clicking, scrolling, and reading through various tabs.
“Agentic” AI is far from new, of course; OpenAI itself rolled out a preview of the web browsing Operator agent in January and introduced the more generalized “ChatGPT agent” in July. Still, prominently featuring this capability in a major product release like this—even in “preview mode”—signals a clear push to get this kind of system in front of end users.
I wanted to put Atlas’ Agent Mode through its paces to see if it could really save me time in doing the kinds of tedious online tasks I plod through every day. In each case, I’ll outline a web-based problem, lay out the Agent Mode prompt I devised to try to solve it, and describe the results. My final evaluation will rank each task on a 10-point scale, with 10 being “did exactly what I wanted with no problems” and one being “complete failure.”
Biased, eager-to-please models threaten health research replicability and trust.
Once upon a time, two villagers visited the fabled Mullah Nasreddin. They hoped that the Sufi philosopher, famed for his acerbic wisdom, could mediate a dispute that had driven a wedge between them. Nasreddin listened patiently to the first villager’s version of the story and, upon its conclusion, exclaimed, “You are absolutely right!” The second villager then presented his case. After hearing him out, Nasreddin again responded, “You are absolutely right!” An observant bystander, confused by Nasreddin’s proclamations, interjected, “But Mullah, they can’t both be right.” Nasreddin paused, regarding the bystander for a moment before replying, “You are absolutely right, too!”
In late May, the White House’s first “Make America Healthy Again” (MAHA) report was criticized for citing multiple research studies that did not exist. Fabricated citations like these are common in the outputs of generative artificial intelligence based on large language models, or LLMs. LLMs have presented plausible-sounding sources, catchy titles, or even false data to craft their conclusions. Here, the White House pushed back on the journalists who first broke the story before admitting to “minor citation errors.”
It is ironic that fake citations were used to support a principal recommendation of the MAHA report: addressing the health research sector’s “replication crisis,” wherein scientists’ findings often cannot be reproduced by other independent teams.
MacOS version launches today, includes Agent Mode preview to “use the Internet for you.”
Back in 2008, Google launched the Chrome browser to help better integrate its industry-leading search engine into the web-browsing experience. Today, OpenAI announced the Atlas browser that it hopes will do something similar for its ChatGPT Large Language Model, answering the question “What if I could chat with a browser?” as the OpenAI team put it.
OpenAI Founder and CEO Sam Altman said in a livestreamed announcement that Atlas will let users “chat with a page,” helping ChatGPT become a core way that users interact with the place where “a ton of work and life happens” online. “The way that we hope people will use the Internet in the future… is that the chat experience and a web browser can be a great analogue,” he said.
The new browser is available for download now on MacOS, and Altman promised Windows and mobile versions would be rolled out “as quick as we can.”
Likeness detection will flag possible AI fakes, but Google doesn’t guarantee removal.
AI content has proliferated across the Internet over the past few years, but those early confabulations with mutated hands have evolved into synthetic images and videos that can be hard to differentiate from reality. Having helped to create this problem, Google has some responsibility to keep AI video in check on YouTube. To that end, the company has started rolling out its promised likeness detection system for creators.
Google’s powerful and freely available AI models have helped fuel the rise of AI content, some of which is aimed at spreading misinformation and harassing individuals. Creators and influencers fear their brands could be tainted by a flood of AI videos that show them saying and doing things that never happened—even lawmakers are fretting about this. Google has placed a large bet on the value of AI content, so banning AI from YouTube, as many want, simply isn’t happening.
Earlier this year, YouTube promised tools that would flag face-stealing AI content on the platform. The likeness detection tool, which is similar to the site’s copyright detection system, has now expanded beyond the initial small group of testers. YouTube says the first batch of eligible creators have been notified they can use likeness detection, but interested parties will need to hand Google even more personal information to get protection from AI fakes.
Sandboxing lessens hassle, but fire-and-forget agentic tools still pose risks.
Anthropic has added web and mobile interfaces for Claude Code, its immensely popular command-line interface (CLI) agentic AI coding tool.
The web interface appears to be well-baked at launch, but the mobile version is limited to iOS and is in an earlier stage of development.
The web version of Claude Code can be given access to a GitHub repository. Once that’s done, developers can give it general marching orders like “add real-time inventory tracking to the dashboard.” As with the CLI version, it gets to work, with updates along the way approximating where it’s at and what it’s doing. The web interface supports the recently implemented Claude Code capability to take suggestions or requested changes while it’s in the middle of working on a task. (Previously, if you saw it doing something wrong or missing something, you often had to cancel and start over.)
Doctors share top concerns of AI surrogates aiding life-or-death decisions.
For more than a decade, researchers have wondered whether artificial intelligence could help predict what incapacitated patients might want when doctors must make life-or-death decisions on their behalf.
It remains one of the most high-stakes questions in health care AI today. But as AI improves, some experts increasingly see it as inevitable that digital “clones” of patients could one day aid family members, doctors, and ethics boards in making end-of-life decisions that are aligned with a patient’s values and goals.
Ars spoke with experts conducting or closely monitoring this research who confirmed that no hospital has yet deployed so-called “AI surrogates.” But AI researcher Muhammad Aurangzeb Ahmad is aiming to change that, taking the first steps toward piloting AI surrogates at a US medical facility.