Another related field harnessing the encoded properties of DNA is data storage. The shortcomings of conventional storage techniques and the promise of DNA-based data storage as a viable alternative have resulted in a vast scientific investigation into bio-data storage. This approach involves employing DNA synthesis, sequencing, and encoding algorithms to store substantial volumes of data with exceptional density and longevity. This field has gained significant attention in the past decade, with several breakthroughs. DNA storage offers advantages such as stability, ease of replication and backup, limitless uses, and the ability to survive harsh conditions. Theoretically, each gram of DNA can store a vast amount of digital information, and it can withstand extreme temperatures when appropriately protected. These unique features make DNA a promising material for secure and long-term data storage in the future . In 2019, a DNA data storage system was created which employs software developed by the joint efforts of Microsoft and the University of Washington team. This innovative system was able to transform the binary code of digital information into the nucleotide bases (A, T, C, and G) that constitute the fundamental elements of DNA . A recent demonstration showcased a technique for conducting searches for similarities within a DNA-based database comprising 1.6 million images, using binding probes and a conversion of images to genetic sequences to execute queries. Experimental findings indicate that this molecular technique demonstrates similar performance to cutting-edge computational algorithms for conducting resemblance searches . Although DNA machine learning is still in its infancy, there is potential for its advancement toward the creation of future 'bio-AIs'.