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Home»Science»AI can decode digital data stored in DNA in minutes instead of days
Science

AI can decode digital data stored in DNA in minutes instead of days

February 21, 2025No Comments2 Mins Read
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DNA can save digital data such as visual and audio files

Science image Co / Alamy

Artificial intelligence can read data stored in DNA chains in 10 minutes more than the days needed for previous methods, DNA storage to approach the practical use of computer.

“DNA can store a large amount of data in a dense form and has been in its own and for thousands of years,” he says Daniella Bar-Lev University of California, San Diego. “In addition, DNA is naturally repeatable, offering a unique advantage for long-term conservation.”

Recovery of information encoded within DNA is a monumental challenge because the chains are confused and stored together. During the data encoding process, sometimes individual chains are sometimes repeated, and some parts can be completely lost. As a result, reading the DNA saved data reconstructs a page with crushed writing, written pages.

“Traditional methods fight with this chaos, they need processing days,” says Bar-Lev. New views “This is, this is, with AI prepared for the Patterns of Patterns,” he explains.

Bar-Lev and his colleagues developed the AI ​​powered method called DNAFERED, which can quickly and accurately decode the DNA sequence. The system is a deep AI model prepared to reconstruct DNA sequences, the third decoding algorithm that identifies and directs errors and the third decoding algorithm.

In experiences, Dnnormer 100 megabyte read 100 megabytes 90 times faster – developed with regulations based on computing algorithms while achieving better or comparable accuracy. Decoded data had a colored image of test tubes, a 24-second audio clip of the famous Astronaut Armstrong fair. DNA written text with a promising data storage medium.

The Group aims to develop DNAFER version of DNNormer to new dna to develop new techniques in DNA, says Omer Sabilaria Technology – Israeli Institute of Technology.

“Because our approach is not based on specific synthesis or sequencing methods, until the future can be more trading viable, it can still be uneven viable,” he said.

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