Ben Hall

@hallben.bsky.social

Professor in computational cancer biology at UCL interested in disease, mutations, and aging. Funded by CRUK, MRC and Royal Society. Personal account for science, code, music, photography! “Tired is the new awake”

My impression is that AI coding is on a "pick two of three" triangle: scope, ship speed, and correctness. Small tools are (speed + correctness) fast prototypes are (speed + scope) and big projects are (scope + correctness). Every project that tries to be all three degrades to "fast prototype."

From Terry Tao’s ICM lecture. While there are additional arrows later that aren’t shown here, verification informs exposition. If an AI proof is autoformalized before it is understood and reworked by a human, the result will be more conceptually brittle even if evidently correct. /1

Bild

A thoughtful piece on what it means to be a postdoc: *independence is about moving forward without all answers *use science conversations to make sense of uncertainty, beyond presenting results *a postdoc is as much about learning to think & adapt as it is about generating data & publishing

eLife@elife.bsky.social · 2d ago

A postdoc comes with challenges and uncertainties different from those of a PhD. In this ecrLife blog Vartika Sharma shares how managing expectations and building a community are key skills that can help us navigate the new uncertainties of a postdoc.

Using LLMs should allow us to think bigger, harder to grasp, difficult to execute, longer to develop, ideas. That idea that’s been in you brain since forever but you hadn’t had the time because you had to retool and what not. Trust yourself. Go for that shit. Now is the fucking time.

Clément Canonne@ccanonne.github.io · 4d ago

"We're all worried," as what it means to do research (in my field, Theoretical CS) seems to be shifting, and shifting fast. What to do? Senior researchers must lead by example, knowing that not everything will pan out. What I'm suggesting below may not work everywhere, but here's my own advice: 1/

One thing that I no longer hear much talk about: Whether AI would help with formal verification go mainstream. Formally verifying programs is pretty hard and is a niche skillset! Doesn't seem like AI has made a difference in that field. Worth asking: why?

9/ Looking back, the reviewer was not the biggest problem. Reviewers can be wrong. Reviewers can be unreasonable. Reviewers can be openly hostile. That is precisely why editors exist. The problem begins when inappropriate behaviour is acknowledged, action is promised, and then nothing changes.

we constantly rely on unreliable tools (some of them in meat suits and with hair) by adding compensating controls around their actions so the outputs are bounded and, while not deterministic, predictable in the real world, this is normal. but now *you* have to look at it, and some people hate that

I only take issue with the final quote: “People need to manage the competing dynamics of relying on generative AI and staying mindfully vigilant.”

Simply put, there is no way in which one can rely on an unreliable tool, especially when it robs us of the very ability to recognize when it's wrong.
I. M. Noone@ianmnoone.bsky.social · last mo.

I only take issue with the final quote: “People need to manage the competing dynamics of relying on generative AI and staying mindfully vigilant.” Simply put, there is no way in which one can rely on an unreliable tool, especially when it robs us of the very ability to recognize when it's wrong.

We are recruiting! We are seeking a Research Technical Specialist in Mass Spectrometry. The main purpose of this position is to provide general and specialist research support including leading on method development in relation to Mass Spectrometry.

UCL – University College London

UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).

ucl.ac.uk

Continuing the marathon clearout of my parents house. Came across this interesting cutting from a 1993 edition of the Radio Times about a programme called Two Seconds to Midnight. It predicts that in 2043 electricity will be generated by renewables and that we will use TVs for our shopping.

An image from the Radio Times from 1993 depicting a family in 2043 and speculating about their lifestyle.

'On average the raw lifetime earnings gap for those aged 37 in 2022 who went to university, and those who could have but did not, was £290,000. And this includes a 3.5 per cent discount rate (applying Treasury Green Book rules) that lowers the value of earnings in later life'. 1/3

Higher education study still makes financial sense for most

DK examines what the Institute for Fiscal Studies has done with a few extra years of data on graduate earnings, and on a new approach to comparing graduates to their non-graduate peers

wonkhe.com

Web-based modeling platforms can enhance collaboration between modelers and experimentalists during early model development. This Community Page by Marvin van Aalst, Alienor Lahlou &co provides guiding principles on how to build agile interactive #modeling tools. 🧪#AcademicSky bit.ly/4ahZ7Nm

The schematic contrasts a classical workflow with a web-enabled collaborative workflow. In the classical setting, experiments generate data that inform modeling and analysis, but interaction between experimentalists and theoreticians occurs through a separate, untracked layer (e.g., files, emails, code repositories), typically late in the process. Introducing a web-based interaction layer integrates models, parametric runs, and fits into a shared space accessible to both communities. This shared layer allows direct access to models, interactive parameter exploration, data upload, and tracking of experimental and modeling runs, thereby placing experimental feedback inside the iterative modeling loop rather than outside it. Interactive exploration enables earlier scrutiny of assumptions, faster feedback, and tighter coupling between experimentation and model refinement within interdisciplinary consortia.

I'm attending a digital humanities event in Montreal. There was a keynote on AI and something about the talk made me wonder if it had been written by Claude. I said as much in the Q&A. As I posed the question, the speaker shifted, looking slightly uncomfortable. What he said next shocked the room +