AiThority Interview with Haoyuan Li, Founder and CEO, Alluxio

In this quick chat, Haoyuan Li, Founder and CEO of Alluxio, highlights the benefits of AI and big data workloads, innovative ways to boost AI and ML initiatives, and the importance of data infrastructure.

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Hi Haoyuan, Welcome to the AiThority’s Interview series. Alluxio started as an open-source project and evolved into a critical player in data orchestration. Can you walk us through that journey and the vision that drives Alluxio today?

Alluxio was founded with the vision of empowering organizations to accelerate innovation by unlocking the full potential of their data, regardless of size, location, or format. Today, our vision remains the same despite tremendous evolutions in applications and technologies over the last 10 years.

Our journey started as big data was just starting to introduce technology and business challenges for organizations. Many of the biggest companies in the world chose Alluxio to help them solve these big data challenges with the objective of extracting more insights from their data through the application of big data analytics. We continue to work with customers to make these analytics applications run more efficiently and at a lower cost.

Over the last several years, advancements in machine learning (ML) and artificial intelligence (AI) have given rise to an entirely new set of applications and uses for an organization’s data. In fact, AI and ML applications often require even bigger data sets than data analytics workloads.

Alluxio’s journey has evolved with this technological shift toward AI and ML with the release of Alluxio Enterprise AI. We now provide solutions tailored to the specific requirements for training, deploying, and serving large-scale AI and ML models.

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Please discuss how Alluxio enhances performance for AI and big data workloads and how customers are benefiting from it.

Alluxio accelerates AI and big data workloads in a variety of ways. First and foremost, Alluxio’s distributed caching technology increases the speed of accessing large volumes of data for data analytics and AI/ML workloads. By intelligently caching data accessed by these workloads near the application infrastructure, we eliminate storage and network bottlenecks and improve end-to-end performance.

Alluxio also enhances productivity by simplifying data access for engineers and data scientists building these data-driven applications. Alluxio’s unified namespace provides these teams with a single interface to access various types of data spread across multiple storage systems and cloud providers.

Finally, our customers realize a much faster product-to-market journey and a substantial reduction in infrastructure costs by leveraging Alluxio. This is accomplished first by reducing data access challenges for various data driven applications and eliminating the need for organizations to invest in expensive and complex high-performance storage solutions. Secondly, by utilizing Alluxio’s distributed caching technology our customers lower their cloud storage costs by reducing data access requests and egress charges.

What has been the most defining moment in the company’s growth so far, and what lessons have you learned along the way?

While it is still early, we believe that the rapid evolution of AI will be the most defining moment for Alluxio. AI models are trained on extremely large volumes of data and must be continuously trained as data changes. For example, one of our social media customers deployed our solution to achieve a 6-hour SLA in updating their models that recommend content to their 100s of millions of users each day while saving 4x times their GPU cost.

For AI to become even more ingrained in our personal and professional lives, organizations must deliver accurate and up-to-date models in near real-time. Alluxio’s solutions provide organizations the ability to accomplish these complex, technical challenges while also lowering infrastructure costs.

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What are some of the most innovative ways you’ve seen companies use Alluxio to accelerate their AI and ML initiatives?

Alluxio Enterprise AI customers leverage our solution to decrease the amount of time it takes to train their AI and ML models, up to 4 times faster in some cases. Prior to deploying Alluxio, these organizations found that the GPUs in their training infrastructure were underutilized during peak periods despite training workloads not completing within their SLAs. This indicates that GPUs are waiting on data needed to do their work and that adding more GPUs to the training infrastructure won’t improve training performance. By introducing Alluxio, our customers eliminate the actual bottleneck by caching training data near the GPU infrastructure to accelerate data access, increase GPU utilization, and improve end-to-end training performance.

You’ve worked closely with AI, data infrastructure, and open-source communities. What’s one piece of advice you’d give to aspiring tech entrepreneurs before we close?

That’s a great question. Starting a company is a long journey. I believe that you have to be passionate about the problems your products solve. Markets change and technology evolves, which means your company and products will need to adapt to these changes. If you’re passionate about the space you are in and the vision you have defined for your company is rooted in solving customer problems then evolving your strategy as trends change will be a natural progression that opens new opportunities for growth.

Thank you, Haoyuan, for sharing your insights with us.

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