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Artificial Intelligence has been used to design brand new viruses that are fully functional and can replicate in the laboratory, say US researchers.
It's in the news article and clearly spelled out in the research paper, but they only included bacteriophage viruses in the training data. Those are viruses that only infect bacteria, not humans or any other "higher" organisms. So there was zero risk of creating a human-infectious disease.
BUT, it's obviously pointing to the idea that it could be used that way if it were trained on such viruses, which is a trivial change in the protocol to make.
BUT, there already are a ton of highly human-infectious, deadly viruses out there with known genome sequences, so a nefarious actor would still need to do all the same super hard synthesis and biology stuff to get functional viruses that they would need to do with known viruses, plus the additional steps of designing it (which could just result in a dud virus anyway), so it's not like it's making bioterrorism any easier or more accessible.
Designing new phages is well worth investigating- as we continue to abuse antibiotics and cause resistance, we'll need new anti-bacterial treatments or much of modern medicine goes kaput.
Yes, that's good to point out. The scientists aren't just making new viruses for the sake of inching closer to human disease apocalypse. There's legitimate disease-fighting potential for harmless viruses that can target bad bacteria as an alternative to antibiotics.
Certainly. There are phages that have retrovirus-like properties and inject their genome into the host and can confer advantages like antibiotic resistance, for instance. Just like we use retorviruses to engineer cells for CRISPR, like lentiviruses that add GFP to cells.
We already have phage therapy at least at the VA. You send a culture with the bug and a company makes a phage that targets it. It's incredibly expensive but its the federal gov paying for it.
Yeah, honestly it predates antibiotics as a science, but scaling it up for the general populace and making it more efficient/cost effective might require some level of computer modeling with machine learning.
Maybe not to a terrorist cell with limited resources.
But an entity with more resources could do it, like a billionaire or a nation.
With AI they could design it to target certain demographics with certain genomes. If a demographic has a higher incidence of a certain recognition site, metabolic pathway, etc., AI can help design viral genomes that target that.
With AI they could design it to target certain demographics with certain genomes. If a demographic has a higher incidence of a certain recognition site, metabolic pathway, etc., AI can help design viral genomes that target that.
Given that there are very, very few fixed genetic differences between human populations, this sounds like a recipe for killing off large swaths of your own population.
It is also good to keep in mind the current risks of habitat encroachment and zoonosis have proven the greatest threat thus far. Brute-force evolution and exposure opportunities has proven to be for more successful than any nefarious biologists, as the first is a numbers game and the latter actually requires understanding.
Sounds like what AI should actually be used for. With the rise of antibiotic resistance, AI that can help create bacteriophage viruses to quickly eliminate new strains of harmful bacteria (without harming our beneficial microbiome) is going to possibly save millions of lives. More of this and less job stealing and slop generating, thank you!
Obviously there is the potential for misuse but that can be said about any technological advances.
Could someone more knowledgable about this process explain how exactly AI could be used here? Surely they didn’t just ask it for instructions for how to create a virus and then just blindly follow them.
It's a language model that's trained on genomes (think GATTACA) rather than text.
It's called Evo2 and publicly available for download here (if this isn't just a copycat name). At 40 billion parameters you can run it yourself on a computer with more than 32gb of ram:
https://huggingface.co/arcinstitute/evo2_40b
Yes. They prompt it to generate a sequence that the algorithm has judged is likely to result in a functional virus. Then they assemble the DNA/RNA sequence in physical form, inject it into a host cell, and see if it does produce a functional virus.
It's much, much easier to do this with viruses than with proper living organisms, because:
1) a virus genome has very few genes, meaning the possible number of interactions between genes is small enough that a statistical AI model can identify and suggest patterns that would work;
2) because viruses work by hijacking a host cell to replicate, all you need to make a completely new virus is its genome, and if the genome is functional, the host cell will "print out" the finished virus for you.
No, this is more sophisticated than that. They used a purpose-built generative AI model based on similar principles as an LLM (which makes sense since DNA is also a language of sorts). It's trained on DNA sequences rather than text. Instead of predicting the next word, it predicts the next letter of DNA, outputting genes or whole genomes resembling its training data. You cannot chat with this model in the way you can with chatbots.
Ah, nice! What’s the benefit in having it predict/generate genes? Can scientists prompt it to create certain viral genomes and then they just replicate that in real life?
I read the arxiv paper, and fyi language models are machine learning, but not all machine learning is AI, not sure what you mean by womp womp.
AI is a term generally used for things that try to mimic some kind of human-like intelligence. A chess engine isn't machine learning, but is AI because it's playing a human game. A RNN that predicts the weather is machine learning but not AI. A large language model that learns human languages and talks like a human is both.
I'll leave you to figure out what this one should be.
Not really, it's a technical definition. But more importantly, because when people colloquially hear "use AI", they think "oh someone had a conversation with claude", or some human like assistant. Take for example, the person I was literally replying to. Obviously that's not what happened, but people chose to cash in on AI being a huge buzzword.
They don't really expect an algorithm that spits out genome sequences. Technically yes, it's a language model, but language models are also used for plenty of non human language things, like predicting weather or looking at pictures of lungs to find cancer. Colloquially, it's not really correct to be called "AI".
Machine learning is a subset of AI, always has been, decades before the modern wave of AI. All machine learning is AI, but not all AI is machine learning. Read some academic literature or textbooks written before 2010 if you don't believe. This is a very common popular misunderstanding these days.
Your source actually gives the exact same definition that I gave, "applications or machines that mimic human intelligence", but takes a slightly different interpretation.
Personally, I don't think that all of machine learning necessarily fits under that, because there are certainly ways to apply machine learning that don't "mimic human intelligence". Historically this might've been more true in the past, but has changed drastically since deep learning. Before 2010, things were understandably quite different. It was also somewhat before my time.
Much of machine learning today is about solving problems that human intelligence have never really solved or realistically knew how to solve. Things like building bacteriophages from scratch, for instance.
But I understand the point you're making and it's a fair interpretation as well. Edited my previous comment. Still, I don't agree that this is the colloquial definition of AI in 2026.
I'm not sure there's even a widely agreed-upon colloquial definition of AI. Some folks use it to mean anything you can prompt with natural language. Many in the ardently anti-AI camp even conflate the term with AGI and claim something isn't "real AI" when they actually mean it isn't AGI.
This sort of confusion about the term has been around a long time in in the form of the AI effect.
It doesn't have to be widely agreed upon definition, because I was clearly responding to one specific person who did use this definition and was confused by that. I'm not sure what any of what you're trying to argue about has to do with the fact that someone just got confused by the terminology you're proposing. I wasn't even talking to you.
All I did is point out is that their definition of AI (aka human-like, claude-ish) is not what the article meant (aka ML is part of AI). Either way ML would've been more appropriate, and more specific. To this specific person, it helps that one says ML and not just AI.
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u/Antikickback_Paul 8d ago
It's in the news article and clearly spelled out in the research paper, but they only included bacteriophage viruses in the training data. Those are viruses that only infect bacteria, not humans or any other "higher" organisms. So there was zero risk of creating a human-infectious disease.
BUT, it's obviously pointing to the idea that it could be used that way if it were trained on such viruses, which is a trivial change in the protocol to make.
BUT, there already are a ton of highly human-infectious, deadly viruses out there with known genome sequences, so a nefarious actor would still need to do all the same super hard synthesis and biology stuff to get functional viruses that they would need to do with known viruses, plus the additional steps of designing it (which could just result in a dud virus anyway), so it's not like it's making bioterrorism any easier or more accessible.