Agentic AI: Single vs Multi-Agent Systems
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 […]
The Case for Centralized AI Model Inference Serving
As AI models continue to increase in scope and accuracy, even tasks once dominated by traditional algorithms are gradually being replaced by Deep Learning models. Algorithmic pipelines — workflows that take an input, process it through a series of algorithms, and produce an output — increasingly rely on one or more AI-based components. These AI […]
Understanding the Tech Stack Behind Generative AI
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 — […]
Create Your Supply Chain Analytics Portfolio to Land Your Dream Job
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 […]
A Simple Implementation of the Attention Mechanism from Scratch
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 […]
My Learning to Be Hired Again After a Year… Part 2
This is the second part of “My learning to being hired again after a year… Part I”. Hard to believe, but it’s been a full year since I published the first part on TDS. And in that time, something beautiful happened. Every so often, someone would leave a comment, highlight a sentence, or send me […]
How to Format Your TDS Draft: A Quick(ish) Guide
We all know what makes both authors and editors happy: a smooth, streamlined publication process where the path from draft to published article is quick and painless. We also know that many of our contributors—old-timers and new ones alike—might not have a lot of experience working with WordPress, the software powering our independent publication, and […]
From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC
Phase space of a nonlinear pendulum. Photo by the author. Hamiltonian mechanics is a way to describe how physical systems, like planets or pendulums, move over time, focusing on energy rather than just forces. By reframing complex dynamics through energy lenses, this 19th-century physics framework now powers cutting-edge generative AI. It uses generalized coordinates \( […]
The Art of Hybrid Architectures
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 […]
AI Agents from Zero to Hero — Part 3
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 […]