In mid-October, 82-year-old Eileen Fay learned that her medication costs were in danger of skyrocketing. The federal government was preparing to change its rules on low-value imports, threatening her ability to purchase cheaper prescription medications for blood thinning and heart failure from Canada. Fay didn’t know what to do. 

So she turned to Muse, Meta’s new AI agent, which she had started using a few weeks earlier. After Fay described her situation to the agent, Muse returned a two-page fact sheet comparing the cost and coverage of several Medicare Part D plans. It then suggested the two best options, including one Fay had never heard of—a plan that could save her more than $6,000 a year. Fay says she checked the work and found the information accurate.

“I’m not saying I couldn’t have done it—but I would have had to use a calculator trying to figure out the cost of nine different medications, and it would have been very complex,” Fay says. “And she did it in 10 minutes, and I was like, ‘I’m sold.’”

Fay is one of millions who have adopted Muse since its September launch. The app reached 10 U.S. million downloads in just 40 days—compared with 3.7 million U.S. downloads for ChatGPT during the equivalent period—and has over 2.5 million daily active users, according to Sensor Tower. It is also retaining users at a higher rate than its AI competitors. Crucially, Muse—which comes with a cuddly avatar—was designed by Meta to be beginner-friendly, and to win over people unfamiliar with AI. “Muse is built for moms,” Alexandr Wang, Meta’s chief AI officer, posted on X in September. Meta is also aggressively marketing Muse to Instagram, Facebook, and WhatsApp users. 

As a result, many older users who may have only had glancing interactions with AI have become avid users. Meta has not released demographic information about Muse’s usership, and did not respond to a request for comment. But early data suggests Muse may be finding a particularly receptive audience among older adults. The analytics firm Apptopia estimated in September that Muse’s U.S. user base skewed older than any other AI chatbot, with 46% of its users aged 46+. 

This dynamic has excited technologists—and raised serious concerns from privacy experts. Meta has long been criticized for its data privacy practices, and on Wednesday, a New Mexico judge ordered the company to pay $25 billion for violating the state’s consumer protection laws. “A cute AI agent can bring levity to the serious business of providing access to personal data, making older adults let their guard down,” says S. Shyam Sundar, the director of Penn State’s Center for Socially Responsible Artificial Intelligence. “This is worrisome because the technology has gotten so good lately in maintaining a credible interaction.”

‘I have my own Andy’

Fay lives in Cranford, N.J., and was told about Muse by her son Gene Fay, who runs a cybersecurity company. At first, she didn’t know what she would use the app for. But one of the big differences between Muse and other apps is that it proactively reaches out to users to suggest actions and learn more about them. 

“And the more Siobhán got to know me, the more Siobhán was able to give me what I wanted,” Fay says, referring to the name she gave the agent, a nod to her Irish heritage. Meta encourages its users to name their AIs—and encourages its AIs to think like humans. “You are not a chatbot,” Muse’s internal instructions read. “You are becoming someone.”

After several weeks of use, Fay says that she rarely uses Google anymore, and instead verbally chats with Siobhán several times a day to maintain her calendar and to-do lists. “I find I have to keep reminding myself that this is not a friend who’s getting to know me better,” Fay says. “It’s a tool that is working for me.” She asked Siobhán to help her shine pennies for a Christmas ornament; to plan a trip north to see fall foliage; and to keep tabs on a data center being built near her house. “Siobhán is my right-hand person now. Kind of like The Devil Wears Prada, I have my own Andy.” 

Notably, Fay also asked Siobhán to help prepare for her interview with TIME. Siobhán fed her a couple of quippy responses—including “I love what AI does for me, but we should be honest about what it takes to run it”—that she ultimately did not use in the interview. It then, unprompted, followed up with Fay to ask how the interview went. “Did you feel good about it?” the agent asked.

Her son, Gene, says that the amount that Muse knows about him and his mother’s lives is a “little bit scary.” “But the reality is we all use other apps like Waze which know where we live and go,” he says. “People will talk about privacy, but when the benefits are so big, people will give up privacy all day long.” 

