BCSWomen AI Accelerator
BCSWomen Chair Sarah Burnett has had a fab idea, which is to hold a series of webinars that talk about AI and how it is changing the world. In BCSWomen we do a lot of stuff about the women, and a lot of stuff to support women, but we also do a lot of stuff that is useful for tech people in general. The AI Accelerator falls into this category; the idea is that tech is changing and AI is driving that change, so we’re going to try and provide a background and overview of AI to help people get to grips with this. Once I heard the idea I had to put my hand up for a talk, and I grabbed the first slot general intro talk – “What is AI?“. The other speaker in the session was Andrew Anderson of Celaton, who talked about the business side of AI. If you want to join in follow @bcswomen on twitter and I’m sure they’ll tweet about the next one soon.
As ever I went a bit over the top on the talk prep, but managed to come up with a theme and 45 slides with a bunch of reveals/animations that I thought covered some key concepts quite well. (Yes 45 slides for 20 minutes is a bit much but hey, I rehearsed the timings down to a tee and it was OK.) The live webinar had a few issues with audio, so I re-recorded my talk as a stand-alone youtube presentation; it’s not as good as the original outing (as a bit of time had passed and I hadn’t rehearsed as much) but I think it still works OK. If you want to watch it, here it is:
You can find the slides online here: AI Accelerator talk slides. I am 99% certain that all the images I used were either free for reuse, or created by me, but if it turns out I’ve used a copyright image let me know and I’ll replace it.
the reasoning behind the talk
I’ve been “doing” AI since I first went to uni in 1993, and what people mean when they say AI has changed massively over this time. Things that I read about as science fiction are now everyday, and a lot of this is down to advances in machine learning (ML). So when I started working on the talk I actually asked myself “What do people really mean, when they say AI?”; it turns out that a lot of the time they’re actually talking ML. There are a lot of other questions that need to be raised (if not answered) – the difference between weak AI and strong AI, the concept of embodiment, the way in which some things which we think of as hard (e.g. chess) turned out to be quite easy, and some things we thought would be easy (e.g. vision) turned out to be quite hard. Hopefully in the talk I covered enough of this stuff to introduce the questions.
I decided that for a tech talk there needed to be a bit of tech in it too though, which is why I spent the second half breaking down a bit what we mean by machine learning, and introducing some different subtypes of machine learning. I expect that if you work in the area there’s nothing much new in the talk, but hopefully it gives an overview, and also gives enough depth for people to learn something from it.
so what about the cute robots?
I wanted a visual example for my slides on ML and particularly classification, so I created a robot image, then edited it about a bit to get 16 different variants (different buttons, different numbers of legs, aerials, arm positions). I then wrote a short program to switch the colours around so I got twice as many (just switching the blue and the red channels gives some cyan robots and some yellow robots).
If you want to use them in talks or whatever, feel free. You can get all 32 of the robots, here, along with the python program that switches colours and the gimp file (.xcf) if you want to edit them yourself.