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Experts Alarmed That AI Is Now Producing Functional Viruses [futurism.com]:

AI can now invent working biological viruses.

In real world experiments, a team of Stanford researchers demonstrated that a virus with AI-written DNA could target and kill specific bacteria, they announced in a study [futurism.com] last week. It opened up a world of possibilities where artificial viruses could be used to cure diseases and fight infections.

But experts say it also opened a Pandora’s box. Bad actors could just as easily use AI to crank out novel bioweapons [futurism.com], keeping doctors and governments on the backfoot with the outrageous pace at which these viruses can be designed, warn Tal Feldman, a Yale Law School student who formerly built AI models for the federal government, and Jonathan Feldman, a computer science and biology researcher at Georgia Tech (no word on whether the two are related).

“There is no sugarcoating the risks,” the pair warned in a piecefor the Washington Post [washingtonpost.com]. “We’re nowhere near ready for a world in which artificial intelligence can create a working virus, but we need to be — because that’s the world we’re now living in.”

In the study, the Stanford researchers used an AI model called Evo to invent DNA for a bacteriophage, a virus that infects bacteria. Unlike a general purpose large language model like ChatGPT [futurism.com], which is trained on written language, Evo was exclusively trained on millions of bacteriophage genomes.

They focused on an extensively studied phage called phiX174, which is known to infect strains of the bacteria E. coli. Using the EVO AI model, the team came up with 302 candidate genomes based on phiX174 and put them to the test by using the designs to chemically assemble new viruses.

Sixteen of them worked, infecting and killing the E. coli strains. Some of them were even deadlier than the natural form of the virus.

But “while the Stanford team played it safe, what’s to stop others from using open data on human pathogens to build their own models?” the two Feldmans warned. “If AI collapses the timeline for designing biological weapons, the United States will have to reduce the timeline for responding to them. We can’t stop novel AI-generated threats. The real challenge is to outpace them.”

That means using the same AI tech to design antibodies, antivirals, and vaccines. This work is already being done to some extent [science.org], but the vast amounts of data needed to accelerate such pioneering research “is siloed in private labs, locked up in proprietary datasets or missing entirely.”

“The federal government should make building these high-quality datasets a priority,” the duo opined.

From there, the federal government would need to build the necessary infrastructure to manufacture these AI-designed medicines, since the “private sector cannot justify the expense of building that capacity for emergencies that may never arrive,” they argue.

Finally, the Food and Drug Administration’s sluggish and creaking regulatory framework [axios.com] would need an overhaul. (Perhaps in a monkey’s paw of such an overhaul, the FDA said it’s using AI to speed-run the approval of medications [futurism.com].)

“Needed are new fast-tracking authorities that allow provisional deployment of AI-generated countermeasures and clinical trials, coupled with rigorous monitoring and safety measures,” they said.

The serious risks posed by AI virus generation shouldn’t be taken lightly. Yet, it’s worth noting that the study in question hasn’t made it out of peer review yet and we still don’t have a full picture of how readily someone could replicate the work the scientists did.

But with agencies like the Centers for Disease Control and Prevention being gutted [wired.com], and vaccines [theguardian.com] and other medical interventions being attacked by a health-crank riddled administration [futurism.com], there’s no denying that the country’s medical policy and infrastructure is in a bad place. That said, when you consider that the administration is finding any excuse to rapidly deploy AI [wsj.com] in every corner of the government [futurism.com], it’s worth treading lightly when we ask for more.

More on synthetic biology:Scientists Debate Whether to Halt Type of Research That Could Destroy All Life on Earth [futurism.com]

AI Creates Bacteria-Killing Viruses: 'Extreme Caution' Warns Genome Pioneer [newsweek.com]:

A California outfit has used artificial intelligence to design viral genomes before they were then built and tested in a laboratory. Following this, bacteria was then successfully infected with a number of these AI-created viruses, proving that generative models can create functional genetics.

"The first generative design of complete genomes."

That's what researchers at Stanford University [newsweek.com] and the Arc Institute in Palo Alto called the results of these experiments. A biologist at NYU Langone Health, Jef Boeke, celebrated the experiment as a substantial step towards AI-designed lifeforms, according to MIT Technology Review [technologyreview.com].

"They saw viruses with new genes, with truncated genes, and even different gene orders and arrangements," Boeke said.

What They Built

They team created 302 full genomes, outlined by their AI, Evo - a LLM similar to that of ChatGPT - and introduced them to E. coli test systems. 16 of these designs created successful bacteriophages which were able to replicate and kill the bacteria.

Brian Hie, who leads the Arc Institute lab, reflected on the moment the plates revealed clearings where bacteria had died. "That was pretty striking, just actually seeing, like, this AI-generated sphere," said Hie.

How the designs were generated

The team targeted bacteriophage phiX174, a minimal DNA phage with approximately 5,000 bases across 11 genes. Around 2 million bacteriophage were used to train the AI model, allowing it to understand the patterns in their makeup and gene order. It then proposed new, complete genomes.

Why it matters

J. Craig Venter helped create the cells with these synthetic genomes. He saw the approach as being "just a faster version of trial-and-error experiments."

"We did the manual AI version - combing through the literature, taking what was known," he explained.

Speed is the appeal here. The prediction from the AI on the protein structure could certainly speed up the processes within drug and biotechnical development. The results could then be used to fight bacterial infections in, for example, farming or even gene therapy.

Samuel King, a student who led the project, said: "There is definitely a lot of potential for this technology."

The team excluded human-infecting viruses from the AI's training, but testing in this area could still be dangerous, warns Venter.

"One area where I urge extreme caution is any viral enhancement research,, especially when it's random so you don't know what you are getting.

"If someone did this with smallpox or anthrax, I would have grave concerns."

There are other issues with this idea. Moving to a 'simple' phage to something more complex such as bacteria - something that AI simply won't be able to do at this point.

"The complexity would rocket from staggering to ... way way more than the number of subatomic particles in the universe," Boeke said.

Despite the challenges surrounding this test, it is an extremely impressive result - and something that could influence the future of genetic engineering.

Original Submission