On Monday, Mel Slater, VR pioneer (and my former boss), gave a public talk as part of the Frontiers in Virtual Reality lecture series co-organised by my colleague Xueni ‘Sylvia’ Pan.

Though I’m very familiar with Mel’s work, every time I hear him speak he brings some new insights, and I thought I would share them (though do watch the talk as well, it contains important insights for all VR creators).

Embodiment

The talk was about embodiment in Virtual Reality, something we have talked about in our MOOC. This is the ability to inhabit another body while in VR.

While many VR experiences don’t show more than hands it is possible to set them up so that you see yourself as having a graphical body (including seeing your new self in a mirror, a powerful part of the illusion). Because VR systems track your hands and head, the hands and head of your virtual body move with you. This correspondence between your own physical movements and the movements you see on your virtual body (called visuomotor congruence) gives you the sensation that this really is your body. …

I recently did something I don’t normally do, I collaborated on an academic paper with my father, Donald Gillies. He is a philosopher of science, and the paper we wrote originated in the mid 90s when he published a book on AI and Scientific method, which summarised the state of the art of AI at the time and how it might impact how we think about science.

This year he was asked to present a paper about his work on AI, but since he has been working on other things (mostly the philosophy of medicine) in the intervening decades, and clearly, AI has moved on a bit since the 90s, he asked me to help update it. We were supposed to present the paper at the Conference on the Philosophy of Science today: Seven perspectives (XXV Conference on Contemporary Philosophy and Methodology of Science), Ferrol, Spain, but that didn’t quite go to plan as Spain went into COVID-19 lockdown during the conference. …

A couple of weeks ago I wrote a post comparing Social VR with video calling as methods for keeping in touch and working during lockdown.

Since then we had a class in Altspace for our Masters in Virtual and Augmented Reality. It was nice to get a chance to use VR for teaching. One interesting feature was that, because we were in a public room we were joined by a number of members of the public, who made some nice additions to the conversation. We ended with a discussion of Social VR and what benefits it has during the COVID-19 lockdown. …

This week I did a “lockdown lecture”, part of a series of talks from academics in Goldsmiths, Department of Computing. They are a way of keeping in touch with our current students, prospective students and wider public during the COVID-19 lockdown. It was great to make contact with a lot of people (almost 250!) and there was a lot of really great, active discussion in the chat, so for me it was a great experience.

The title of the talk was Virtual Reality and Artificial Intelligence, two of my main interests. I often talk about the two separately, but it was a chance to talk about how AI (or more exactly Machine Learning) can be used to make better VR experiences. …

There are many ways of classifying different types of VR interaction. These classifications have different uses. Our MOOC describes various exotic forms such as Natural Interaction, Magical Interaction, Passive Interaction and Non-Diegetic Interaction. Most of these are based on full body movements, which will increase the sense of presence, relative to traditional buttons and menu interfaces.

In a recent paper, Understanding the role of Interactive Machine Learning in Movement Interaction Design, I had another go at defining important types of movement interaction. This time they related to how the movement is defined and, therefore, how we design these different types of interaction. …

In my last post I talked about Social VR and mentioned an important paper by Mel Slater, Anthony Steed and colleagues, called Small-Group Behavior in a Virtual and Real Environment: A Comparative Study. I thought I should talk about it in a bit more detail as it has important implications for current Social VR.

The paper was published in 2000, making it about 20 years old (but that means the research was done even earlier). This is a reminder that VR research has been happening for a long time (this is far from being their first paper), and that this older research is still very relevant as we are only just starting to put some of the technologies from that era into widespread practice. …

I’m writing this a couple of weeks in to the UK’s lockdown for the COVID-19 pandemic. This is my first chance to take a step back to think and write after two very hectic weeks of adjusting to teaching and research online (and, to be honest a very hectic 6 months, for lots of, mostly good, reasons).

It is also a chance to reflect on a couple of weeks of having almost constant meetings, but having them all remote and online. Like most people I have done the majority of these via a bewildering number of video conferencing systems (Skype- standard and business, Zoom, Microsoft Teams, Big Blue Button, Whereby, Discord, WhatsApp, WeChat, and probably others, it sometimes seems like every meeting has to introduce a new platform). Having VR headsets at home (plus friends and colleagues who also have them), I have also been lucky enough to have meetings in a similarly bewildering set of Social VR platforms (Mozilla Hubs, AltSpace, Rec Room, VR Chat, Big Screen and others). …

Today I am proud to be launching a new MOOC: Machine Learning for All, together with this blog to support the course. I have been working on the course for almost a year and, in a certain sense, even longer because it builds on over a decade of work on how to democratise machine learning.

The course is based on two fundamental beliefs of mine: that (almost) anyone can learn to do machine learning and that everyone should.

Anyone Can

The first belief might seem strange given that machine learning is often seen as one of the most advanced sub-fields of computer science, filled with the brainiest, most mathematically adept researchers. …