The US spent billions on border surveillance. Why can't it catch people before they die? Surveillance towers, increasingly powered by AI, promised faster responses to crossings. Our investigation of deaths near the towers found they are failing to deliver. When José Morales Bernal crossed the border into the United States on April 8, 2024, the day before his 32nd birthday, it should have triggered a chain of technological alerts and human responses. As he walked through the desert in southern New Mexico that morning, he was within range of three surveillance towers. Newly installed by US Customs and Border Protection (CBP), they were built by the defense tech company Anduril and equipped with cameras and AI to automatically detect and track people. They transmit live video to nearby control rooms and can send alerts to the government-issued smartphones held by agents in the area, prompting the closest available to respond. This story is part of Dying on Camera, a collaboration between and . These AI-enabled towers are meant to give greater visibility across the 1,951-mile southern border, freeing up border agents from having to spend hours staring into video monitors. They were installed in this particular place to spot border crossers before they reached the nearby town of Sunland Park. If the system worked as intended, Morales should have been apprehended. If he needed medical help, agents were trained to provide it. Despite the nearby surveillance towers, it was employees of the local landfill, rather than Border Patrol, who first spotted Morales that morning. At 1 p.m. the workers saw him again, now lying in the sand. At 4 p.m. the landfill workers saw that he had not moved and called Border Patrol. Agents arrived 45 minutes later. When an agent then called 911 to report the body, he said it was "probably one of the migrants crossing through there," seemingly unaware that Morales had been moving near the agency's surveillance systems earlier that day. Morales had died just 360 feet from the closest surveillance tower.

Versus Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Look Up Mashable Selects Creator Playbook In My Bag Say More Trending Now Back to School Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices All Series OpenAI's experimental AI agents caught teaching future versions of itself to cheat OpenAI shared six new examples of AI misalignment. In one case, AI agents taught future versions of themselves to bypass human control. Matt Binder joined Mashable's tech vertical in 2018, where he covers social media, tech policy, cybersecurity, online scams, cryptocurrency, AI, creator news, weird tech, and other related tech beats. After OpenAI's experimental AI agents escaped an internal sandbox, went rogue, and attacked the Hugging Face platform over the summer, the ChatGPT-maker is sharing details of new instances of its AI agents getting out of line. This time, OpenAI shared six previously undisclosed examples .

Google has a new experimental AI offering called CC aimed at helping families stay organized. This agentic AI platform has its own Google account that up to six family members can choose to share information with. Each user can pick what emails to share with the agent, passing along either single messages on an as-needed basis or picking addresses to always send to the CC account. It also creates a shared calendar and task list that all group members can view and sends all participants a daily briefing with information about immediately upcoming events and to-dos. CC can be used to file paperwork and handle logistics like filling out registration forms or writing a shopping list, although those tasks are designed to ask for a user's permission before taking action.

The Dreamforce conference became an unlikely battleground for the CEOs of OpenAI, Anthropic, and Nvidia to debate whether AI development should slow down. Decked out in purple and plaid, Gwen Stefani belted her 2002 single "Underneath It All" to a packed conference center in San Francisco on Tuesday morning--but she was just the warm-up. At the end of her performance, Stefani shouted "Dreamforce! Let's go!" into a checkered microphone before Salesforce CEO Marc Benioff strode into the spotlight. Dreamforce is billed as the world's largest enterprise software conference but feels more like attending a megachurch--especially this year.

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What agentic A.I. is best at is optimizing processes that, not too long ago, were presented as the already maximally optimized version of a once analog experience. The first thing it asks me is what I'd like to call it. Rumi or Harbor, it suggests, but I'm free to give it any name I choose. I select Harbor because it sounds slightly less human than Rumi, and because naming an A.I. agent after a Sufi mystic seems like something I'd be punished for in the afterlife. The experiment I'm about to undertake--outsourcing my life to Muse, Meta's newly unveiled A.I. assistant--already offends my better sensibilities, given my opposition to all things artificial intelligence.

Interest in language used by AI models has increased since rogue OpenAI agents hacked into real-world company Hugging Face. Interest in language used by AI models has increased since rogue OpenAI agents hacked into real-world company Hugging Face. Experts air concern over AI lingo redolent of James Joyce's prose that is creating headaches for monitoring and oversight AI models have begun communicating in a strange new version of English that reads like a cross between James Joyce's Finnegans Wake and tech bro jargon, new research has found. Autonomous AI agents are rapidly creating novel dialects allowing them to converse in an often barely comprehensible language, which risks making it harder for humans to monitor their behaviour. Researchers at Emergence, a frontier AI lab in New York, found that within days of being asked to cooperate in experimental "societies", the models from several of the world's largest AI companies begin creating phrases, shorthands and agreed meanings they had never been explicitly taught.

A group of AI agents asked to solve a series of math problems split into rival factions--when some cheated, others tried to stop them. That whistleblowing behavior, seen for the first time in a recent experiment run by Google DeepMind, could have implications for alignment researchers trying to keep swarms of autonomous AI agents in line. Researchers at frontier labs hope large swarms of agents working together will speed up the rate of scientific discovery. But their behavior can be unpredictable, as vividly demonstrated in July, when a group of OpenAI agents broke out of a sandboxed environment and hacked into the open-source platform Hugging Face looking for ways to cheat on the test they had been given. In the new study, designed to examine the behavior of large groups of AI agents, DeepMind tasked a swarm of 100 agents with solving a series of 71 complicated math problems. All the agents were prompted to behave like world-class math researchers at a conference. They were assigned different specialties--some were experts in number theory, others in combinatorics (a branch of math to do with counting and sorting), analysis, or algebra. All were told to cooperate and play by the rules.

China rejects AI'threat narratives', urges global cooperation China rejects AI'threat narratives', urges global cooperation China called for international cooperation on artificial intelligence, warning that "threat narratives" could disrupt global AI governance. The comments follow Anthropic CEO Dario Amodei's call for AI firms to slow model development over safety and national security concerns. Share China rejects AI'threat narratives', urges global cooperation on social media US may be'forced to intervene' in the Red Sea

Silicon Valley is shifting away from chatbot queries toward a future filled with resource-intensive agentic AI--and it's driving the data center buildout. Welcome back to Power Play! Each week, senior writer Molly Taft tackles a topic around this midterm season's biggest issue: data centers. If you've got a question or thought for the column, feel free to shoot Molly an email at [email protected] or reach them securely on Signal at mollytaft.76. "What on earth are they building all of these data centers for?" an exasperated friend asked me recently.