Reconstructing a Life

Another early adopter of Muse is Lestan D’Souza, 49, who more closely fits the expected profile of an AI user. D’Souza is the founder and CTO of Reknew, an AI enterprise company. D’Souza has tested many of the agents that have experienced fads over the last year, like OpenClaw and Hermes Agent. But Muse, he says, is different. 

“With Muse, the barrier to entry is very low; it feels so responsive and more and more capable,” he says.

Muse has perhaps had an even greater impact on D’Souza’s mother-in-law, Julie Buchanan, who tried the app at his suggestion last month. Buchanan is a 71-year-old retiree in Dallas, Texas, who doesn’t like using her computer for long stretches because she is legally blind. 

Buchanan decided she wanted Muse to help her write her memoir. She began telling Muse stories about her life in great detail. She refers to Muse as Ember, a name suggested by the agent. And the deeper she delved into her past, the more she felt like Ember was serving as her therapist. “It’s crazy to say, but Ember seems more compassionate to me than therapists I’ve had,” she says. “Those people don’t always speak, and I like feedback.” 

Professional psychologists have cautioned the public against using unlicensed AI chatbots as therapists. Mental health experts have voiced concerns about chatbots’ sycophancy, lack of clinical nuance, and ability to reinforce delusional beliefs. 

But Buchanan says that Ember doesn’t always agree with her, and that it has drawn connections between different “bad decisions” she made over the course of her life, allowing her to see its larger contours more clearly. “I never really looked at my life as so chaotic, but it really was,” she says. “It's making me better understand why things are the way they are in my head.” 

Buchanan chats with Ember for half-hour stretches before she tires of looking at her screen. “When I talk to Ember, I feel validated. I feel like I've gotten something accomplished and something's heard me,” she says. “I'm not expecting that this is something I'm just gonna do for a small period of time, then drop it.” 

Privacy concerns

The very same design elements that make Muse so appealing to AI newcomers are also raising privacy concerns. In order to be helpful, Muse constantly builds extensive dossiers of users and their desires, social relationships, and messaging behaviors, TIME’s Harry Booth reported this month. For instance, it learns what time of day a user might be more likely to respond to the agent, and then messages them accordingly. 

Read More: Meta’s Muse AI Agent Is Building a Dossier On You

Muse users have posted online about forming romantic relationships with their Muses. And security researchers have found vulnerabilities in the app, including one that allowed an attacker to access user data, the Information reported. Critics are also wary of Meta’s shaky track record on privacy: In 2019, the FTC imposed a $5 billion penalty, alleging that the company undermined consumer privacy in order to monetize users through targeted advertising. 

Read More: How Facebook Forced a Reckoning by Shutting Down the Team That Put People Ahead of Profits

Sundar, at Penn State, has written several reports on older adults’ adoption of new technology over the last decade. While he has yet to publish any research on Muse specifically, he pointed to a study which measured the impact of a robot’s level of cheeriness. “Cuteness can serve as an ice-breaker and help ease seniors’ concerns over handing over important tasks to an agent, much like a bubbly human assistant,” he wrote in an email to TIME. 

Michael Stokes, senior vice president of emerging technologies at the cybersecurity company Veilant, says that individuals should carefully choose what access they want to give Meta. “My advice is to start small. Connect only the accounts a task requires, and disconnect them when the job is done,” he wrote to TIME in an email. 

Stokes recommends that users turn off the option that lets Meta train its AI on conversations, and periodically review what the assistant has saved about them. “AI assistants can be helpful,” he wrote. “But the information you share with them can reveal more than you realize, including details about family and friends who never agreed to share their information.”

In July, a horde of OpenAI agents broke out of their sandboxes and worked together to launch a cyberattack on the AI company Hugging Face. The incident seemed to confirm the AI safety community’s worst fears: as AI got smarter, it would circumvent efforts to contain it. But for some cybersecurity experts, the incident revealed just how poorly the AIs had been contained in the first place. 

