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We’ve seen this shift the last few years from building rigid programming systems to natural language-driven workflows, all made possible with more advanced large language models. One of the interesting areas into these Agentic Ai systems is the difference between building a single versus multi-agent workflow, or perhaps the difference between working with more flexible […]

In the previous parts of this series, we looked at Graph Convolutional Networks (GCNs) and Graph Attention Networks (GATs). Both architectures work fine, but they also have some limitations! A big one is that for large graphs, calculating the node representations with GCNs and GATs will become v-e-r-y slow. Another limitation is that if the

Introduction The Attention Mechanism is often associated with the transformer architecture, but it was already used in RNNs. In Machine Translation or MT (e.g., English-Italian) tasks, when you want to predict the next Italian word, you need your model to focus, or pay attention, on the most important English words that are useful to make

Supply chains are under pressure like never before. From climate-driven disruptions to geopolitical shifts, businesses must adapt to rising costs, new trade barriers and growing sustainability demands. In this new world where supply chains face uncertainty, Supply Chain Analytics is essential to keep resilient operations. Samir, can you advise me on how to build a supply chain analytics

Understanding the Tech Stack Behind Generative AI When ChatGPT reached the one million user mark within five days and took off faster than any other technology in history, the world began to pay attention to artificial intelligence and AI applications. And so it continued apace. Since then, many different terms have been buzzing around —

In my previous article, I discussed how morphological feature extractors mimic the way biological experts visually assess images. This time, I want to go a step further and explore a new question:Can different architectures complement each other to build an AI that “sees” like an expert? Introduction: Rethinking Model Architecture Design While building a high

When I talk to [large] organisations that have not yet properly started with Data Science (DS) and Machine Learning (ML), they often tell me that they have to run a data integration project first, because “…all the data is scattered across the organisation, hidden in silos and packed away at odd formats on obscure servers

The 3d Reconstruction journey from 2D photographs to 3D models follows a structured path.  This path consists of distinct steps that build upon each other to transform flat images into spatial information.  Understanding this pipeline is crucial for anyone looking to create high-quality 3D reconstructions. Let me explain… Most people think 3D reconstruction means: Taking

Intro In Part 1 of this tutorial series, we introduced AI Agents, autonomous programs that perform tasks, make decisions, and communicate with others.  In Part 2 of this tutorial series, we understood how to make the Agent try and retry until the task is completed through Iterations and Chains.  A single Agent can usually operate