NEVER kid yourself. To understand the world's job market, look beyond the unemployed students. So, let's go and pick our poison :

GENERATIVE A.I. technologies are driven by what scientist call a neural network, a mathematical system that learns skills by analyzing vast amounts of data.

The image creator Midjourney, for example, is underpinned by neural network that has analyzed millions of digital images and the options that describe each of those images. The system learned to recognize the links between the images and the words.

So when you ask it for an image of a rhinoceros leaping off the Golden Gate Bridge, it knows what to do.

Profluent's technology is driven by a similar A.I. model that learns from the sequence of  amino acids and nucleic acids - the chemical compounds that define the microscopic biological mechanism that scientists use to edit genes.

ESSENTIALLY, it analyzes the behaviour of CRISPR gene editors pulled from nature and learns how to generate entirely new gene editors.

'' These A.I. models learn from sequences -whether those are sequences of characters or words or computer code or amino acids,'' said Profluent's chief executive, Ali Madani, a researcher who previously worked in the A.I. lab at software giants Salesforce.

Profluent has not yet put these synthetic gene editors through clinical trials, so it is not clear if they can match or exceed the performance of CRISPR. But this proof of concept shows that A.I. models can produce something capable of editing the human genome.

Still, it is unlikely to affect health care in the short term. Fyodr Urnov, a gene editing pioneer and scientific director at the Innovative Genomics Institute at the University of California, Berkeley said scientists had no shortage of naturally  occurring gene editors that they could use to fight illness and disease.

The bottleneck, he said, is the cost of pushing these editors through preclinical studies, such as safety, manufacturing and regulatory reviews, before they can be used on patients.

But generative A.I. systems often hold enormous potential because they tend to improve quickly as they learn from increasingly large amounts of data. 

If technology like Profluent's continues to improve, it could eventually allow scientists to edit genes in far more precise ways.

The hope, Dr. Urnov said, is that this could, in the long term, lead to a world where medicines and treatments are quickly tailored to individual people even faster than we can do today.

'' I dream of a world where we have CRISPR on demand within weeks,'' he said.

Scientists have long cautioned against using CRISPR for human enhancement because it is a relatively new technology that could potentially have undesired side effects, such as triggering cancer, and have warned against unethical uses, such as genetically modifying human embryos.

This is also a concern with synthetic gene editors. But scientists already have access to everything they need to edit embryos.

'' A bad actor, someone who is unethical, is not worried about whether they use an A.I.-created editor or not, '' Dr. Fraser said. '' They are just going to go ahead and use what's available.''

This Research Publishing continues. The  World Students Society thanks Cade Metz.


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