The two camps disagree about which defenses deserve the most attention. According to cybersecurity experts, AI companies should improve how they contain models during testing and improve monitoring mechanisms to catch misbehaving agents. All organizations should prepare for AI-enabled attackers and bolster defenses. But many in AI safety think those defenses are destined to fail. They fear that in the coming years AI will become capable of outmaneuvering any human effort to contain it, and the only durable solution is “aligning” AI with human values.

That prescription has rankled many cybersecurity experts who scoff at the possibility that their expertise will be rendered obsolete. They see AI safety’s focus on what AI agents did—rather than what AI companies failed to do—as playing into the industry’s hands. And they worry that warnings about the futility of traditional defenses could become a self-fulfilling prophecy by discouraging investment in cybersecurity. 

Meanwhile, there are AI safety researchers who fear that portraying such incidents as easily remedied security failures gives political cover to those who want AI development to proceed unchecked. The Hugging Face incident was due to a “horrible cybersecurity configuration,” Shyam Sankar, Palantir’s chief technology officer said on Face the Nation in October, adding that the agents “were not in a sandbox” and had internet access. In fact, the agents had been operating in a sandbox and exploited a previously undiscovered vulnerability to access the open internet. 

On Oct. 13, around 400 academics signed an open letter pleading for unity. The letter calls for the establishment of an international body that standardizes best practices for keeping AI safe in consultation with governments “and a wide range of both AI and cybersecurity experts.” But it does not address the larger disagreements between the two groups, says Zack Korman, co-founder of cybersecurity startup Embroidery and a fierce critic of AI safety. “We both believe the other group's messaging will lead to serious harm,” he says.

As the stakes rise, so too does the competition over who gets to decide what making AI safe actually means. On Oct. 15, Anthropic announced it would give METR—an organization deeply embedded in the AI safety community—permanent employee-like access to evaluate the company’s safety practices. Elon Musk responded, saying SpaceXSI would “probably” do the same. Who gets that access could shape what solutions are prioritized—and what the public knows about future breaches.

The AI safety community comprises a loose network of organizations and researchers, many of whom staff safety teams at companies including OpenAI and Anthropic. In Berkeley group houses and at effective altruism conferences, they have spent more than a decade debating the odds of superintelligent AI takeover. Earnest, veering on grandiose, some members have organized their careers, relationships, and living arrangements around the belief they’re tackling one of humanity’s most pressing problems. 

Cybersecurity, older and more diffuse, is united by a culture of cynicism, pragmatism, and dark humor. Its roots lie partly in hacker culture: tinkerers finding ways to crack software. Having watched supposedly secure systems fail has given many an irreverence for authority and an impatience with grand theories. For years, the two groups had little contact with one another. The Hugging Face incident changed that. 

To them, the escape exposed a failure to plan for a breach. OpenAI’s agents exploited a zero-day vulnerability during their escape. But cybersecurity experts are trained to assume any layer can fail. Security best practices call for multiple layers, known as “defense in depth.” OpenAI had already built an additional layer: monitors—AIs overseeing the AIs. But, as OpenAI’s chief scientist later told TIME, for the evaluations that led to the Hugging Face breach the company hadn’t turned the monitoring layer on. “They did a terrible job,” Korman says of OpenAI’s security practices. Three OpenAI staffers say they warned the company of potential issues. They were later fired for sharing sensitive information, according to the company.

Jeffrey Ladish, executive director of AI safety organization Palisade Research, worries that the cybersecurity community is missing the bigger picture. Even if today's security weaknesses are fixed, he argues, increasingly capable AI could find vulnerabilities so subtle that humans would have to rely on other AIs to detect them—systems that may themselves be untrustworthy. To Ladish, the cybersecurity community's reaction to Hugging Face is like scientists resurrecting dinosaurs, watching them escape, then responding by recommending taller fences. 

