By Ace Stryker, Solidigm

The rapid growth of artificial intelligence (AI) is driving an unprecedented demand for data storage solutions that are both powerful and efficient. As AI applications grow and scale, data centers face significant challenges. In response, the storage industry is undergoing a shift, with solid-state drives (SSDs) emerging as a critical enabler of AI innovation. This article explores the key trends and predictions shaping the future of AI data storage in 2025 and beyond.

Driven By AI, Power Efficiency Needs Will Revolutionize Data Centers

As AI continues to grow, its energy demands are soaring. AI is anticipated to more than double electricity needs by 2030, primarily due to the increasing demand for data center power to process complex AI data sets. This will reshape the data center landscape in 2025.

Power consumption is one of the primary challenges facing the expansion of AI data centers. In some regions, power limitations are already slowing the development of AI infrastructure. Storage plays a pivotal role in this issue, as traditional hard disk drives (HDDs) required to meet performance demands are constantly running and consuming significant power. Companies are scrambling to develop sustainable storage solutions that help data centers and enterprises address the power, space, and environmental challenges of modern AI applications.

High-density SSDs will be at the forefront of this transformation. By storing more data in less space, these ultra-dense drives reduce the need for multiple HDDs, resulting in:

• 80% less power for AI storage solutions
• Reduced cooling costs
• Smaller data center footprints
• Less e-waste at end-of-life
  

From the core to the edge, extreme AI energy use and limited power availability make every watt and square inch in the AI data center matter. Power and space-efficient SSDs that maximize AI potential while delivering a more fully utilized return on AI infrastructure investment are the future.

Solid-State Drives Will Continue to Displace Hard Disk Drives in Data Centers

The storage landscape is poised for a significant transformation in 2025. Solid-state drives (SSDs) will continue to gain traction, eventually supplanting hard disk drives (HDDs) as the dominant storage technology in data centers.

AI will be a key driver of this. Approximately 90% of data centers today use HDDs to store the reams of information that make AI work, from machine learning to large-language models. However, HDDs -- invented way back in the 1950s -- are unsuitable for data-intensive AI applications. Their slow performance, inferior reliability, and limited storage capacity make them a bottleneck.

AI needs a massive amount of data, and it needs to be able to access that data at speed. SSDs offer higher density and orders of magnitude faster performance than HDDs, enabling lightning-quick data access and processing. SSDs can store more data in less space, reducing power consumption and the overall footprint of data centers. SSDs also offer a longer lifespan, reducing the need for frequent replacements and minimizing electronic waste.

The advent of QLC technology will further accelerate the adoption of SSDs in the data center. By allowing four bits of data to be stored in each memory cell, QLC technology has enabled the development of higher-capacity SSDs that are more cost-effective and efficient.

As the storage landscape continues to evolve, one thing is clear: the future of data storage is solid-state. SSDs will do for data what the PC did for the semiconductor or the Internet for connectivity-enable new solutions and real-world benefits that we can't even imagine yet.

AI Moves to the Edge with High-Performance SSDs

AI is increasingly happening in places outside the data center, as certain industries and applications need to move infrastructure toward their data instead of the reverse. Key reasons for this include reduced latency and enhanced security by processing data closer to its source.

Quintillion bytes worth of data are generated every day. That data needs to be stored, accessed, and analyzed. Traditional edge servers can quickly become overwhelmed, and the challenge will only worsen as more services and applications rely on AI. Without access to data, these applications simply cannot function. Storage density also becomes more critical with this shift to the edge in order to tackle challenges such as tight space constraints in edge infrastructure devices.

As a result, the edge computing landscape is undergoing a significant transformation as AI workloads demand higher capacity, superior performance, and reliability. In 2025, we predict that high-density solid-state drives (SSDs) will be crucial in enabling edge AI applications and revolutionizing industries like healthcare, manufacturing, remote applications, and smart cities.

By storing data close to the source of generation, SSDs contribute to the effectiveness of edge AI by enabling real-time processing capabilities, reduced reliance on distant data centers, and enhanced efficiency for mission-critical applications. They also offer superior performance, reliability, and durability.

Because SSDs have no moving parts, they are less prone to damage from shocks and vibrations, common in edge environments. This durability enhances lifespan and reduces mechanical failures, downtime, and maintenance costs of AI systems. SSDs are also well-suited to onsite data storage in remote areas with harsh weather conditions and consume less power, making them ideal for locations with limited power resources.

Expect SSDs to advance AI edge applications in industries where delays in data processing can lead to critical failures. With their superior performance, reliability, and durability, SSDs are poised to revolutionize edge AI applications, transforming industries and improving lives.

Shattering the 100TB Single Device Barrier-And Advancing Even Farther

Two years into the artificial intelligence revolution, the technology industry has witnessed an unprecedented surge in data demand. The scale of data required to power AI systems is staggering, rendering current storage infrastructure inadequate. As we move into 2025, the industry is poised for a significant breakthrough in storage technology.

AI algorithms demand an extreme amount of data to thrive. For example, the median size of an AI model training set more than doubled in 2022 and multiplied by six in 2023. This trend shows no signs of slowing down, with AI models increasingly relying on massive datasets to train and improve.

Current storage infrastructure, often reliant on hard disk drive (HDD) storage, is struggling to keep up with the sheer scale of AI data demands at scale. Adding more hard drives is not a viable solution, as it leads to increased power consumption, rack space requirements, and maintenance costs. It's becoming clear: AI will simply need a more efficient storage infrastructure.

In 2025, we predict that storage industry innovators will focus on pushing the capacity of solid-state drives (SSDs) to help address these challenges. The largest available standard form factor SSD has already shattered 100TB single device and currently stands at 122.88TB, roughly equivalent to storing 4K-quality copies of every movie theatrically released in the 1990s, 2.6 times over. The key to unlocking higher SSD capacities lies in quad-level cell (QLC) technology, which allows the storage of four bits of data in each memory cell, significantly increasing storage density. As SSD technology advances, we predict this breakthrough will have far-reaching implications for the AI industry, enabling faster, more efficient, and more cost-effective data storage and processing.

As AI continues to transform industries, the role of solid-state drives in powering its advancement will only continue to grow. By harnessing the potential of high-density SSDs, innovators can unlock new possibilities for AI-driven applications and drive sustainable growth.

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ABOUT THE AUTHOR

Ace Stryker is director of market development at Solidigm, a leading provider of innovative NAND flash memory solutions. He is responsible for identifying emerging market opportunities for Solidigm's data center products, with a current focus on generative AI applications.