@cung.u.truyn4: Khiêu khích chính thất và cái kết #phimhanquoc #thienngado

Cung Đấu Truyện
Cung Đấu Truyện
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Tuesday 06 October 2026 01:09:43 GMT
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AI Just Created a Virus ,  Scientists at Stanford University and the Arc Institute have demonstrated a striking new capability for artificial intelligence: designing viral genomes that have never existed in nature and producing viruses from those designs in the laboratory. The study, published in Science in August 2026, focused on bacteriophage Phi X-174, a small virus that infects E. coli. Because its genome is only about 5,400 nucleotides long and has been studied for nearly a century, Phi X-174 provided a relatively simple and well-understood system for testing whether AI could generate functional viral genomes. The researchers used an AI model called Evo, developed by a team led by Stanford computational biologist Brian Hie. Unlike AI systems trained primarily on human language, Evo was trained on enormous collections of biological sequences. The model analyzed roughly nine trillion nucleotides from organisms across the tree of life, learning patterns in DNA that help determine whether a sequence can function biologically. The researchers then gave Evo additional information about Phi X-174 and roughly 15,000 of its closest relatives. The goal was not simply to copy an existing virus, but to have the AI generate new genome sequences while preserving the underlying biological rules needed for a virus to function. Evo produced approximately 700,000 candidate genomes. Scientists computationally screened these designs and selected a smaller group for experimental testing. They synthesized DNA corresponding to 285 candidate genomes and introduced the DNA into E. coli. Most designs failed to produce functional viruses. But in some experiments, the bacteria began producing viral particles. The viral genes were expressed inside the cells, viral proteins assembled into protective protein shells, and new phage particles were produced. Eventually, the viruses broke out of the bacterial cells, releasing new phages capable of infecting other E. coli. In total, 16 of the 285 tested genomes produced viable viruses. Some of these AI-designed phages were surprisingly fit and multiplied faster than natural Phi X-174 under the experimental conditions. The achievement is important because these viruses were not simply copied from an organism found in nature. Their genome sequences were generated by an AI model and had not previously existed as natural viral genomes. At the same time, the researchers emphasize that the designs were based on Phi X-174 and related bacteriophages, which infect bacteria rather than humans. They also deliberately excluded genetic information from viruses that infect humans and other animals. The work points toward a potentially important new direction in biology. Viruses can serve as tools for delivering genes, studying cells, developing medicines, and potentially treating bacterial infections. In the future, AI-generated biological systems could help scientists explore designs that would be extremely difficult to discover through traditional trial and error. #AI #ArtificialIntelligence #SyntheticBiology #Bacteriophage #Phage #Virus #Ecoli #DNA #Genomics #Bioengineering #StructuralBiology #Science #SciTok #FutureOfScience #learnontiktok #Science #learning #immune #stem #coolscience #nanomachine #biotok #simulation #funfacts #biology #3danimation #ScienceExplained #biochemistry #ATP
AI Just Created a Virus , Scientists at Stanford University and the Arc Institute have demonstrated a striking new capability for artificial intelligence: designing viral genomes that have never existed in nature and producing viruses from those designs in the laboratory. The study, published in Science in August 2026, focused on bacteriophage Phi X-174, a small virus that infects E. coli. Because its genome is only about 5,400 nucleotides long and has been studied for nearly a century, Phi X-174 provided a relatively simple and well-understood system for testing whether AI could generate functional viral genomes. The researchers used an AI model called Evo, developed by a team led by Stanford computational biologist Brian Hie. Unlike AI systems trained primarily on human language, Evo was trained on enormous collections of biological sequences. The model analyzed roughly nine trillion nucleotides from organisms across the tree of life, learning patterns in DNA that help determine whether a sequence can function biologically. The researchers then gave Evo additional information about Phi X-174 and roughly 15,000 of its closest relatives. The goal was not simply to copy an existing virus, but to have the AI generate new genome sequences while preserving the underlying biological rules needed for a virus to function. Evo produced approximately 700,000 candidate genomes. Scientists computationally screened these designs and selected a smaller group for experimental testing. They synthesized DNA corresponding to 285 candidate genomes and introduced the DNA into E. coli. Most designs failed to produce functional viruses. But in some experiments, the bacteria began producing viral particles. The viral genes were expressed inside the cells, viral proteins assembled into protective protein shells, and new phage particles were produced. Eventually, the viruses broke out of the bacterial cells, releasing new phages capable of infecting other E. coli. In total, 16 of the 285 tested genomes produced viable viruses. Some of these AI-designed phages were surprisingly fit and multiplied faster than natural Phi X-174 under the experimental conditions. The achievement is important because these viruses were not simply copied from an organism found in nature. Their genome sequences were generated by an AI model and had not previously existed as natural viral genomes. At the same time, the researchers emphasize that the designs were based on Phi X-174 and related bacteriophages, which infect bacteria rather than humans. They also deliberately excluded genetic information from viruses that infect humans and other animals. The work points toward a potentially important new direction in biology. Viruses can serve as tools for delivering genes, studying cells, developing medicines, and potentially treating bacterial infections. In the future, AI-generated biological systems could help scientists explore designs that would be extremely difficult to discover through traditional trial and error. #AI #ArtificialIntelligence #SyntheticBiology #Bacteriophage #Phage #Virus #Ecoli #DNA #Genomics #Bioengineering #StructuralBiology #Science #SciTok #FutureOfScience #learnontiktok #Science #learning #immune #stem #coolscience #nanomachine #biotok #simulation #funfacts #biology #3danimation #ScienceExplained #biochemistry #ATP

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