A hands-on guide for exploring how to train a simple AI model using TensorFlow.js to inpaint missing parts of images - without needing large datasets or prior machine learning experience.
The final article in the Agentic AI series explores multi-agent systems: how specialised agents collaborate through structured handoffs to complete complex user goals.
The orchestrator-worker pattern brings scalable structure to agentic AI workflows by cleanly separating high-level planning from specialised task execution. Through a practical trip planning example, this article demonstrates how LLMs can dynamically coordinate expert agents, grounded in schema-driven logic and real-world data.
This article explores how to implement a reflection loop-an agentic AI pattern where a model generates, critiques, and iteratively improves its output - using image captioning as a practical example.
Unlock faster, more diverse reasoning by running multiple LLM prompts in parallel and aggregating their responses into a single, cohesive output.
A hands-on walkthrough for web developers to demystify large language models by actually building a mini Transformer from scratch.
Explore how to intelligently route AI queries using schema-guided function calling and contextual categorisation.
Learn how prompt chaining enables AI to tackle complex tasks through step-by-step reasoning, boosting both accuracy and interpretability.
In this article we take a look at how to see if an image has low-entropy for LCP calculation.
WebP, AVIF, JPEG XL, Progressive JPEG - how do these image formats compare in terms of their load speeds and how can we measure it? In this article we review a small app that gives us a visual answer.
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