Artificial Intelligence News

Artificial intelligence is reshaping law, ethics, and society at a speed that threatens fundamental human dignity. Dr. Maria Randazzo of Charles Darwin University warns that current regulation fails to protect rights such as privacy, autonomy, and anti-discrimination. The “black box problem” leaves people unable to trace or challenge AI decisions that may harm them.

While superconducting qubits are great at fast calculations, they struggle to store information for long periods. A team at Caltech has now developed a clever solution: converting quantum information into sound waves. By using a tiny device that acts like a miniature tuning fork, the researchers were able to extend quantum memory lifetimes up to 30 times longer than before. This breakthrough could pave the way toward practical, scalable quantum computers that can both compute and remember.

Researchers discovered that bees use flight movements to sharpen brain signals, enabling them to recognize patterns with remarkable accuracy. A digital model of their brain shows that this movement-based perception could revolutionize AI and robotics by emphasizing efficiency over massive computing power.

A research team has created a quantum logic gate that uses fewer qubits by encoding them with the powerful GKP error-correction code. By entangling quantum vibrations inside a single atom, they achieved a milestone that could transform how quantum computers scale.

Researchers have unveiled a new quantum material that could make quantum computers much more stable by using magnetism to protect delicate qubits from environmental disturbances. Unlike traditional approaches that rely on rare spin-orbit interactions, this method uses magnetic interactions—common in many materials—to create robust topological excitations. Combined with a new computational tool for finding such materials, this breakthrough could pave the way for practical, disturbance-resistant quantum computers.

Scientists have designed swarms of microscopic robots that communicate and coordinate using sound waves, much like bees or birds. These self-organizing micromachines can adapt to their surroundings, reform if damaged, and potentially undertake complex tasks such as cleaning polluted areas, delivering targeted medical treatments, or exploring hazardous environments.

Researchers at Harvard have created a groundbreaking metasurface that can replace bulky and complex optical components used in quantum computing with a single, ultra-thin, nanostructured layer. This innovation could make quantum networks far more scalable, stable, and compact. By harnessing the power of graph theory, the team simplified the design of these quantum metasurfaces, enabling them to generate entangled photons and perform sophisticated quantum operations — all on a chip thinner than a human hair. It’s a radical leap forward for room-temperature quantum technology and photonics.

AI-generated videos are becoming dangerously convincing and UC Riverside researchers have teamed up with Google to fight back. Their new system, UNITE, can detect deepfakes even when faces aren’t visible, going beyond traditional methods by scanning backgrounds, motion, and subtle cues. As fake content becomes easier to generate and harder to detect, this universal tool might become essential for newsrooms and social media platforms trying to safeguard the truth.

Even the most powerful AI models, including ChatGPT, can make surprisingly basic errors when navigating ethical medical decisions, a new study reveals. Researchers tweaked familiar ethical dilemmas and discovered that AI often defaulted to intuitive but incorrect responses—sometimes ignoring updated facts. The findings raise serious concerns about using AI for high-stakes health decisions and underscore the need for human oversight, especially when ethical nuance or emotional intelligence is involved.

Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends them diving into word meaning instead—an abrupt “phase transition” reminiscent of water flashing into steam. By revealing this hidden switch, researchers open a window into how transformer models such as ChatGPT grow smarter and hint at new ways to make them leaner, safer, and more predictable.

A multinational team has cracked a long-standing barrier to reliable quantum computing by inventing an algorithm that lets ordinary computers faithfully mimic a fault-tolerant quantum circuit built on the notoriously tricky GKP bosonic code, promising a crucial test-bed for future quantum hardware.

A research team has achieved the holy grail of quantum computing: an exponential speedup that’s unconditional. By using clever error correction and IBM’s powerful 127-qubit processors, they tackled a variation of Simon’s problem, showing quantum machines are now breaking free from classical limitations, for real.

Quantum computing just got a significant boost thanks to researchers at the University of Osaka, who developed a much more efficient way to create “magic states” a key component for fault-tolerant quantum computers. By pioneering a low-level, or “level-zero,” distillation method, they dramatically reduced the number of qubits and computational resources needed, overcoming one of the biggest obstacles: quantum noise. This innovation could accelerate the arrival of powerful quantum machines capable of revolutionizing industries from finance to biotech.

Chalmers engineers built a pulse-driven qubit amplifier that’s ten times more efficient, stays cool, and safeguards quantum states—key for bigger, better quantum machines.

Scientists at the University of Amsterdam discovered that our brains automatically understand how we can move through different environments—whether it’s swimming in a lake or walking a path—without conscious thought. These “action possibilities,” or affordances, light up specific brain regions independently of what’s visually present. In contrast, AI models like ChatGPT still struggle with these intuitive judgments, missing the physical context that humans naturally grasp.

AI is revolutionizing the job landscape, prompting nations worldwide to prepare their workforces for dramatic changes. A University of Georgia study evaluated 50 countries’ national AI strategies and found significant differences in how governments prioritize education and workforce training. While many jobs could disappear in the coming decades, new careers requiring advanced AI skills are emerging. Countries like Germany and Spain are leading with early education and cultural support for AI, but few emphasize developing essential human soft skills like creativity and communication—qualities AI can’t replace.

Imagine supercomputers that think with light instead of electricity. That s the breakthrough two European research teams have made, demonstrating how intense laser pulses through ultra-thin glass fibers can perform AI-like computations thousands of times faster than traditional electronics. Their system doesn t just break speed records it achieves near state-of-the-art results in tasks like image recognition, all in under a trillionth of a second.

AI researchers in Switzerland have found a way to dramatically cut cement s carbon footprint by redesigning its recipe. Their system simulates thousands of ingredient combinations, pinpointing those that keep cement strong while emitting far less CO2 all in seconds.

Researchers have created a revolutionary robotic skin that brings machines closer to human-like touch. Made from a flexible, low-cost gel material, this skin transforms the entire surface of a robotic hand into a sensitive, intelligent sensor. Unlike traditional robotic skins that rely on a patchwork of different sensors, this material can detect pressure, temperature, pain, and even distinguish multiple contact points all at once.

A team of researchers has shown that even small-scale quantum computers can enhance machine learning performance, using a novel photonic quantum circuit. Their findings suggest that today s quantum technology isn t just experimental it can already outperform classical systems in specific tasks. Notably, this photonic approach could also drastically reduce energy consumption, offering a sustainable path forward as machine learning s power needs soar.