Adrian Liston

@LabListon

🇦🇺🇧🇪🇬🇧👨‍🔬🌈 Professor of Pathology & Head of Immunology at @Cambridge_Uni. Fellow & Welfare Tutor at @Catz_Cambridge. Founder & CSO at Aila Biotech.

Cambridge, England listonlab.uk Joined December 2018

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Adrian Liston @LabListon Aug 27

Two post-doc positions available in our lab!

It is a supportive environment and one which boosts careers! Historically, of our ~30 post-docs 27% have gone on to tenure-track positions, 27% did another post-doc, and 42% have gone on to positions in biotech or pharma.

Adrian Liston @LabListon 3d

RemindMe! 10 years not to be disappointed that bio-AI companies didn't deliver, and just sucked resources out of the system, because we would have shifted the goal posts!

Remember, the important thing isn't whether diseases are cured or not, it is whether our IPO raises $$$

Jake Wintermute 🧬/acc Verified account @SynBio1 3d

I don't think the interesting question is "can we cure all diseases in 10 years?" because we can't

The interesting question is "10 years from now, will Bio-AI still be accelerating so quickly that failed predictions about today's tech don't matter?"

Lots of people are pointing out that you pay a price for over-hyping a technology. Historically, this is true. The peak of inflated expectations is followed by the trough of disillusionment.

But that model applies to a stable technology: CRISPR or RNAi, for example. These were powerful tools with a wide, but defined, scope. The CRISPR of 2026 would be recognizable to a CRISPR researcher in 2016.

AI does not seem to be like that. AI accelerates. The AI tooling of 2036 won't look anything like the tooling today. It will be more powerful to a degree that is hard for me to comprehend.

By the time Dario's predictions about curing all diseases are false, AI will be in effect, a new technology. There will be no time to be disappointed.

I'm not sure I'm fully convinced by the above logic. But I assume some version of it is behind the choice of Dario and other neolab leaders to let rip on hype. The acceleration of AI means they don't expect to pay a price for being wrong.
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Adrian Liston @LabListon Nov 3

Wearing the R on your sleeve

Headquarters Verified account @HQNewsNow Nov 2

Ken Paxton: The criticism has been that I let a child predator out after 1 day. Well guess what? They served 60 days.

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Adrian Liston @LabListon Oct 25

Biology has literally never worked like this.

Mira Verified account @_Mira___Mira_ Oct 25

If you had an exponential amount of compute you could solve simulate biology exactly and wouldn't need to run any experiments.

Some of you will think "of course, but that's an unrealistic assumption" and others will think "no, you need experiments even with that much compute. That's just How It's Done".

You would of course need evaluations once you have a solution, but you don't in principle need experiments to find it: Experiments are a way to save compute, dating from a time when it was much more expensive.

And I think the presentation is exponential but real systems aren't irreducibly exponential. AlphaFold worked, after all.
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Adrian Liston @LabListon Oct 20

Love this. 5+10 is a good way to do it, too

nature Verified account @Nature Oct 20

China has selected its first group of young researchers to receive funding for up to 15 years, in one of the longest research grants on offer to scientists globally

go.nature.com/4z4Q3pw
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