In the autumn of 2025, a series of rapid-fire innovations revealed China’s new strategy in the global technology race. Faced with American sanctions designed to block its progress, Beijing didn’t just find a workaround; it began building a parallel world for artificial intelligence, complete with its own hardware, open-source software, and a bold play for the allegiance of developing nations. This is the story of how a trade war intended to contain China may have unleashed it. ...

Artificial intelligence promises a revolution, but in offices from Bratislava to Silicon Valley, it often delivers vague, useless results. The problem is not the machine. It is the user. Getting what you need from a powerful AI is a new skill, a discipline of clarity. The secret lies not in code, but in a well-crafted request. This is Bratislava—where old stone meets new glass, and the future arrives on a quiet current. In an office overlooking the Danube, Anna wrestled with that future. She had asked her artificial intelligence for a simple report on recent sales. The words that came back were smooth, confident, and wrong. The machine hallucinated trends. It invented product categories. It was useless. ...

In labs from Silicon Valley to Slovakia, a new form of software is taking shape. “Agentic AI” doesn’t just follow instructions; it creates its own. As corporate giants and a global community of open-source developers race to define this new frontier, they are building the blueprints for a future of autonomous work. But this revolution in code carries unprecedented power, and with it, profound risks. This is Bratislava. A developer watches her cursor blink on a line of code, but she is not writing the next step. She is writing the destination. She gives the machine a goal, a set of tools, and the authority to begin. The code she is building will not simply follow instructions. It will create its own. ...

An agent named Ellie writes emails for Virgin Voyages. She works inside Google’s new system. She does not get tired. Ellie learned the cruise line’s clever, cheeky voice, then she wrote marketing campaigns. The human team spent 40 percent less time on copy. In July, sales rose 28 percent year-over-year. This is the promise Google made real. On October 9, 2025, the company officially opened the door to this world. They called it Gemini Enterprise. It was not another tool. It was meant to be “the new front door for AI in the workplace”. The price was a challenge: thirty dollars a month per user for large companies and twenty-one for small businesses. It was a direct shot at Microsoft. ...

It started with a harmless request for a flan recipe, hidden in a LinkedIn profile. But the trick that duped a recruiting AI revealed a profound vulnerability in the automated systems now gatekeeping the modern workforce. Job applicants are embedding invisible commands in their resumes, turning a simple document into a potential weapon. This is the world of prompt injection, where a line of white text on a white page can hijack a machine, bypass security, and fundamentally corrupt the hiring process. The ghost in the machine is no longer a metaphor; it’s a candidate. ...

OpenAI’s latest developer day revealed a powerful new vision: a unified platform where AI agents could be built in minutes and world-class apps would run directly inside a chat window. The technology was seamless, the business opportunity immense. But for many developers, the demonstration of progress came with a familiar and unwelcome price: the construction of a new digital fortress, with OpenAI as its gatekeeper. This is Bratislava, the old city quiet under an autumn sky. Inside a glass-walled office overlooking the Danube, a young developer watched the recaps from San Francisco. He saw an engineer build a functioning AI agent in eight minutes, a task that might have taken his team a full quarter. The demonstration was clean, powerful, and fast. The feeling it produced was not joy. It was recognition. ...

Artificial intelligence offers a seductive bargain: perfect recall, instant analysis, and flawless execution. But as we delegate more of our thinking to these powerful new tools, a difficult question emerges from labs and classrooms. What is the long-term cost of this cognitive outsourcing? New research reveals an unsettling trade-off, forcing a new conversation about not just how we work, but how we think. The student sits in a quiet lab, a cap of sensors pressed to her scalp. On the screen is a writing prompt, the kind designed to test reasoning. A blinking cursor waits. She is a participant in a 2025 MIT experiment, and her task is to write an essay. But she has a powerful new partner. She types a query into a chat window, and the language model responds. Words fill the page. The task is executed. ...

A new analysis challenges the widespread fear of AI-driven job loss. After reviewing U.S. labor data for the 33 months since ChatGPT’s public launch, researchers found the job market remains remarkably stable, with no evidence of widespread disruption. The findings suggest that, for now, the reality of AI’s impact is far more gradual than the speculation. This is Modra—a wine town nestled in the Small Carpathians. The air smells of damp earth and fermenting grapes. Here, as in offices and factories worldwide, a question hangs in the air, potent and unspoken: When will the machines take the jobs? ...

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. ...