Procedural generation

Nodevember #1

Last November, the Nodevember event took place. This event focuses on doing procedural rendering with 3D software and it offers daily-themed challenges: the goal is to start with the simplest possible 3D model (a cube, a sphere…) and to create amazing visuals only with nodes and procedural shading.

Read More »Nodevember #1

“L’Oulipo”: mixing maths and literature

In 1911, the French writer André Gide said that: “Art is born from constraint, thrives in the struggle and is killed by freedom” (personal translation of the original quote). Although some might disagree and believe that one should create in total liberty, others have decidedly followed this path to eventually come together as a group of writers and mathematicians called the “OuLiPo”.

Read More »“L’Oulipo”: mixing maths and literature

AI & Art with Cali Rezo (4): Explainability and uncertainty of AI models

In the third article of the series, we discussed how to apply AI to art analysis. Even if our results were not as conclusive as we’d hoped, they still raised a few questions that we will tackle today: what is really happening in these black box models that are neural networks? And to which extent can we assess how certain a model is of its predictions?

Read More »AI & Art with Cali Rezo (4): Explainability and uncertainty of AI models

AI & Art with Cali Rezo (1): Project & Goals

Nowadays, machine learning (ML) is a red-hot topic which is discussed everywhere in various ways. More and more companies are relying on AI as part of their production process, be it in the domain of finance, medicine, management, art… This last application of ML algorithms, in particular, is really interesting to me. And, since the great abstract painter Cali Rezo shares this interest, we decided we would collaborate on a project to study how to apply AI to art.

Read More »AI & Art with Cali Rezo (1): Project & Goals

A peek at Markov chains

Last time, we introduced the basic concepts of our name generator and we saw how webcrawlers can help us gather information easily and efficiently. Now, it’s time to use this information to actually produce some words! To do so, we will rely on statistics and Markov chains.

Read More »A peek at Markov chains