The greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”
— Eliezer Yudkowsky
AI is complex. Our explainers make it accessible. From large language models and neural networks to AI regulation and ethical frameworks, we break down the concepts, technologies, and debates shaping artificial intelligence — in plain language, with depth and accuracy. Built to stay relevant long after the news cycle moves on.
A routine release at Anthropic exposed 512,000 lines of Claude Code through a source map file, allowing developers to reconstruct and analyze large parts of its internal architecture.
Days after Super Micro’s co-founder was charged in what U.S. authorities call the biggest export control violation in American history, Congress has a bill ready — one that would embed tracking directly into chips before they leave the country.
AI was built to reduce risk. But as its use spreads, its risks are becoming measurable and costly. Munich Re, a Germany-based global reinsurer and one of the largest in the world, marks a turning point: AI is now a risk category being priced and insured.ng priced, managed, and insured.
India wants to stake its claim in the three way AI dominance race with U.S. and China. Foundation models remain key to this race.
The U.S. says it is promoting secure AI exports, not reviving the Biden-era AI Diffusion Rule. But as new controls on advanced AI chips emerge, the debate is shifting toward a larger question: who will control the computing power shaping the future of artificial intelligence?
An AI model that comes with an inbuilt safety valve and is guided by moral set of codes and principles? That’s Constitutional AI for you.
Pax Silica agreement between US and India could become a cornerstone of the global AI and chip ecosystem
An explainer article dissecting the term AI Browser, how does it differ from a regular browser and what future holds for internet search dynamics.
AI models are transforming industries. However, when even their creators can’t fully explain how they work, trust, safety and regulation all hit a wall. This is the “black box” problem.
From Shannon’s “chess machines” to Deep Blue and AlphaZero, chess has been the sandbox where researchers turned abstract ideas about machine intelligence into systems that could challenge the best human minds.