Forward-loving: Researchers from all over the world are currently embracing DNA-based storage. Both can bridge the best of the world by combining digital data and biology, although some challenges are still slowing down the market and industry.
Visionary solutions using DNA sequencing have been seen as the future of the world of storage for a few years. Biology has solved the data encoding problem a few billion years ago, so we can learn one or two things from nature, while we prepare to expand the world’s digital scope 180 zettabytes – the amount of 180 billion terabytes by the end of 2025.
Israeli researchers say they have found a way to significantly improve the data recovery process, which is the biggest issue of DNA storage technology, which is now facing. A team of Technion – Israel Institute of Technology used specially trained AI models to speed up data recovery from DNA strands. Needless to say, this process is still much slower than the “modern” storage technologies available on the market.
AI technology in question is known as DNAFORMER, and is based on a transformer model trained by technology researchers on synthetic data. The data simulator fed to DNAFORMER was also made in Technion. The model can re-organize accurate DNA sequences from error-prone copies and promote even more thanksgiving data integrity for a custom error-right algorithm designed to work well with DNA.
DNAFORMER is much faster in recovering data than earlier unveiled methods. The AI model can read 100 megabytes 3,200 times faster than the most accurate current method, and it appears that it can do so with the loss of data. The accuracy is improved “up to 40 percent”, which can further reduce the total recovery process time.
Israeli researchers tested the capabilities of DNaformer on a small 3.1-Magabyte data set, including a color still, a 24-second audio clip, a written piece about DNA storage and some random data. The latter was useful to show how the model could behave when encrypted or even compressed digital data. Official studies stated that the team achieved the “data rate” of the 1.6 bits per (DNA) base in a high-shrine regime, stating that the data cuts the time required to read for only 10 minutes from several days.
The Technion team stated that DNAFORMER will be further developed and various data storage would suit the needs. Technology can easily be compatible with scale and various scenarios, with promising possibilities for its adaptability. Researchers are already thinking about the improvement in the “market demand” and DNA sequencing in future to improve their AI technology.
