How the Pope's Magnifica Humanitas offers a template for individuals to meet the AI moment Despite a lack of regulation, we still have the ability to steer artificial intelligence in ways that can benefit our common humanity. Pope Leo XIV's new encyclical on artificial intelligence includes a statement that warrants serious attention from technologists and policymakers: "Technology is never neutral." As the pope says, the choice before us--the choice AI presents--is one between the Tower of Babel and the rebuilding of our common humanity. In the biblical story of the Tower of Babel, humans sought to build a massive structure that reached all the way to Heaven, only to have their project thwarted when God made those involved unable to understand one another. It was a pursuit fixated on relentless growth, divorced from any concern about God's commandments or the human cost. It resulted in failure and atomization.

Watch a subscriber-only discussion exploring how AI might enter the physical world. AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion. Watch a conversation with editor in chief Mat Honan, senior AI editor Will Douglas Heaven, and AI reporter Grace Huckins exploring how AI might enter the physical world. A woman's uterus has been kept alive outside the body for the first time Jessica Hamzelou Want to understand the current state of AI? Check out these charts. Want to understand the current state of AI? Check out these charts.

Building customer trust with on-brand content production has become a strategic imperative. Storytelling is core to humanity's DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans' innovation of natural pigments and charcoals for cave paintings to literal representation by the camera. The landscape of storytelling continues to shift under our feet. Social and streaming platforms have multiplied, audiences have fragmented, and our demand for fresh, unique media is insatiable. A recent McKinsey podcast cites that we are watching upwards of 12 hours of video content daily, often on multiple devices and multiple platforms.

Anthropic's Code with Claude showed off coding's future--whether you like it or not As tools like Claude Code get better, more and more developers are happy to hand off coding tasks to them. The way software gets built has changed for good. The vibes were strong at Code with Claude, Anthropic's two-day event for software developers in London that kicked off on May 19, the same day as Google's I/O in Palo Alto. "Who here has shipped a pull request in the last week that was completely written by Claude?" Jeremy Hadfield, an engineer at Anthropic, asked from the main stage. Almost half the people in the packed room--many sitting with laptops on their knees, coding or prompting as they watched the talks--raised their hands. Pull requests are fixes or updates to existing software that are submitted for review before they go live.

Why sovereignty over data and models is becoming a defining factor in enterprise AI success,as well as a prerequisite for forging safe agentic systems. When generative AI first moved from research labs into real-world business applications, enterprises made a tacit bargain: "Capability now, control later." Feed your proprietary data into third-party AI models, and you will get powerful results. But your data passes through systems you do not own, under governance you do not set. The protections you rely on are only as durable as the provider's next policy update. Now, with generative AI established in everyday business operations and sophisticated new agentic AI systems advancing every day, companies are reevaluating the terms of that deal.

The success of agentic AI in financial services depends not just on smarter models, but on an authoritative context data store--one that is accessible, reliable, and governed at scale. Financial services companies have unique needs when it comes to business AI. They operate in one of the most highly regulated sectors while responding to external events that are updated by the second. As a result, the success of agentic AI in financial services depends less on the sophistication of the system and more on the quality, security, and accessibility of the data it relies on. "It all starts with the data," says Steve Mayzak, global managing director of Search AI at Elastic. Agentic AI--systems that can independently plan and take actions to complete tasks, rather than simply generate responses--holds enormous potential for financial services due to its ability to incorporate real-time data and optimize complex workflows.

Join a subscriber-only discussion live on Thursday, May 21. A woman's uterus has been kept alive outside the body for the first time Jessica Hamzelou Want to understand the current state of AI? Check out these charts. A woman's uterus has been kept alive outside the body for the first time The team behind the feat plan to study uterine disorders and the early stages of pregnancy--and potentially grow a human fetus. Want to understand the current state of AI? Check out these charts. According to Stanford's 2026 AI Index, AI is sprinting, and we're struggling to keep up. The ultimate plan to live forever is a brand new body.

Daron Acemoglu is more cautious than most about predictions of a jobs apocalypse. A few months before he was awarded the Nobel Prize in economics in 2024, Daron Acemoglu published a paper that earned him few fans in Silicon Valley. Contrary to what Big Tech CEOs had been promising--an overhaul of all white-collar work--Acemoglu estimated that AI would give only a small boost to US productivity and would not obviate the need for human work. It's okay at automating certain tasks, he wrote, but some jobs will be perfectly fine. Two years later, Acemoglu's measured take has not caught on. Chatter about an AI jobs apocalypse pops up everywhere from Senator Bernie Sanders's rallies to conversations I overhear in line at the grocery store.

Successful AI implementation requires shifts in workplace culture as well as use cases that can scale across the enterprise. In finance departments that have long been defined by precision and control, AI has arrived less as a neatly managed upgrade than as a quiet insurgency. Employees are already using it while leadership races to impose structure, governance, and strategy after the fact. The result is a paradox: one of the most tightly regulated functions in the enterprise is now among the most experimentally transformed. What's emerging is a layered shift in how work gets done. From variance commentary and fraud detection to contract review and close narrative drafting, AI is embedding itself across workflows, particularly where unstructured data once slowed down everything.

Cybersecurity was already under strain before AI entered the stack. Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore. This session from MIT Technology Review's EmTech AI conference explores why security must be rethought with AI at its core, not layered on after the fact. A prolific inventor and internationally recognized authority in knowledge representation, inference calculus, and AI planning, Tarique has spent his career applying autonomously collaborative AI to solve complex, ultra-high-scale challenges across cybersecurity, data security, and compliance -- with deep expertise spanning Data Classification, DLP, and DSPM industries. His groundbreaking innovations and multiple USPTO patents have earned him global recognition, including frequent invitations to deliver keynote addresses at prestigious international security conferences and forums. At GCCybersecurity, Tarique architected the core AI algorithms powering the company's 4th and 5th generation fully autonomous data leak protection and exfiltration platform -- among the most advanced platform of its kind.