A Gemma model helped discover a new potential cancer therapy pathway

I think it's important that people know this. Despite what the other AI companies claim or put out as occasional PR, they have absolutely no real interest (through internal work or funding external researchers) in using AI to benefit science and humanity as a whole. They just want their digital god. As such, there is simply not enough funding for AI research with scientific applications. Consequently, many people in machine learning are not working in scientific applications, even though they really want to.

Someone has to do it. Big pharma has a lot of money and if AI can reduce their costs in human resources, they will be willing to put some of their profits aside to further the research in AI space.

Money wells are drying up across the trch Industry and ai companies will have to look for funds from adjacent industries like biotech and medicine.

I think I believe OpenAI's claim that they have better models that are too expensive to serve up to people.

I think Google have only trained what they feel they need, and not a megamodel, but I can't justify this view other as some kind of general feeling. They obviously know enough to make excellent models though, so I doubt they're behind in any meaningful sense.

When they do, someone like OpenAI comes along and runs the VC enshittification playbook on it.

> What made this prediction so exciting was that it was a novel idea. Although CK2 has been implicated in many cellular functions, including as a modulator of the immune system, inhibiting CK2 via silmitasertib has not been reported in the literature to explicitly enhance MHC-I expression or antigen presentation. This highlights that the model was generating a new, testable hypothesis, and not just repeating known facts.

This just in "excel helped discover a potential cancer cure using pitvottables"

Reading comments around AI is always fun

> It's not like the model has devised new knowledge. Kind of a low hanging fruit.

Just keep moving goalposts.

If someone discovers anything, it does not change anything if someone else could have discovered it theoretically as well?

It is awesome.

But what I’ll say is, ideally they would demonstrate whether this model can perform any better than simple linear models for predicting gene expression interactions.

We’ve seen that some of the single cell “foundation” models aren’t actually the best at in silico perturbation modeling. Simple linear models can outperform them.

So this article makes me wonder: if we take this dataset they’ve acquired, and run very standard single cell RNA seq analyses (including pathway analyses), would this published association pop out?

My guess is that yes… it would. You’d just need the right scientist, right computational biologist, and right question.

However, I don’t say this to discredit the work in TFA. We are still in the early days of scSeq foundation models, and I am excited about their potential.

Cellular level computational simulation existed a very long time and it's more impressive by the day because of large collections of experimental datasets available.

However to infer or predict celular acitivities you need a ton of domain knowledge and experties about particular cell types, biological processes and specific environments. Typically the successful ones are human curated and validated (e.g large interaction networks based on literature).

In cancer it's even more unpredictable because of the lack of good (experimental) models, in-vivo or in-vitro, representing what actually happens the clinically and biologically underneath. Given the single cell resolution, its uncertainty will also amplify because of how heterogeneous inter- and intra- tumours are.

Having said that, a foundation model is definitely the future for futher development. But with all of these things, the bigger the model, the harder the validation process.

If you can have porn without the human trafficking and exploitation associated with the porn industry, that's a big win too

Their research is pivoting to STDs

Both is equally important, just in another dimension.

Well you might be pleased to know that there are large safety teams working at all frontier model companies worried about the same thing! You could even apply if you have related skills.

Seems like no matter how positive the headline about the technology is, there is invariably someone in the comments pointing out a worst case hypothetical. Is there a name for this phenomenon?

We’ve just had a virus - specifically engineered to be highly infectious for humans - escaping the lab (which was running very lax safety level - BSL2 instead of required BSL4) and killing millions and shutting down half the globe. So I’m wondering what safeguards and prevention you’re talking about :)