Maths to 18? Is this the way to make people data literate?

Rishi Sunak, the UK Prime Minister, has caused some waves in the past few days with one of his personal pledges that young people should have to study maths until 18. As he said himself in his speech:

“Every opportunity I’ve had in life began with the education I was so fortunate to receive and it’s the single most important reason why I came into politics: to give every child the highest possible standard of education.”

Rishi Sunak, January 2023

While on the surface this may seem like a great idea, critics have been keen to pull apart all the ways that compulsory maths education is either a bad thing (from Simon Pegg’s passionate rant about lack of focus on the arts, many people saying how much they hated maths at school) or simply won’t work (lack of qualified teachers or investment in schools, or even children going to school hungry). All of these criticisms have merit and I’m a big believer in ideas being criticised and pulled apart to get to something that works rather than biased idealism.

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Walking Ultra Marathons

Last year, I walked the Cancer Research Shine Night Walk full Marathon around London and raised just under £1000 in sponsorship for Cancer Research UK. Never one to do less than I’ve done previously, in 2022 I decided that one marathon wasn’t enough and to do justice to raising funds for this amazing charity I needed to up my game. Then I discovered ultra marathons!

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Ember smart mug – is it worth it? Review

Grey ember mug full of tea on a desk

I am notoriously difficult to buy gifts for, and it’s something that my husband mentions regularly as I don’t really need anything, and I have all the computing, gaming and Lego I want1. This year he approached my birthday grinning that he had found me the prefect present… and he really had.

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Corsair Keyboard Restoration

A few weeks ago, a friend of mine was asking about which was the best gaming keyboard to buy as theirs was “broken”. I knew that they had a pretty decent Corsair gaming keyboard and that they hadn’t had it all that long (maybe less than a year). The scientist in me immediately asked “In what way is it broken?”.

“The keys are sticking and often don’t register. I’m going to throw it away.”

Always one unable to resist a challenge and prevent something ending up in landfill if I can help, I offered to take a look to see if I could fix it. I wasn’t surprised at the state of it when it arrived. My friend often ends up eating and drinking at their desk during both work and gaming, and most people don’t clean their tech regularly, if at all.

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Marathon Musings

A huge congratulations to everyone who ran the London Marathon yesterday. I, like many others, watched from the sofa as forty thousand ran the streets of London, raising money for some incredible causes. I want to shout out my friend Rob Wiles, who was raising money for Children with Cancer UK. As the TV coverage reminded me, there were even more people running “virtual” marathons around the world, for those who couldn’t (or chose not to) attend in person. This was something that Tim Peake set a precedent for when he ran the marathon from the International Space Station back in 2016 and I wonder if this will continue as an option should everything finally return to normal…

For once, while I was watching from my sofa, I felt enthusiastic empathy rather than jealousy at their fitness – my legs were only just back to normal after my own marathon the weekend before.

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Explainable AI

Last week, I attended the Re Work Explainable AI mini summit. I am really loving so many great speakers being accessible online, particularly in a three to four hour format, which makes it easy to fit in around work commitments better than an in person summit – had it not been online I would have missed out on some great speakers.

Explainability is something I’ve been really focussing on recently. While it’s always been important, my frustration has been in research focussing on tools for machine learning engineers and not on clear explanations for the general public – the very people using, and being affected by, the systems we build. I was keen to attend this summit in particular as a refresh of where we were in terms of current best practise.

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Andrew Ng Fireside Chat with the RSS Data Science Section

On the 10th February the Royal Statistical Society Data Science Section were delighted to host a fireside chat with Andrew Ng, who shouldn’t need any introduction!

It was a great talk and one of my fellow committee members, James Weatherall, has already written a great blog post summarising the event. If you weren’t able to attend, the full session is now available on the RSS YouTube channel.

If you have any speaker suggestions that you’d like to see, please let me, or any of the committee, know!

Journal29 puzzle book – review

Original 1985 cover of Escape from Blood Castle Puzzle book, showing a red haired boy on a rack.
The original 1985 cover.

It will come as no surprise to anyone who has read any of my other posts that I loved puzzle books as child. I started with the Usbourne puzzle adventure series – cartoon books with clues on each page either in the pictures or what was said. I think my favourite was “Escape from Blood Castle“, which I got as a Christmas present in 1985. It was a perfect mix of slightly creepy and logical deduction that really appealed to me and I loved having new books from this series as they were published.

I quickly moved on to more text based mysteries – particularly the Hawkeye Collins and Amy Adams sleuth series. These were typical kids solve the mystery books. Unlike the Usbourne puzzle solvers, each mystery was stand alone and the answers were in the back of the book in mirror writing. At that age I didn’t have a small pocket mirror so taught myself how to read backwards to check my answers1. After that, it was whatever puzzles I could get may hands on.

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Efficient AI

One of the great benefits of lockdown for me is the time I have to catch up on some of the papers released that are not directly related to my day to day work. In the past week I’ve been catching up on some of the more general outputs from NeurIPS 2020. One of the papers that really caught my eye was “Ultra-Low Precision 4-bit Training of Deep Neural Networks” by Xiao Sun et al.

It’s no doubt that AI in its current form takes a lot of energy. You only have to look at some of the estimated costs of GPT-3 to see how the trend is pushing for larger, more complex models with larger, more complex hardware to get state of the art results. These AI super-models take a tremendous amount of power to train, with costs out of the reach of individuals and most businesses. AI edge computing has been looking at moving on going training into smaller models on edge devices, but to get the accuracy and the speed, the default option is expensive dedicated hardware and more memory. Is there another way?

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