March 2026

How knowledge transfers from large teacher models to smaller student models through distillation techniques. Image: GaussianWaves The Free Lunch That Came With a Bill In October 2019, a team at Hugging Face, a French-American AI startup, published a model called DistilBERT. It retained 97% of its parent model’s performance on language-understanding benchmarks while running 60% faster and carrying 40% fewer parameters. “The numbers looked like a free lunch. Six years later, the bill arrived — as a geopolitical crisis.” When Distillation […]

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Cover Image Compared with the past, Today, AI tools such as ChatGPT, Google Gemini and Claude are experiencing a rapid growth. These tools are capable of generating various types of contents including texts, images, computer codes and even music based on simple prompts provided by users. Actually, How do these systems generate entirely new content from just a user prompt? In this article, we will explore how generative AI systems generate create content from user prompts. We will begin […]

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And why they matter in Machine learning! Read Loss Landscapes: Part 1 In the previous part, we learned what loss landscapes are, how they are formed, and the difference between simple, convex bowls and rugged, non-convex mountains. But knowing what the landscape looks like is only half the battle. How do we actually find the bottom of those valleys to train our machine learning model? 6: Gradient Descent Gradient descent is the core optimization algorithm in machine learning. Its entire job […]

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And why they matter in Machine learning! TL;DR: In machine learning, the loss landscape is a mathematical surface that maps a model’s parameters (its weights) to a specific “loss” value. The geometry of this surface — which can be full of bowls, ridges, valleys, and saddle points — drastically affects how easy or hard it is to train the model. Even though real-world AI models live in incredibly high dimensions, looking at simple 2D and 3D vizualisations will give you the core […]

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Part7 of the OpenClaw Series — Self-hosted AI Stack Introduction So far in this series, we’ve built a fully functional local AI agent: OpenClaw with Qwen3, SearXNG for web search, and Telegram as the interface. The agent runs, responds, and acts. But something is missing: visibility. How do you know what the agent is actually doing? How do you dispatch tasks in a structured way? How do you track progress in real time? That’s exactly what Mission Control (now rebranded as Autensa) provides — an […]

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How Category Encoding and Label Handling Influence Bias and Model Stability Machine learning models do not understand text. They work with numbers. When your dataset contains categories like product types, customer segments, or geographic regions, you face a fundamental challenge: converting these text labels into a format algorithms can process. Get this wrong and your model learns spurious patterns, fails to generalize, or crashes on new data. Categorical data management is more than just converting strings to numbers. It’s […]

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La inteligencia artificial no es una estrategia. Es la forma más rápida y más implacable de descubrir si realmente tienes una. En los últimos dos años, la inteligencia artificial se ha presentado como motor de productividad, palanca de reducción de costes, carrera por la infraestructura y, en sus versiones más dramáticas, como una ruptura civilizatoria. Los consejos de administración exigen hojas de ruta de inteligencia artificial. Los CEO anuncian agendas «AI-first». Divisiones enteras se reorganizan alrededor de herramientas […]

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The Honda Prelude was never simply a car. It was an engineering thesis disguised as a coupe: compact, disciplined, and unapologetically technical. At its best, it distilled Honda’s faith in precision manufacturing and clever packaging into something accessible and aspirational. Its return for 2026, after more than a quarter century away, isn’t nostalgia so much as institutional memory. The Prelude name carries expectations: balance over brute force, innovation over ornament, and a willingness to pursue mechanical elegance even […]

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