Blog

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 ( […]

Introduction Writing code is about solving problems, but not every problem is predictable. In the real world, your software will encounter unexpected situations: missing files, invalid user inputs, network timeouts, or even hardware failures. This is why handling errors isn’t just a nice-to-have; it’s a critical part of building robust and reliable applications for production.

Authors Alex (Qian) Wan: Alex (Qian) is a designer specializing in AI for B2B products. She is currently working at Microsoft, focusing on machine learning and Copilot for data analysis. Previously, she was the Gen AI design lead at VMware.Eli Ruoyong Hong : Eli is a design lead at Robert Bosch specializing in AI and

Large language models (LLMs) are improving in efficiency and are now able to understand different data formats, offering possibilities for myriads of applications in different domains. Initially, LLMs were inherently able to process only text. The image understanding feature was integrated by coupling an LLM with another image encoding model. However, gpt-4o was trained on

Why build things the hard way when you can design them the smart way? As a Supply Chain Data Scientist, I’ve explored various frameworks like LangChain and LangGraph to build AI agents using Python. Leveraging LLMs with LangChain for Supply Chain Analytics — A Control Tower Powered by GPT — (Image by Samir Saci) The illustration above is from an

Intro In Part 1 of this tutorial series, we introduced AI Agents, autonomous programs that perform tasks, make decisions, and communicate with others.  Agents perform actions through Tools. It might happen that a Tool doesn’t work on the first try, or that multiple Tools must be activated in sequence. Agents should be able to organize

Uncertainty quantification (UQ) in a Machine Learning (ML) model allows one to estimate the precision of its predictions. This is extremely important for utilizing its predictions in real-world tasks. For instance, if a machine learning model is trained to predict a property of a material, a predicted value with a 20% uncertainty (error) is likely

AI is transforming the way businesses operate, and nearly every company is exploring how to leverage this technology. As a result, the demand for AI and machine learning skills has skyrocketed in recent years. With nearly four years of experience in AI/ML, I’ve decided to create the ultimate guide to help you enter this rapidly

The state space of the first two neuron activations over time follows an attractor. What is one thing in common between memories, oscillating chemical reactions and double pendulums? All these systems have a basin of attraction for possible states, like a magnet that draws the system towards certain trajectories. Complex systems with multiple inputs usually