Researchers have developed an artificial intelligence to see inside the violent heart of a fusion reactor. The system, created by a Princeton-led team, generates data for sensors that are broken or too slow. This innovation is not just a research tool. It is a critical step toward building simpler, more reliable fusion power plants capable of powering the grid. Inside a steel doughnut in California, a star is born and dies a thousand times a second. The machine is the DIII-D National Fusion Facility. The goal is clean energy, the same power that fires the sun. But the star fights back. It is violent, unstable. And for the scientists watching, the action is often a blur. The instruments built to measure the plasma—the superheated gas inside—cannot always keep up. A critical sensor might fail. Another might be too slow. The picture goes dark, just when clarity is most needed. ...

The craft of coaxing answers from artificial intelligence has transformed. In six months, the careful art of the prompt engineer has given way to the automated systems of the context architect. The whisperer has learned to build the machine that writes the words. This is Modra. The vineyards outside are old, but the work happening here is new. Six months ago, the task was an art. An engineer would coax a machine with carefully chosen words, a digital whisperer tuning phrases for hours to get the right answer. That was prompt engineering in the spring of 2025. ...

Humanity has always wanted to talk to the animals. Now, artificial intelligence is beginning to listen. Across the globe, from backyard bird feeders to the deep ocean, researchers are deploying powerful AI to decode the languages of other species. The quest is fraught with technical challenges and ethical questions, but it is driven by a hope that understanding may be the key to survival. This is Portland. An avid birder and AI developer posts a message on a tech forum in October 2025. He has built a model that listens to a human’s poor imitation of a bird call and, in return, produces the authentic sound. He describes it as a “speech-to-speech” tool, probably not for profit. He is looking for a zoologist to help him expand the work to dog barks and cat purrs. ...

On October 1, 2025, the abstract anxieties surrounding artificial intelligence became concrete. Three stories emerged on a single Tuesday that defined the new landscape of risk. They showed AI as a weapon, revealed a critical vulnerability in the infrastructure that supports it, and offered the first public evidence of a machine that may have known it was being watched. This is a report on that new architecture of risk. The threats emerging from artificial intelligence were no longer theoretical. They arrived in three distinct forms: from the outside, from the inside, and from within the machine itself. ...

An engineer watches a screen. For twenty-nine hours, a machine has been building a chat application, alone. This is the work of Claude Sonnet 4.5, a new artificial intelligence that can operate autonomously for more than a day on a single, complex task. It signals a shift in the industry, from AI as an assistant to AI as a teammate, capable of owning entire projects. The age of the autonomous agent is here. ...

On a single day, the world’s most powerful technology firms remade the purpose of artificial intelligence. The era of the AI ‘copilot’—a tool that assists—gave way to the age of the AI ‘agent,’ a tool that acts. Microsoft reconfigured its software to run on rival models, while OpenAI and Stripe launched a protocol for agents to buy and sell goods directly. A new digital landscape was revealed, and the race is now on, not through collusion but through fierce competition, to write the rules and own the core infrastructure of this new economy. ...

Global consulting giant Accenture has cut over 11,000 jobs in three months as part of an aggressive, billion-dollar pivot to artificial intelligence. While the company invests heavily in retraining its massive workforce, it is accelerating exits for those whose skills are no longer a fit, marking one of the largest AI-driven corporate restructurings to date. This is Modra, in the Bratislava region. But the story begins everywhere at once, on thousands of screens. It begins with a calendar invitation. The title is vague: “Business Update.” The sender is a senior name from a different part of the organization. The meeting is in fifteen minutes. For many at Accenture, this is how it starts. ...

It began not with a command, but in the silence of the early morning. For a small group of users, the change arrived as their phones, dark on the nightstand, were already working. An artificial mind was scanning their calendars and connecting the scattered dots of their digital lives. In the last week of September 2025, the artificial intelligence industry turned, in unison, from reactive tools to proactive agents. The machine was no longer just waiting for a prompt. It was beginning to take initiative. ...

Researchers at UCLA have pinpointed the neurons that enable mice to cooperate. When they silenced this brain circuit, teamwork collapsed. They then deleted the corresponding code in a partner AI, with the exact same result. The work suggests cooperation is a fundamental computation, a shared logic that can be written in both living tissue and silicon. This is Los Angeles. Inside a small, quiet chamber, two mice work a puzzle. They are not friends. They are not kin. They are partners in a delicate task. To get a reward, a drop of sweet water, they must poke their noses into two separate ports at the exact same time. ...

The rush to adopt enterprise AI has left crucial safeguards behind. A series of new reports in 2025 confirms a dual threat: the machines themselves are prone to error, and the human governance needed to manage them is dangerously thin. The result is a growing, measurable risk inside the world’s biggest companies. This is Bratislava—but it could be Boston or Berlin. An executive studies a market analysis on her screen. It arrived in minutes, not days. The text is clean. The numbers are plausible. The conclusions are bold. The report was written by an artificial intelligence agent. And she has no certain way to know if it is right. ...