For decades, quantum computing has been a futuristic dream, promising to revolutionize industries from pharmaceuticals to finance. While IBM and Google have made impressive strides using superconducting qubits, Microsoft’s latest breakthrough—the Majorana 1 chip—introduces a new state of matter to make quantum computing more stable and scalable.

Artificial Intelligence (AI) has revolutionized the way we interact with technology. From drafting emails to answering complex questions, they offer incredible utility and accessibility. However, beneath their impressive capabilities lies a fundamental limitation: AIs are not inherently correct. Understanding this limitation and addressing it through guardrails is critical for fostering trust, transparency, and responsible AI use.

AI is transforming industries, redefining productivity, and reshaping how we interact with technology. The newest AI models have proven they are powerful as they are powered by massive datasets and intricate algorithms, have an impressive ability to generate human-like text. However, as revolutionary as the newest AI models are, they are not infallible sources of truth. Instead of being deemed “correct,” they should be recognized as providers of the “next best answer.”

Artificial Intelligence (AI) has rapidly evolved from a niche technological endeavor to a cornerstone of modern society, influencing sectors ranging from healthcare to finance. Its integration promises unprecedented advancements, yet it also presents challenges that necessitate careful navigation.

While nations debate frameworks and carve out strategies, one thing remains clear: regulating outcomes, not technology, is the only way to ensure AI systems are safe, ethical, and beneficial for humanity.

Large Language Models might seem mysterious, but at their core, they’re just powerful tools for predicting what comes next in a sequence of words. By thinking of them as a puzzle-builder that uses patterns and probabilities, we can demystify how they work and appreciate their strengths and limitations.

As artificial intelligence (AI) continues to advance at an exponential rate, we are increasingly confronted with a paradox: the more intelligent machines become, the less certain we are about the reality they present. AI is creating a new form of “pseudo-reality,” one where machines influence perceptions, create simulations, and blur the line between what is real and what is fabricated.

The UK government's recent announcement of a comprehensive AI rollout across public services underscores the transformative potential of artificial intelligence in enhancing efficiency and economic growth. Prime Minister Keir Starmer emphasized the ambition to make Britain a world leader in AI, with plans to increase public AI computing power twentyfold by 2030 and integrate AI into various sectors, including education and infrastructure management.