Artificial Intelligence

Today, we had an engaging fNIRS workshop at RITMO. One of the tasks we explored was “hyperscanning,” a term that confused several of the non-psychology people present. I was also bewildered when I encountered this term for the first time, so here is a short blog post to explain what it is. What is Hyperscanning? The short answer is that hyperscanning is the simultaneous recording of neural or physiological activity from two or more people to study interpersonal brain dynamics. ...

I see that the concept of “tempo octave” is being used by some researchers in the music information retrieval (MIR) community. This is a confusing term from a musical perspective. Here I explain why this is a bad idea. Octaves An octave is a core term in (Western) music theory related to describing intervals, relationships between two notes (and tones!) with a frequency ratio of 2:1. Here is an example of an octave: ...

Yesterday, I wrote about some reflections I had during Olgerta Asko’s PhD defence. Today, while chopping up the video recording to put on the RITMO web page, I thought that it might help to use a videogram to assist with segmentation. Videograms A videogram is similar to a motiongram, the main difference being that the videogram uses the regular video image as input to the “compression” instead of a motion video. Both give an impression of what is in a video file over time. We have functions for creating both videograms and motiongrams in the Musical Gestures Toolbox, but they are optimised for using other functions in the toolbox. ...

Today, we had the PhD defence of Olgerta Asko at RITMO. Her research is super interesting in itself (check out this feature story for an overview). This blog post is following up on one of the points she made during her trial lecture that I hadn’t thought about before: the difference between generalisation, inference, and deliberation. Towards deliberation Olga argued that current AI—here understood as large language models (LLMs)—are based on generalisation. They extract patterns from a lot of data and apply them broadly. As we have seen with recent commercial products and as I have explored in many ways on this blog, LLMs excel at this task. ...

Yesterday, I wrote about the history and future of AI in general. Today, I am continuing my explorations by examining the role of AI in the arts and the impact of the arts on AI. The exploration is based on this notebook, with 60 sources collected by NotebookLM. AI in the Arts AI has a multi-generational history in the arts, transitioning from centuries-old mechanical automatons to symbolic rule-making and eventually to deep learning-based approaches. In the following, I will go through some of the works picked out by NotebookLM. Some of them I know well, others I hadn’t heard about before. A complete list of detected works is at the end of the post. ...

Due to MishMash, I am nowadays lecturing on AI, music, and creativity several times a week. I usually include a brief overview of machine learning history, mainly to explain that ChatGPT didn’t come out of nowhere but was the result of decades of research. To check that my story holds and to get a few more critical years and names in place. This blog post summarizes the brief history of AI to date. ...

I find Google’s NotebookLM to be one of the most powerful tools for researchers these days. Its core function is to work with the material you upload. Hence, it differs from ChatGPT and other tools that invent things on their own or search the web. It also has many different types of reports, including audio and video. But how accurate is it? Testing NotebookLM To test NotebookLM on some material I know very well, I decided to provide it with a collection of public data about myself, more specifically, what I have registered in the Norwegian NVA system, which is the database we use in Norway to register all our academic activities. This includes academic publications, public lectures, artistic works, interviews, etc. In my case, that contains around 1000 entries dating back to 2000. ...

Happy new year! As we move into 2026, I am currently undergoing a gradual shift in my academic life. I don’t have any new annual projects planned this year (like 365 Sound Actions or #StillStanding). This year is more about wrapping up old things and moving on with exciting new projects. I am more or less done with writing Still Standing, which summarizes 15 years of micromotion research. My AMBIENT project is also about to end, with sveral of my doctoral and postdoctoral fellows wrapping up their projects in the coming months. The plan is to write a book based on AMBIENT, too, summarizing my interest in indoor environments. However, book writing takes time, so it will probably take a few years before I have completed that project. ...

Yesterday, I wrote about how I cleaned up a lot of old mess here on this blog. This made me realize that I have not paid attention to creating alt text for all my images, that is, descriptive text that describes the content of the image. That is an enormous job when you have several thousand images on a blog like this. So I decided to ask CoPilot for help. Getting AI help CoPilot first suggested creating alt text based on the image file names. That could have been a good idea if the filenames had been descriptive. However, they are not (in general), hence I asked for a solution that would actually analyse the content of the images. After a series of iterations, we (CoPilot and I) ended up with a Python script that does the job. ...

After running this blog for over two decades, it was time for some serious housekeeping. I converted from WordPress to Hugo some years ago, but never had time to do a proper cleanup. Then, the focus was on conversion and making it work. Now, with the help of GitHub Copilot, I finally got around to cleaning up the technical debt that had accumulated across several thousand posts. The Scale of the Challenge This blog currently contains more than 2000 English posts and 200 Norwegian posts, spanning from 2000 to 2025. In the beginning, I wrote HTML code manually, then moved on to server-side includes, then to WordPress, and now to Hugo. Throughout those years, I have changed themes and explored new web standards as they have evolved. That history shows in the inconsistencies that have built up in the content. ...