Skip Levens, Marketing Director, Media & Entertainment at Quantum – Interview Insights

Skip Levens is a seasoned product leader and AI strategist at Quantum, a company renowned for its expertise in data management solutions for AI and unstructured data. Currently, Skip is responsible for driving engagement, awareness, and growth for Quantum’s comprehensive end-to-end solutions. Throughout his career, which includes key roles at Apple, Backblaze, Symply, and Active Storage, he has successfully spearheaded marketing efforts, launched new products, built strategic partnerships, and driven substantial business growth.

Quantum is at the forefront of providing complete data solutions that help organizations manage, enrich, and protect unstructured data, such as video and audio files, on a massive scale. Their technology is focused on transforming raw data into actionable insights, empowering businesses to extract value and make data-driven decisions. With secure, scalable, and flexible infrastructure that combines on-premise and cloud solutions, Quantum helps organizations manage data growth efficiently while ensuring its security and flexibility throughout the lifecycle.

Can you provide an overview of Quantum’s approach to AI-driven data management for unstructured data?

At Quantum, we help customers integrate artificial intelligence (AI) and machine learning (ML) into their core business operations. Our solutions allow customers to not just manage their unstructured data but also extract meaningful insights from it, creating actionable business intelligence. By leveraging AI and ML, organizations can shift from merely coping with increasing volumes of data to using those insights to drive operational efficiency and amplify human expertise across all phases of their operations.

How does Quantum’s AI technology analyze unstructured data, and what key innovations differentiate your platform from competitors?

When organizations first adopt AI/ML tools, they often encounter disordered workflows and disjointed data management, making it difficult to enforce security and protection standards. Moreover, early development efforts are often hindered by inadequate storage systems and poor file performance.

In response, we developed Myriad, a high-performance, software-defined file storage and intelligent fabric environment that elegantly tackles the challenges of AI/ML pipelines and high-performance workflows. Myriad consolidates workflows without the hardware limitations that often plague legacy systems. Built with the latest storage and cloud technologies, it is powered by Kubernetes and operates on a microservices-driven architecture, making it highly responsive with minimal administrative intervention.

Myriad is specifically designed to extract the highest performance from NVMe storage and intelligent fabric networking, with near-instantaneous Remote Direct Memory Access (RDMA) connections between components. As a result, Myriad is able to adapt intelligently to changes, requiring little administrative oversight to perform routine tasks. Its intelligent fabric architecture also ensures load-balancing with multiple 100Gbps bandwidth ports functioning as a single, balanced IP address.

When paired with our ActiveScale cloud-like object storage, Myriad enables organizations to archive and preserve large-scale data lakes and content with ease. Together, these systems provide a true end-to-end data management solution for AI pipelines. Additionally, our CatDV solution allows customers to tag and catalog their data, preparing it for more sophisticated analysis and AI-driven insights.

Could you share insights on the use of AI for video surveillance at the Paris Olympics, and other large-scale implementations?

AI can enhance video surveillance by identifying patterns and deriving insights from real-time video streams at scales far beyond human capacity. AI-powered systems can flag suspicious behavior from hundreds of cameras simultaneously, something a human operator could never manage in real time.

Additionally, AI can be employed for crowd sentiment analysis, monitoring long queues and identifying potential frustrations. By freeing human security experts to focus on actionable insights, AI dramatically increases both efficiency and safety in large-scale operations like the Paris Olympics.

What challenges do organizations face when implementing AI for unstructured data analysis, and how does Quantum help overcome them?

The biggest challenge organizations face is rethinking their storage and data management strategies. Many companies expand their storage capabilities piecemeal, leading to a complex mix of multi-vendor systems that create inefficiencies.

Quantum helps customers streamline their storage environments by integrating “hot” storage—where data is ingested and processed quickly—with cost-effective “cold” storage for archiving large volumes of data. This approach simplifies management, reduces the burden on administrative staff, and allows for rapid movement between hot and cold workflows, which is crucial for AI/ML integration.

How do Quantum’s AI innovations integrate with other AI-powered tools to enhance organizational efficiency?

Many people think of storage for AI/ML as merely feeding data to GPUs for analysis, but this is just one aspect. The true value of an AI-powered storage system is its ability to support continuous AI/ML development and iterative processes based on proprietary data. For instance, building knowledge bots that inform internal operations requires well-ordered and readily accessible proprietary data.

Quantum’s AI-powered storage solutions ensure that proprietary data is efficiently categorized and managed, streamlining its use in training and inference loops for custom AI models. This enables organizations to optimize their AI tools, ensuring they are highly informed and tailored to the company’s unique needs.

Can you elaborate on the AI-enabled workflow management tools and how they optimize data processes?

We are developing a suite of AI-enabled workflow management tools that automate key tasks and provide real-time insights. These tools use advanced AI-driven classification and tagging systems to organize data, making it easier to retrieve and even automate common actions, such as resizing files for specific AI training sets.

Our automation tools manage data movement, backups, and compliance tasks based on policy, ensuring consistent application and reducing the burden on administrators. Real-time analytics also offer immediate insights into data usage patterns, ensuring data integrity and quality throughout its lifecycle.

What is the future of AI-powered data management, and what trends do you foresee?

The future of AI-powered data management will see tools become more expressive and open-ended, allowing for dynamic interaction with your data. In the near future, you’ll be able to ask your system questions like “What’s the fastest-growing data type in my hot zone?” and receive immediate, actionable answers. Organizations that adopt these capabilities will set themselves apart, using AI to manage ever-evolving streams of data with greater precision and insight.

What role do your cloud-based analytics and storage-as-a-service offerings play in your data management strategy?

For organizations with growing storage demands, public cloud storage can be costly and unpredictable. To address this, we developed Quantum GO, which offers the flexibility and scalability of the cloud with predictable, low-cost subscription models. This service gives customers a “pay-as-you-grow” model for in-house cloud storage, combining the benefits of the public cloud with the control and cost-efficiency of on-premise infrastructure.

How does Quantum stay ahead in the evolving AI and data management landscape?

In today’s fast-changing environment, being just a storage provider is no longer enough. Quantum continues to invest in AI-driven innovations, enhancing our customers’ ability to manage and extract value from their data throughout its lifecycle. We are expanding our AI capabilities to streamline processes like video transcription, multilingual translations, and rapid search functionalities across thousands of files, helping our customers stay ahead in a data-driven world.

What advice would you give to organizations just starting with AI and unstructured data management?

AI/ML has generated a lot of hype, and it can be difficult for organizations to navigate what’s practical. My advice is to first focus on the data—how it’s created, captured, and preserved. It’s crucial to have a storage solution that is ready to access data when needed and helps streamline both current and future workflows. Even if your AI/ML goals aren’t fully defined, taking steps to simplify storage and data management now will pay dividends in the long run.