Just reading this, the inevitable scaremongering about biological weapons comes up.

Since most of us here are devs, we understand that software engineering capabilities can be used for good or bad - mostly good, in practice.

I think this should not be different for biology.

I would like to reach out and talk to biologists - do you find these models to be useful and capable? Can it save you time the way a highly capable colleague would?

Do you think these models will lead to similar discoveries and improvements as they did in math and CS?

Honestly the focus on gloom and doom does not sit well with me. I would love to read about some pharmaceutical researcher gushing about how they cut the time to market - for real - with these models by 90% on a new cancer treatment.

But as this stands, the usage of biology as merely a scaremongering vehicle makes me think this is more about picking a scary technical subject the likely audience of this doc is not familiar with, Gell-Mann style.

IF these models are not that capable in this regard (which I suspect), this fearmongering approach will likely lead to never developing these capabilities to an useful degree, meaning life sciences won't benefit from this as much as it could.

I feel somebody better qualified should write a comprehensive review of how these models can be used in biology. In the meantime, here are my two cents:

- the models help to retrieve information faster, but one must be careful with hallucinations.

- they don't circumvent the need for a well-equipped lab.

- in the same way, they are generally capable but until we get the robots and a more reliable interface between model and real world, one needs human feet (and hands) in the lab.

Where I hope these models will revolutionize things is in software development for biology. If one could go two levels up in the complexity and utility ladder for simulation and flow orchestration, many good things would come from it. Here is an oversimplified example of a prompt: "use all published information about the workings of the EBV virus and human cells, and create a compartimentalized model of biochemical interactions in cells expressing latency III in the NES cancer of this patient. Then use that code to simulate different therapy regimes. Ground your simulations with the results of these marker tests." There would be a zillion more steps to create an actual personalized therapy but a well-grounded LLM could help in most them. Also, cancer treatment could get an immediate boost even without new drugs by simply offloading work from overworked (and often terminally depressed) oncologists.

> I would like to reach out and talk to biologists - do you find these models to be useful and capable? Can it save you time the way a highly capable colleague would?

Well, I would say they have done precisely that in evaluating the model, no? For example section 2.2.5.1:

>Uplift and feasibility results

>The median expert assessed the model as a force-multiplier that saves meaningful time (uplift level 2 of 4), with only two biology experts rating it comparable to consulting a knowledgeable specialist (level 3). No expert assigned the highest rating. Most experts were able to iterate with the model toward a plan they judged as having only narrow gaps, but feasibility scores reflected that substantial outside expertise remained necessary to close them.

Other similar examples also in the system card

Dario (the founder) has a phd in biophysics, so I assume that’s why they mention biological weapons so much - it’s probably one of the things he fears the most?

> Just reading this, the inevitable scaremongering about biological weapons comes up.

It's very easy to learn more about this if it's seriously a question you have.

I don't quite follow why you think that you are so much more thoughtful than Anthropic/OpenAI/Google such that you agree that LLMs can't autonomously create very bad things but—in this area that is not your domain of expertise—you disagree and insist that LLMs cannot create damaging things autonomously in biology.

I will be charitable and reframe your question for you: is outputting a sequence of tokens, let's call them characters, by LLM dangerous? Clearly not, we have to figure out what interpreter is being used, download runtimes etc.

Is outputting a sequence of tokens, let's call them DNA bases, by LLM dangerous? What if we call them RNA bases? Amino acids? What if we're able to send our token output to a machine that automatically synthesizes the relevant molecules?

It is not scaremongering.

Surely more than 10% of the time consumed by going to market with a cancer treatment is giving it to living organisms and waiting to see what happens, which can't be made any faster with software. That's not to say speedups can't happen, but 90% can't happen.

Not that that justifies doom and gloom, but there is a pretty inescapable assymetry here between weaponry and medicine. You can manufacture and blast every conceivable candidate weapon molecule at a target population since you're inherently breaking the law anyway and don't lose much if nothing you try actually works.

Though I still wonder how much of this worry is sci-fi scenarios imagined by the underinformed. I'm not an expert by any means, but surely there are plenty of biochemical weapons already known that can achieve enormous rates of mass death pleasing to even the most ambitious terrorist. The bottleneck to deployment isn't discovering new weapons so much as manufacturing them without being caught or accidentally killing yourself first.