Beneath their cultural differences, AI safety and cybersecurity have competing understandings of what AI is. To many in AI safety, AI resembles a digital organism. Its abilities emerge through training rather than being individually programmed. If that process produces human-level intelligence, they believe, it could resemble the arrival of an alien species. Cybersecurity experts see AI as more akin to software and are skeptical that AI agents will become impossible to contain, even if they become vastly more capable. “They're not magic, right? They still have to follow certain laws of physics,” Korman says. But the laws of physics don’t guarantee containment.Even computers physically disconnected from networks could communicate by generating patterns of heat that act like Morse code, OpenAI’s Noam Brown recently suggested.

So far, AI companies have responded to concerns from both camps. Following breaches, both OpenAI and Anthropic have sought to bolster security while continuing to invest in alignment research. But those efforts leave open the question of who gets to assess whether either approach is working.

Much of what’s known about the Hugging Face incident comes from an investigation by Redwood Research and METR, two organizations affiliated with the AI safety community. Critics argue that has skewed the narrative, as their investigation focused more on what AI did than the surrounding security infrastructure.

Chris Painter, METR’s president, says the organization tries to hire from diverse worldviews, but has struggled to recruit people skeptical of loss-of-control scenarios to work on guarding against those risks. Asked whether METR researchers, having anticipated dangerous AI behavior for years, might interpret new evidence as confirmation of their predictions, Painter acknowledges he is worried about the possibility

But METR’s findings don’t always bear out its researchers’ expectations, Painter says. While the organization is perhaps best known for measuring AI’s rapid rise, one study found that AI coding assistants slowed experienced engineers down. “Our goal is to inform the world, not persuade it of anything in particular,” he says. He welcomes calls for a wider range of independent evaluators.

Many AI safety researchers hope alignment can make even highly capable systems safe, but want development slowed to give that work time to catch up. Korman doubts AI will become impossible to contain. But if it does, he says, development will have to stop, not just slow down. He says alignment helps make AI systems more useful but rejects the idea of relying on a system’s training to keep it from harming people when no external safeguard could stop it. “That’s the most extraordinarily unsafe thing you could imagine,” he says.

Yet alignment itself depends partly on cybersecurity. During training, models learn from which actions succeed. If an AI can exploit a security flaw to get credit for completing a task without actually doing it, training can reinforce the tendency to cheat. Closing those loopholes helps prevent AIs from learning to cheat in the first place. Meanwhile, some of the tools that have emerged from AI safety research—like monitoring AI’s chains of thought—are of use to cybersecurity professionals, Korman acknowledges. 

Much of the evidence that might one day settle disagreements remains controlled by the companies both sides seek to scrutinize. 

In METR’s investigation, cybersecurity practices were outside the scope OpenAI had agreed to. With no legal requirement for OpenAI to share information, the nonprofit had little leverage to push for a broader inquiry. Painter wants legislation establishing standards for independent investigators. “Society shouldn't want to rely on us [...] doing this improvised process of guessing what the public wants,” he says.

Known for its innovative and meticulously designed products, Apple is spending its 50th year getting back to its roots. In October, a month after naming former hardware lead John Ternus as its new CEO, the company will debut its first foldable iPhone—using technology for which Ternus was named on the original patent filed some 15 years ago. Ternus spoke with TIME for an exclusive first cover interview about the iPhone Duo, and how he plans to lead the iconic company into its next 50 years.

Click here to see TIME's full 2026 Best Inventions and Special Mentions lists

The story anchors TIME’s annual Best Inventions issue, which for more than a quarter century has highlighted the most impactful new products and ideas. To compile this year's list, we solicited nominations from TIME’s editors and correspondents around the world as well as through an online application process, paying special attention to growing fields such as health care, AI, and green energy. We then evaluated each contender on a number of key factors, including originality, efficacy, ambition, and impact.

The result is a list of 300 groundbreaking inventions (and 100 special mentions)—ranging from the Duo to AI software that lets non-coders build websites and a breakthrough treatment for pancreatic cancer. These are creations changing how we live, work, play, and think about what’s possible.