Technology

While the world was busy watching SpaceX blanket low-Earth orbit with thousands of Starlink satellites, Amazon has been working in the shadows.

In the ever-evolving landscape of generative AI, where text prompts can conjure entire worlds, Kling AI—developed by the innovative minds at Kuaishou—has just dropped a bombshell update.

Forget massive GPU clusters sipping megawatts of electricity. In a laboratory at the University of California, Los Angeles, researchers have built and experimentally demonstrated a system that generates complex, high-quality color images using nothing but coherent light, passive optical elements, and a single camera sensor. The heavy lifting that normally requires billions of multiply-accumulate operations on silicon is now performed instantly by physics.

For now, the skies over every major hub are a little quieter, and thousands of engineers are learning, in the hardest possible way, that quality assurance is not a checkbox. It is the only thing standing between a normal Tuesday morning and catastrophe.

The global solar industry has passed the point of no return. According to the latest data from Global Energy Monitor’s Solar Power Tracker, the world’s total pipeline of solar capacity – both operational and under development – now stands at an astonishing 2.85 terawatts (TWac). That is enough to power the entire planet several times over if fully realized. More importantly, the distribution of this future capacity reveals a dramatic and irreversible shift in the geography of clean energy.

In a quiet regulatory bombshell, the California Department of Motor Vehicles (DMV) has granted Waymo the largest autonomous-vehicle deployment permit in state history, effectively opening 12,000 square miles of territory stretching from the Napa Valley wine country in the north to the Mexican border in the south.

In a world where fitness trackers masquerade as chunky smartwatches and rings that promise to decode your sleep feel more like a guilty fashion faux pas, one Boston startup is whispering a revolution right into your ear—literally.

In the high-stakes arena of AI hardware, where fortunes rise and fall on the back of silicon efficiency, Google's latest move has sent shockwaves through the industry.

Google DeepMind has released Gemini Robotics-ER 1.5, the first publicly available foundation model built specifically to serve as a “reasoning brain” for physical robots. Unlike earlier robotics AIs that were locked inside labs or tied to specific hardware, this model is open to every developer through Google AI Studio and the Gemini API — no special access, no NDA.

In the high-stakes world of robotics, where a single glitch can turn a nimble helper into a toppled statue, Skild AI has unveiled a breakthrough that's as resilient as it is revolutionary. Meet Skild Brain, a foundation model designed to serve as a "universal brain" for robots of every shape and size—from agile quadrupeds to hulking humanoids and everyday home assistants.

Jay Neo, the former creative lead behind some of MrBeast’s most viral moments, has quietly launched Palo AI, an analytics platform that treats YouTube videos the way hedge funds treat stock charts.

A sweeping 94-page survey published in August 2025 offers the most comprehensive roadmap yet for the next generation of scientific AI. Titled A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers, the paper analyzes 270 scientific datasets and 190 benchmarks to explain why ordinary LLMs fail at real science—and how specialized scientific LLMs (SciLLMs) are rapidly closing the gap through richer multimodal data and closed-loop autonomous agents.

A comprehensive 78-page preprint published on arXiv (arXiv:2508.16628, August 2024, updated November 2025) by researchers from Stanford, Oxford, and the Max Planck Institute for Human Development argues that artificial intelligence has already moved far beyond being a neutral tool. It is actively reshaping human cognition itself — often in ways that most users never notice.

In the rapidly evolving landscape of artificial intelligence, few advancements have captured the imagination of researchers quite like SciAgent. This groundbreaking multi-agent system, detailed in a recent arXiv preprint (arXiv:2511.08151, by authors from leading AI labs including xAI collaborators), represents a paradigm shift in how machines tackle complex scientific problems.