Tag Archives: LLMs

5 Surprising Truths About the AI Revolution

We live in a time when technological change is happening faster than ever. This sense of acceleration isn’t just a subjective impression—it’s a measurable reality. As early as 1999, Vint Cerf, one of the fathers of the internet, observed that one year in the internet industry was like seven “dog years.” That comparison, once apt at capturing the pace of innovation, now seems insufficient in the context of artificial intelligence. The speed at which AI is reshaping our world is unprecedented—faster than in previous technology waves, including the internet era. The amount of data and analysis on the topic is overwhelming, and media narratives often swing between utopian excitement and dystopian fear. Yet beneath the headlines lie hard numbers that paint a far more nuanced and fascinating picture.

In this article, I present five of the most surprising and counterintuitive findings from the latest analyses. They help explain the true nature of the AI revolution—its unprecedented speed, paradoxical economics, geopolitical tensions, impact on the physical world, and the fundamental shift in the labor market. These are truths worth knowing to navigate the era ahead with intent.

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Transformer – Roadmap

Introduction

Welcome to my postsseries on the inner workings of Transformers, with a focus on their application in large language models (LLMs). Over time, I’ll break down key components—like self-attention, positional encoding, and layer normalization—highlighting how they contribute to the remarkable capabilities of modern LLMs. Each part of this post will explore one element in depth, grounded in both theoretical understanding and practical relevance. The goal is to make these complex systems more transparent and accessible, especially for those interested in research, development, or curious exploration. Let’s begin this journey into the architecture behind today’s most powerful AI models.