Working with ODEs Physical systems can typically be modeled through differential equations, or equations including derivatives. Forces, hence Newton’s Laws, can be expressed as derivatives, as can Maxwell’s Equations, so differential equations can describe most physics problems. A differential equation describes how a system changes based on the system’s current state, in effect defining state…

A mini multi-agent competition among 3 different LLM agents Generated using ChatGPT 4o.This article was originally posted on Art Fish Intelligence. LLMs are good at many things, and one of those things is playing games. People have used LLMs to play all sorts of games such as Minecraft, Chess, murder mystery games, Werewolf, and the…

As illustrated in figure 1, DSPy is a pytorch-like/lego-like framework for building LLM-based apps. Out of the box, it comes with: Signatures: These are specifications to define input and output behaviour of a DSPy program. These can be defined using short-hand notation (like “question -> answer” where the framework automatically understands question is the input…

End-to-end Project Implementation 19 min read · Aug 29, 2024 Image created by the authorDeveloping, deploying, and maintaining machine learning models in production can be challenging and complex. This is where Machine Learning Operations (MLOps) comes into play. MLOps is a set of practices that automate and simplify machine learning (ML)…

DFS can be implemented in two ways: iterative and recursive. Here, I’ll show you how to do it recursively as IMHO it is easier to understand and to code. This is also a fantastic opportunity to learn how recursion works if you’re not familiar with it yet. DFS implementation will be in pure Python. Below…

There is a lot of talk about the value of data being the new gold. Many companies are therefore pouring large sums of money into becoming data-driven. It is sold as a completely new way of doing business, almost as if business has never been driven by data before. Sure, many companies struggle with being…

Data Format Fundamentals — Single Precision (FP32) vs Half Precision (FP16) Now, let’s take a closer look at FP32 and FP16 formats. The FP32 and FP16 are IEEE formats that represent floating numbers using 32-bit binary storage and 16-bit binary storage. Both formats comprise three parts: a) a sign bit, b) exponent bits, and c)…

A gentle introduction to the latest multi-modal transfusion model Recently, Meta and Waymo released their latest paper — Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model, which integrates the popular transformer model with the diffusion model for multi-modal training and prediction purposes. Like Meta’s previous work, the Transfusion model is based on the…

One image can be worth thousands of words. Image by authorA confusion matrix is a convenient way to present the types of mistakes a machine learning mode makes. It is an N by N grid with numbers, where the value in the [n, m] cell represents the number of examples annotated with the n-th class…

Revisiting CPU for ML in an Era of GPU Scarcity Photo by Quino Al on UnsplashThe recent successes in AI are often attributed to the emergence and evolutions of the GPU. The GPU’s architecture, which typically includes thousands of multi-processors, high-speed memory, dedicated tensor cores, and more, is particularly well-suited to meet the intensive demands…