When we think about artificial intelligence (AI), our minds often jump to algorithms, neural networks, and other computing innovations. While these are certainly integral components of AI systems, one often overlooked aspect is storage. Storage plays a foundational role in AI by providing an easily accessible reservoir of vast amounts of data that is the essential fuel powering AI applications. Although storage doesn’t often get a lot of attention, it is the critical advancements in storage technology during the past twenty years that have enabled the rise of AI today.

The Data Explosion

In today's digital age, more data is being created than ever before. Smartphones, social media, IoT devices, and other technologies generate massive amounts of data every day. AI systems harness these large reservoirs of data to make informed decisions and predictions. However, the sheer volume of data presents a storage challenge, requiring scalable and efficient storage solutions to manage and process data quickly and effectively.

Advancements in Storage Technology

Over the past two decades, storage technology has evolved significantly to meet the demands of AI applications. Solid-state drives (SSDs), with their faster read and write speeds, have replaced traditional hard disk drives (HDDs) in many AI systems, enabling quicker access to data for training. Non-Volatile Memory Express (NVMe) has further enhanced storage performance, offering even faster data transfer speeds for AI workloads.

Cloud storage solutions have also played a crucial role in the storage revolution, providing scalable and cost-effective storage options for AI applications. Organizations can now store and access large datasets in the cloud, leveraging the flexibility and scalability of cloud storage for their AI projects. Cloud storage has not only made data more accessible but has also enabled collaboration and data sharing among researchers and developers working on AI projects worldwide.

A Timeline of Storage Evolution During the Past 20 Years

2000s: The 2000s saw the rise of solid-state drives (SSDs) as a faster and more reliable alternative to traditional hard disk drives (HDDs).

Mid-2000s: Non-Volatile Memory Express (NVMe) emerged as a storage interface protocol designed for SSDs, offering significantly faster data transfer speeds.

Late 2000s: Cloud storage solutions began to revolutionize data management for AI applications, offering scalable and cost-effective storage options.

2010s: Introduction of 3D NAND flash memory, increasing storage density and lowering costs.

2020s: Emergence of storage class memory (SCM), offering higher performance and lower latency compared to traditional NAND flash memory.

The Future of Storage

Looking ahead, the future of storage in AI is set to advance even faster than the past twenty years have seen. Researchers and developers are exploring new technologies that will further revolutionize storage capabilities. Future storage possibilities such as DNA data storage that leverages DNA molecules to store data, quantum storage, which stores and retrieves data at the quantum level, and photonic storage, using light instead of electrons to store and retrieve data, are all cutting-edge storage technologies that are poised to reshape the landscape of storage and enable even greater advancements in the field of artificial intelligence in the future.

With so many rapid advances in storage technology over the past twenty years and more to come in the next decade, storage will continue to be the foundation upon which many of the advances in artificial intelligence are built upon. Advances in finance, healthcare, education, and other areas will all continue as new storage technologies also develop.