Artificial intelligence is no longer something reserved for engineers, coders, or tech insiders. It is quickly becoming one of the most important skills of our time — shaping how people work, learn, create, communicate, and build businesses. But for many beginners, AI still feels confusing, intimidating, and full of technical language.
Artificial intelligence is increasingly seen as a real productivity story, not just a technology story. The OECD’s recent work estimates that AI could raise annual total factor productivity growth by roughly 0.25 to 0.6 percentage pointsover a 10-year horizon, equivalent to about 0.4 to 0.9
Artificial intelligence is advancing at a breathtaking pace in research labs and tech giants — yet across everyday business operations, adoption remains uneven, fragmented, and often disappointingly slow. The result is a widening gap between what AI can do and what most organizations actually deploy at scale. The Paradox: Ubiquity Without
For years, the world’s biggest artificial intelligence gatherings sounded like emergency meetings: catastrophic risk, existential threats, runaway systems. Today, the tone has changed. Across continents, global AI summits are increasingly focused on deployment, economic growth, public services, and measurable outcomes — not just hypothetical dangers. This shift is not speculation.
Artificial intelligence is no longer advancing in isolated labs or single companies. Instead, it is being shaped in high-level forums where governments, startups, corporations, investors, and academia converge. Major AI leadership conferences have become strategic infrastructure for the digital age — places where policy is negotiated, partnerships are formed, and the
AI is rapidly transforming smartphone cameras from passive imaging tools into autonomous creative systems. The next wave of devices doesn’t just capture reality — it interprets, reconstructs, and even invents it. Evidence from recent flagship launches, manufacturer briefings, and technical previews shows that AI-centric camera systems with generative editing and
Artificial intelligence is no longer just a software story. It is becoming a hard-infrastructure story — about where the data centers sit, who controls advanced chips, how much electricity is available, and whether a country has domestic access to the compute needed to train and run modern AI systems. The OECD
What once looked like a fringe experiment is starting to look more like a new production layer. AI-focused film events are no longer limited to tech demos or online curiosities: Runway’s AI Festival, launched in 2022, has expanded beyond film into design, fashion, advertising and gaming, while the Reply
Google’s latest Gemini push appears to be a two-step upgrade, not a single launch. On February 12, Bloomberg reported that Google had updated Gemini Deep Think to improve performance in math and science research. A week later, TechCrunch reported that Google released Gemini 3.1 Pro in preview, bringing
While executives proclaim artificial intelligence as the future of finance, the departments that manage corporate cash, risk, and liquidity are moving at a far slower pace. Treasury teams — arguably the most risk-sensitive units in any company — remain cautious, constrained by data problems, legacy systems, and regulatory exposure. Recent surveys show
From AI Race to AI Commons: The New Delhi Declaration’s Big Global Signal The New Delhi Declaration has emerged as a major statement of global intent on artificial intelligence, with the Indian government saying it was endorsed by 91 countries and international organisations after the AI Impact Summit in
Artificial intelligence assistants are no longer experimental tools — they are becoming daily work companions. Yet not all AI models are built for the same job. While Grok, ChatGPT, Perplexity, and Google Gemini are often grouped together, they differ significantly in design philosophy, data access, reliability, and use cases. Understanding those