Every time you book a cab on an app or scroll through a list of movies on your favourite streaming platform, there is an entire ecosystem at work behind the screen that helps you get the best results quickly. The process is rooted in data, which is material for the next generation of machine learning. 

What matters to consumers is quick, high-quality results. That’s also the goal of large enterprises. These companies are using trillions of bytes of data through fast data lakes that help them store and access relevant data in real-time. 

Fuelling the next wave of AI acceleration 

The next wave of AI acceleration will depend on storage that supports bigger models or more powerful graphics processing units. As enterprises move into the next level of AI adoption, a big constraint they face is how quickly they can access and interpret the available data. Faster interpretation leads to faster decision-making, which will show on the bottom line. 

This is where fast data lakes are making an impact. Data lakes are designed to store raw, structured, and unstructured data in scalable ways. But traditional data lakes, often built on slower disk-based architectures, are becoming a hindrance in a fast-paced AI environment. While these work well for batch analytics, they fall short for modern AI pipelines that require tonnes of data to be accessible quickly. 

As AI applications become increasingly ubiquitous, far more data is set to become hot, which is frequently accessed and, therefore, needs fast retrieval, instead of cold, which is rarely accessed. The right storage technology, thus becomes crucial for managing hot data for ensuring the effectiveness and efficiency of data lakes. Fast data lakes enable organisations to store huge datasets in formats optimised for machine learning (ML), while serving data at the high Input/Output Operations Per Second (IOPS) and bandwidth demanded by modern AI pipelines. 

Flash storage is well-suited for fast data lakes, allowing models to be trained or retrained on massive datasets without waiting hours or days for data retrieval. 

AI is changing the storage game in terms of performance, capacity, and power efficiency. That’s where flash storage solutions from companies such as Sandisk come in. If AI retraining depends on a slow data lake, the entire pipeline can stall. These flash storage drives allow data lakes to maintain enormous data volumes while delivering dramatically faster read/write speeds over traditional disk-based storage, supporting total cost of ownership considerations. 

Fast data lakes are accelerating the next wave of AI by providing speed, scale, and flexibility to handle the massive volumes and diverse formats of data that modern AI and machine learning models require. 

By fuelling fast data lakes with high-performance, high-capacity, and power-efficient flash storage, enterprises are now on their way to eliminate storage bottlenecks and unlock the next level of AI acceleration—where data moves fast for the models that depend on it. 

(The author is chief product officer, Sandisk. Views are personal.)