Jyunmi

So first, this comes as a preprint.

It's not a fully peer-reviewed paper yet.

We've talked in the past how papers coming in from archive and things like that are not peer-reviewed, and then they're changing their CS policy so that only peer-reviewed papers come in because there's this huge influx of AI content

processed, or AI in the process of making and reviewing those papers.

So just highlight that this is a preprint.

That means it hasn't been peer-reviewed.

All right.

And second, binding is only step one in making any medicine.

So Boltzgen won't tell you if it's safe on animals or humans, how long or how it will survive in the body.

And can they make it cheaply and reliable?

So this is just that first stage.

So what that means is still need human expertise, animal studies, clinical trials and all of the normal steps.

Third, the model has a training data bias.

In some tests, it kept spitting out designs that look like a very common protein family.

Basically, it was leaning on its comfort zone.

And the team had to rebalance the data to reduce that effect.

But this kind of bias never disappears completely.

Fourth, the experiments are impressive but still limited.

They were done in collaborating labs that know the team and the tools.

We've not seen a random lab on the other side of the world download the code and run their own pipeline for their own targets and report similar successes.