Showing items from Artificial Intelligence and Data Science

The Ultimate LLM Inference Battle, vLLM vs. Ollama vs. ZML

Raphaël Semeteys
7 Min To Read
29 Jan, 2026
- Artificial intelligence and data science

A structured, data-driven comparison of today’s leading open-source engines for serving AI models.

The Yoga of Image Generation – Part 3

Raphaël Semeteys
5 Min To Read
24 Jun, 2025
- Artificial intelligence and data science

In the first two parts of this series, we explored Stable Diffusion, ComfyUI, and how to build Text-to-Image and Image-to-Image workflows to generate images of Yoga poses. With the help of ControlNets, we learned how to transfer a pose from an abstract reference image to our final generated image.

The Yoga of Image Generation – Part 2

Raphaël Semeteys
4 Min To Read
14 Apr, 2025
- Artificial intelligence and data science

In the first part of this series on image generation, we explored how to set up a simple Text-to-Image workflow using Stable Diffusion and ComfyUI, running it locally. We also introduced embeddings to enhance prompts and adjust image styles. However, we found that embeddings alone were not sufficient for our specific use case: generating accurate yoga poses.

The Yoga of Image Generation – Part 1

Raphaël Semeteys
6 Min To Read
11 Feb, 2025
- Artificial intelligence and data science

In this series of articles, I will introduce image generation using Stable Diffusion and ComfyUI. This first article discusses the theory and provides basic examples. My goal is to generate precise images of yoga poses using only your local machine. Due to legal restrictions, I cannot use images from the Internet. Given these limitations, how can generative AI assist?

How Open is Generative AI? Part 2

Raphaël Semeteys Luxin Zhang
20 Min To Read
19 Dec, 2023
- Artificial intelligence and data science

Embarking on the second and last part of our ‘Generative AI Openness’ series, we earlier established a straightforward framework to gauge the openness of Large Language Models (LLMs) and utilized it to explore LLM development and the positioning of key players. We noticed a trend towards increasingly restricted LLM artifacts for OpenAI and Google, contrasted with Meta’s more open approach.

How Open is Generative AI? Part 1

Raphaël Semeteys Luxin Zhang
18 Min To Read
25 Oct, 2023
- Artificial intelligence and data science

Welcome to this two-part series on Generative AI Openness, where we explore the history, current landscape, and potential future of open collaboration and proprietary control in the development of Language Language Models (LLMs). In this first part, we will delve into the importance of inspecting the openness of each component in the LLM training process, and how this can impact the potential limitations on the model use or reuse imposed by one or more of its components. In the second part of this series, we will explore the potential benefits and drawbacks of sharing Generative AIs openly for the collective advancement of society.