Category Archives: Commentary

Conference Summary: MGMS Adaptive Immune Receptors Meeting 2024

On 5th April 2024, over 60 researchers braved the train strikes and gusty weather to gather at Lady Margaret Hall in Oxford and engage in a day full of scientific talks, posters and discussions on the topic of adaptive immune receptor (AIR) analysis!

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How can FemTech help close the gender health gap?

An excellent previous blog post from Sarah [1] describes the gender data gap and touches on the fact that women experience poorer healthcare outcomes. This arises from, amongst other things, the historical exclusion of women from clinical trials and this idea of the ‘male default’, where, for example, drug dosages and diagnostic thresholds are benchmarked against men, or even surgical instruments are designed to fit male hands [2]. I thought I would follow up on Sarah’s blog post and discuss how FemTech can help to close this gender health gap.

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Inverse Vaccines

One of the nice things about OPIG, is that you can talk about something which is outside of your wheelhouse without feeling that the specialists in the group are going to eat your lunch. Last week, I gave an overview of the Hubbell group‘s Nature paper Synthetically glycosylated antigens for the antigen-specific suppression of established immune responses. I am not an immunologist by any stretch of the imagination, but sometimes you come across a piece of really interesting science and just want to say to people: Have you seen this, look at this, it’s really clever!

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An Open-Source CUDA for AMD GPUs – ZLUDA

Lots of work has been put into making AMD designed GPUs to work nicely with GPU accelerated frameworks like PyTorch. Despite this, getting performant code on non-NVIDIA graphics cards can be challenging for both users and developers. Even in the case where the developer has appropriately optimised for each platform there are often gaps in performance where, at the driver-level, instructions to the GPU may not be optimised fully. This is because software developed using CUDA can benefit from optimisations like operation-fusing without having to specify in many cases.

This may not be much of a concern for most researchers as we simply use what is available to us. Most of the time this is usually NVIDIA GPUs and there is hardly a choice to it. NVIDIA is aware of this and prices their products accordingly. Part of the problem is that system designers just dont have an incentive to build AMD platfroms other than for highly specialised machines.

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Fail fast

While scrolling through my Instagram reels feed, I came across a reel of Jensen Huang, NVIDIA’s CEO, talking about the need to fail fast, which motivated me to write a post. ‘Fail fast’ is a recent piece of advice I have been hearing since I embarked on my PhD; fail fast on the research directions that we plan to pursue so that we can understand the difficulties and limitations of the research problems and methods used which will in turn give us more time to finetune our problem and develop more nuanced approaches. Since childhood, most of us have been taught that failures eventually lead to success and that persevering towards success is critical. However, one thing that I could not come to terms with is the narrative of several failures ‘magically’ leading to success. If you were destined to be successful, why would you even fail? And also, for every failure-to-success story we hear, there are many other stories of failure that we don’t.

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250 Trips on the Oxford Tube: what I’ve learnt

The Oxford Tube is a bus service that shuttles people between Oxford and London taking approximately 1 hour and 30 minutes. I have now taken the bus over 250 times which is approximately 375 hours or a fortnight of my life.

In this time spent on the bus, I have discovered some tips and tricks that make the journey ever so slightly more bearable. I shall share them so that others can optimise their experience. Enjoy!

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On National AI strategies


Recently, I have become quite interested in how countries have been shaping their national AI strategies or frameworks. Since the launch of ChatGPT, several concerns have been raised about AI safety and how such groundbreaking AI technologies could augment or adversely affect our daily lives. To address the public’s concerns and set standards and practices for AI development, some countries have recently released their national AI frameworks. As a budding academic researcher in this space who is keen to make AI more useful for medicine and healthcare, there are two key aspects from the few frameworks I have looked at (specifically the US, UK and Singapore) that are of interest to me, namely, the multi-stakeholder approach and focus on AI education which I will delve further into in this post.

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OPIG: A decade of Scientific Shenanigans. What’s changed?

2013 was a big year: Andy Murray clinched the Wimbledon title, NASA’s Curiosity Rover discovered water-bearing minerals on Mars, and ‘twerk’ and ‘selfie’ made their way into the dictionary, something equally significant happened—the birth of BLOPIG.com. Intrigued by how the group has changed over the last decade, I started on a journey to unearth the some of the publications from then till now. Questioning their focus, methods, and evolution of the groups’ research over the past decade. This blog post is what I found.

While delving into each publication of the past decade genuinely seemed like an interesting idea, the imminent threat to my PhD progress forced me to adopt the most 2023-appropriate approach: outsourcing the task to AI. After collecting abstracts from all the group’s papers, I enlisted the help of everyone’s’ favourite hallucinator to summarise the works and (hopefully) highlight the shifts in their research.

So after a relatively long, sequence of prompts, this is (apparently) what we do?

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Lucubration or Gaslighting?​

Or: The best lies have a nugget of truth in them.​

Lucubration – The action or occupation of intensive study originally by candle or lamplight.

Gaslighting – Psychological abuse in which a person or group causes someone to question their own sanity, memories, or perception.

I was recently having a play with Google Bard. Bard, unlike ChatGPT has access to live data. It also undergoes live feedback and quality control. I was hoping to see if it would find me any journals with articles on prion research which I’d previously overlooked.

Me: Please show me some recent articles about prion research.
(Because always be polite to our AI overlords, they’ll remember!)

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