Imagine if you asked a large language model to write a fantasy story about a girl who wanders into a magical forest and meets a pirate with the same name as your brother, a fairy allergic to pixie dust, and a cat who speaks in iambic pentameter. Then, pair that with an AI image generator to illustrate the story. Add a model generating high-fidelity music from text descriptions to create an original soundtrack.
With a few simple prompts, anyone could create their own personalized multi-modal entertainment that’s been tailored specifically to their own imagination and preferences.
Sounds futuristic, but it’s happening now, and all of this intelligence – along with cutting-edge applications in the metaverse – would not be possible without data storage.
Putting the Intelligence in AI
The story scenario is all in good fun, but companies are taking AI seriously. Roughly 44% are looking to integrate the technology into their business plans. In order to do that, they’ll need diversified storage solutions to keep up with AI and other cutting-edge tech trends.
AI uses machine learning, deep machine learning, and neural networks to get the job done, and each processes data differently. When starring in our own AI-generated illustrated story, we must consider the production crew of the central processing units (CPUs), graphics processing units (GPUs), and GPU clusters in the case of large language models (LLMs).
These components are actually doing the “work” in near real time. But first, they must learn via training libraries, which can be quite large. They also need to be quick to effectively tell the story.
This is where data storage comes into play.
Depending on the use case, AI doesn’t necessarily consume more storage than other data-hungry applications; but it does consume storage differently as it moves data from multiple storage systems to AI processing systems.
Without a robust storage infrastructure, no single LLM can work, let alone a more complex mix of multi-modal systems involved in the AI process. The right mix of high-capacity hard disk drive (HDD) storage devices to store massive quantities of data to train LLMs combined with high-performance, low-latency solid-state drive (SSD) storage to run the LLMs are a must.
Unleashing the Metaverse
Augmented reality (AR) and virtual reality (VR) in the metaverse are also innovative tech trends on the rise in business. In fact, a recent study shows that 82% of surveyed business leaders expect their business activities to include the metaverse by 2026.
Consumer goods companies, retailers, and hospitality have begun to build the metaverse into their customer experiences. Other industries, like aeronautics and healthcare, are using the metaverse to train employees, simulating specific scenarios and teaching employees how to work through issues.
The metaverse could also take college learning to a new level. Students may someday soon roll out of bed and drop into a virtual augmented college classroom without even leaving their dorm rooms. The experience will be real enough to where users could hear the conversations around them just like in an actual lecture hall.
These applications depend on powerful storage in the background. Rendering fully interactive virtual worlds will require untold amounts of storage that will need to be responsive and fast like what’s used in gaming. Demanding hundreds of terabytes or more, this storage will also need to be high capacity.
Keeping Up with Data Demands
Storage innovation is key to delivering performance, capacity, resilience, and endurance for AI, in the metaverse and beyond. Developments in storage protocols and storage interfaces play a major role in meeting growing data requirements, bringing with them greater bandwidth and efficiency to support the increased data volumes moving between systems in AI, VR, and AR environments.
New technologies are increasing the areal density and capacity of HDDs today and building toward advancements for the future. The story of these advanced technologies has the potential to be the next story of human cultural experience, but it’s not possible without continuous innovation in data storage.