Last week, I posted a first article about my internship at LabGenius, a London-based biotech startup. Today, let’s continue with a focus on the tools and various skills this experience helped me develop.
This year, I’m finishing my studies at Polytech Sorbonne. To end my formation in Applied Mathematics and Computer Science, I did a 6-month internship; between March and August, I had the chance to work in London at LabGenius.
To end this series of articles on the AI & Art project I realized in collaboration with Cali Rezo, today I would like to give you some of my thoughts on this project and on AI in general, plus some info on the tools we used and on Cali’s upcoming events.
Over the past few weeks, we explored several questions related to AI and its application to art generation or analysis. Before finishing the series, let’s look at things from Cali’s point of view and talk a bit about artists and technology…
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?
In the last article, we focused on VAEs and GANs for image generation. This time, we’ll talk about analyzing images and trying to identify classes. We will also take this opportunity to talk about the usual traps and limits of AI classification.
To start off with this series of articles on the AI & Art project I did in collaboration with Cali Rezo, we’ll discuss some common generative models and how we applied them to her artwork to create new images in a “Cali-like” style.
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.
This semester, in the course of my High Performance Computing class, I applied basic notions of parallelization and distributed computing to common problems. For example, I studied how parallelizing the modelization of the shallow water equations can save you a lot of time!
Can we send a game into the Matrix and ‘re-virtualize’ it? Would it change its nature, its rules and its objectives, or could new technologies bring a freshness to some overused gameplays?