One of the things I’ve enjoyed least about my OU Maths journey so far has been group theory. I ploughed through whole swathes of M208 applying the techniques and not really seeing the relevance1 I found group theory and the proofs related to it tedious. Mainly because I was proving something that was “obvious”. However, I’ve always had a healthy acceptance of partial learnings – knowing that if I was being taught a technique then there was a reason for it. Two years later and that reason finally hit me. Continue reading M337: Group theory becomes relevant
I love choose your own adventure books. I read The Warlock of Firetop Mountain when it was first released and then pretty much every single Fighting Fantasy book released after it1. I also credit one of these books with improving my French reading and vocabulary after finding “La Malediction du Pharaon” in a charity shop2. One of the themes that run through all these books is your statistics: stamina, skill, and luck3. As you use these abilities they deplete. Use them too much and you will likely come to a sticky end in the books.
Real life is pretty similar, both mentally and physically. Continue reading Determination and Stamina: valuable stats but they’re not infinite
I gave myself a birthday present again this year, by registering for another 60 points worth of Open University maths modules. I’d put it off for quite a while as I couldn’t decide which level three modules I wanted to do most and also in which order. The only fixed option was “The quantum word” which was only available once I’d completed1 60 points worth. This left me with a choice of 3 modules from 4 other interesting options. Sadly, I discovered (thanks to a comment) that the pure maths module I intended to do was a 60 point module, meaning I either had to lose that from my choice or two of the modules I was really wanting to do. In the end, pure mathematics lost out and I’m committed to four 30 point modules. Continue reading OU level 3: Complex numbers and stochastic dynamics
One of the modules I’m considering for level 3 of my OU maths degree is the quantum world. I recall my A-Level chemistry teacher trying to explain that electrons weren’t solid balls orbiting an atom but rather a probability cloud of where the electron could be. I read a lot of popular science books at the time but found that there was a huge gap between the very high level “here’s a thing, it’s really cool” and “here’s a thing and after 3 pages we’ll dive into complex theory that you’ve never encountered”. Hence when I heard that a new introductory book on the principles of quantum theory had been written specifically for inquisitive young people to help them decide if they wanted to learn the maths needed to take it further, I thought “this sounds like a book 16 year old me would have wanted to read” and I bought a copy for the kindle. Continue reading Review: Q is for Quantum by Terry Rudolph
Throughout my academic career one thing that was repeatedly enforced was that if you were claiming something to be true in a paper, you needed to show results to prove it or cite a credible source that had those results. It took a lot of effort in those pre-Google Scholar and pre-Arxiv days1. Reading the journals, being aware of retractions and clarifications and building the evidence to support your own work took time2. Writing up my thesis was painful solely because of finding the right references for things that were “known”. I had several excellent reviewers who sent me back copies of my thesis with “citation needed” where I’d stated things as facts without a reference. My tutor at Oxford was very clear on this: without a citation, it’s your opinion not a fact. Continue reading Citation Needed – without it you have opinion not facts
While there may be disagreements on whether AI is something to worry about or not, there is general agreement that it will change the workforce. What is a potential concern is how quickly these changes will appear. Anyone who has been watching Inside the Factory1 can see how few people are needed on production lines that are largely automated: a single person with the title “manager” whose team consists entirely of robots. It wasn’t too long ago that these factories would have been full of manual labour.
The nature of our workforce has changed. It’s been changing constantly – the AI revolution is no different in that respect. We just need to be aware of the speed and scale of potential change and ensure that we are giving everyone the opportunity to be skilled in the roles that will form part of our future. There is an inevitability about this. Just as globalisation made it easy for companies to outsource work to cheaper locations (and even easier with micro contract sites) AI will make it cheaper and easier for companies to do tasks so it will be adopted. Tasks that aren’t interesting enough or wide market enough or even too difficult right now to be automated will still need human workers. Everything else will slowly be lost “to the robots”. Continue reading Is a Robot tax on companies using AI a way of protecting the workforce?
While I like to kid myself that maybe I’m only a quarter or third of the way through my life, statistics suggest that I’m now in the second half and my future holds a gradual decline to the grave. I’m not afraid of my age, it’s just a number1. I certainly don’t feel it. My father recently said that he doesn’t feel his age either and is sometimes surprised to see an old man staring back at him from the mirror.
As an atheist, death terrifies me. My own and that of those I love. I don’t have the easy comfort blanket of an afterlife and mourn the loss of everything an individual was when they cease to be. Continue reading Chatbot immortality
You may have heard in the news that Girlguiding are looking to inspire girls and young women into STEM by introducing new interest badges. This is, without a doubt, fantastic news. The interest badge system has been a backbone of both Scouting and Guiding since they began as a way of encouraging young people to try new things. So, helping Guides explore these skills with new badges is a great step forward.
Or is it? The BBC article pokes gentle fun at the old-fashioned image of Guiding with the journalist’s memories of badges for tying knots and table-laying: “Fast forward some 25 years and it’s clear much has changed”1 Continue reading Girlguiding STEM badges – great news, but a generation late in the reporting
Artificial intelligence has progressed immensely in the past decade with the fantastic open source nature of the community. However there are relatively few people, even in the research areas, that understand the history of the field from both the computational and biological standpoints. Standing on the shoulders of giants is a great way to step forward, but can you truly innovate without understanding the fundamentals?
I go to a lot of conferences and I’ve noticed a subtle change in the past few years. Solutions that are being spoken about now don’t appear to be as far forward as some of those presented a couple of years ago. This may be subjective, but the more I speak to people about my own background in biochemically accurate computational neuron models, the more interest it sparks. Our current deep learning model neurons are barely scratching the surface of what biological neurons can do. Is it any wonder that models need complexity and are limited in their scope? Continue reading Biologically Inspired Artificial Intelligence
I chaired a breakfast meeting for Women in Data Science recently, and one of the topics for discussion was how to retain talent. While demand is outstripping supply and the market is going crazy, it’s enough of a minefield finding good people in the first place.
Add to this that even after you’ve made an offer to someone, recruiters will be contacting them regularly to try to tempt them away to other roles. It’s impossible to prevent this. I’m a big believer in not playing games with recruitment – I know what I can afford and won’t get into a bidding war. If I’m paying a fair salary and they go elsewhere for money, then they are more likely to jump when a recruiter calls regardless of how well you incentivise them. This isn’t a big company or small company thing, if you want to keep hold of your team after you’ve done the very hard job of hiring them then you need to understand what motivates them and either make sure that you continue to provide those needs or plan to be hiring again in the next 12-24 months. Continue reading Incentivising data scientists