An ultracold atomic gas is used as a self-contained miniuniverse to show that time can be defined without an external clock. It’s demonstrated that entropy exchange between different sectors of the system provides an internal time that robustly orders the dynamics and yields a Schr\ odinger description of the observed evolution.
The first real brain upload just happened — and it might be the strongest evidence yet that simulation theory isn’t just philosophy anymore. A startup called Eon Systems copied a complete biological brain (139,255 neurons, 54 million synapses) into a physics simulation, and the digital fly started walking, grooming, and feeding on its own. No training. No AI. Just the copied wiring on a laptop. We break down how they did it, why a billion euros in previous brain simulation projects failed, what Nick Bostrom’s simulation argument actually says, and why a fruit fly on a laptop just moved the needle on whether our own reality could be simulated. We also look hard at the limitations — this work is not yet peer reviewed — and what it would actually take to scale this to a human brain.
Team leader Professor Sumeet Walia said the goal was to remove the delay and energy cost of transferring data between separate systems. “We’ve made real-time decision making a possibility with our invention, because it doesn’t need to process large amounts of irrelevant data and it’s not being slowed down by data transfer to separate processors.”
The device also showed the ability to retain visual information for longer periods without frequent electrical refresh signals, which reduces energy use and improves efficiency.
First author and RMIT PhD researcher Aishani Mazumder said the system draws inspiration from how the brain processes information. “Neuromorphic vision systems are designed to use similar analog processing to the human brain, which can greatly reduce the amount of energy needed to perform complex visual tasks compared with today’s technologies.”
Quantum computing has long been viewed as one of the most promising technologies of the future, and 2026 is bringing new signs of progress. Major technology companies and research institutions continue to invest billions into developing more stable and scalable quantum systems capable of solving problems beyond the reach of traditional computers. Recent advances have focused on improving error correction, increasing qubit reliability, and developing practical applications in fields such as drug discovery, materials science, logistics, and financial modelling. While widespread commercial adoption remains years away, experts believe the pace of innovation is accelerating as competition intensifies across the industry.
Board-certified family physician Dr. Gabrielle Lyon discusses groundbreaking anti-aging research during ‘America’s Newsroom,’ including a gene therapy that could reverse biological aging.
OpenAI introduces Deployment Simulation, a method to predict AI model behavior before deployment using real conversation data to improve safety and evaluation accuracy.
For 100 years the rule was absolute: to see quantum behavior, you freeze your machine to near absolute zero. In August 2025, a team at the University of Chicago broke it inside a living cell.
They turned enhanced yellow fluorescent protein from the same family that makes jellyfish glow into a working qubit, and detected the signal inside living mammalian cells and bacteria. Published in *Nature*, named a top-ten breakthrough of the year.
What you’ll learn: ✅ How a glowing protein became a real qubit. ✅ Why nature solved this before our best labs did. ✅ What genetically encoded quantum sensors mean by 2030.
There’s quantum machinery glowing inside you right now — and it’s more elegant than anything we’ve engineered.
Defying the laws of thermodynamics, experiments are beginning to show that a quantum state that is frozen forever might not be impossible. If we can tame it, it could unlock whole new types of matter