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  • AI Foundations

    A History of Artificial Intelligence — Part 3: From Transformers to ChatGPT — and What It Means for the Strong AI Debate

    This is the final part of a three-part series on the history of AI. Part 1 covered AI’s philosophical origins and the Turing Test, Strong AI vs. Weak AI, and Searle’s Chinese Room argument. Part 2 traced the rise of machine learning and deep learning through the founding of OpenAI in 2015. Part 3 picks up the story with the breakthrough that made ChatGPT possible. The Paper That Changed Everything By 2017, deep learning had already transformed computer vision and game-playing AI, as Part 2 described. But language remained stubbornly difficult. Earlier neural network architectures processed text sequentially, word by word, which made them slow to train and bad at…

  • AI Foundations

    A History of Artificial Intelligence — Part 2: The Machine Learning Revolution and the Road to OpenAI

    This is Part 2 of a three-part series tracing the history of artificial intelligence. Part 1 covered AI’s philosophical origins, the Dartmouth Conference, and the AI winters. Part 2 picks up with the shift toward machine learning and traces the path to the founding of OpenAI. A New Approach: Learning From Data Instead of Rules By the end of Part 1, AI research had hit a wall. The symbolic, rule-based approaches of expert systems, sometimes retroactively called “Good Old Fashioned AI”, involved pre-programming knowledge and rules directly into a system. These approaches were brittle and difficult to scale. A quieter alternative had existed since the field’s earliest days but had…

  • AI Foundations

    A History of Artificial Intelligence — Part 1: From Ancient Dreams to the Birth of a Field

    This is Part 1 of a three-part series tracing the history of artificial intelligence, from its philosophical roots to the creation of OpenAI and ChatGPT. Part 1 covers the early foundations of AI through the AI winters of the 1970s and 80s. Before the Machines: A Question, Not a Technology Long before computers existed, humans imagined artificial beings capable of thought — from mechanical automatons in ancient myth to philosophical debates about the nature of mind. But the scientific story of AI begins not with a machine, but with a question. In the 1950s, researchers started exploring whether intelligence could be formalized, tested, and eventually built into machines. The foundations…

  • Enterprise AI

    The Governance Imperative: Why Agentic AI Deployment Is Outpacing Enterprise Readiness

    From Pilot Fatigue to Production Reality Enterprise AI has crossed a threshold. Gartner forecasts that 40% of enterprise applications will embed task-specific AI agents by end of 2026, up from under 5% in 2025. That is not incremental adoption, it is a structural reconfiguration of how enterprises orchestrate work. The transition from isolated generative AI experiments to production-grade, multi-agent architectures is no longer a roadmap item. It is happening now, unevenly, and largely ahead of the governance frameworks designed to contain it. The numbers are unambiguous about the asymmetry. Only 8% of organisations globally have a comprehensive AI governance framework, while 88% are actively using AI across business functions. That…

  • AI News & Industry Updates

    When the AI Boom Meets Reality: Understanding the June 2026 Stock Selloff

    A Turbulent Week for AI Stocks The artificial intelligence sector has been one of the most exciting investment stories of the past several years. But in late June 2026, the mood shifted sharply. On June 23–24, 2026, the tech-heavy Nasdaq dropped 2.21% and the S&P 500 fell 1.44%, as investors sold semiconductor and AI-related shares broadly. The impact did not stay confined to Wall Street. South Korea’s Kospi index tumbled 10%, tripping a circuit breaker (an automatic 20-minute trading halt) with memory chipmakers SK Hynix and Samsung each falling more than 12%. In total, semiconductor stocks shed more than $1.3 trillion in market value during this correction. For many observers,…

  • AI News & Industry Updates

    OpenAI’s $852 Billion Valuation: What It Means for the Future of AI

    The Biggest Bet in Tech History Artificial Intelligence has seen no shortage of headline-grabbing moments over the past few years, but one development from mid-2026 stands apart from the rest. OpenAI closed its largest funding round to date, raising $122 billion at an $852 billion valuation, with major investments from Amazon, NVIDIA, and SoftBank leading the round. To put that number in perspective, $852 billion places OpenAI among the most valuable companies ever created, surpassing the market capitalisation of most nations’ largest corporations and approaching the GDP of entire economies. This is not just a story about one company raising money. It is a signal about where the technology industry…

  • AI Engineering

    Why AI Engineering Is Becoming One of the Most In-Demand Technology Skills

    The Rise of AI Engineering Artificial Intelligence has moved far beyond research laboratories and technology giants. Businesses of every size, from startups to global enterprises, are now actively looking for practical ways to integrate AI into their daily operations. As a result, AI Engineering has emerged as one of the fastest-growing and most in-demand career paths in the technology industry. Unlike traditional software development, AI engineering focuses on building applications that can understand language, generate content, analyze data, and automate complex tasks using modern AI models. AI engineers combine software engineering skills with machine learning tools, APIs, cloud services, and prompt engineering to design intelligent applications that solve real business…

  • AI Foundations

    What Is Artificial Intelligence? A Beginner’s Guide

    Introduction Artificial Intelligence (AI) is one of the most transformative and talked-about technologies of our time, and for good reason. In just a few decades, AI has moved from the pages of science fiction novels into our smartphones, hospitals, classrooms, and workplaces. It powers the recommendations that appear when you open Netflix, helps doctors detect diseases earlier than ever before, and enables cars to navigate roads with minimal human input. What makes AI remarkable is not just what it can do today, but how rapidly it continues to evolve. New breakthroughs in language understanding, image generation, and autonomous reasoning are being announced almost every month. Industries that once seemed immune…