Dell Technologies World was all about AI; what about security?
At Dell Technologies World 2024, Dell made it crystal clear that it is all-in on AI, but the company must also emphasize the importance of cybersecurity.
- Dave Gruber,
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Enterprise Strategy Group
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As a cybersecurity industry analyst, I spend most of my time working with security companies, but at Dell Technologies World last week, I was immersed in conversations about AI.
Though Dell isn't a cybersecurity company, it offers several high-quality managed security services focused on helping its customers keep their operating environment safe and secure. Services include security program assessment and maturity development, zero-trust strategy development, managed detection and response, vulnerability management and traditional incident response services.
While rich in security talent to support these offerings, Dell's engineering investment in these areas primarily focuses on integrations, implementation and unified management. The company works closely with various security providers, including Zscaler, Okta, CrowdStrike, Halcyon, Palo Alto Networks, Deep Instinct and Index Engines -- all of which were at the conference.
I spent plenty of time with Dell's services team and the many security vendors present at the event, but I was more focused this year on how and where Dell is delivering AI in support of the massive transformation that companies are going through as they AI-enable their operations.
Dell is all-in on AI, which dominated the conversation throughout the week. The Dell AI Factory was at the center of it all, and Dell laid out a strategy for every company to plot a course for their own AI journeys. While running fast, Dell was quick to admit that it is learning along with its customers but made a pledge to be transparent and to communicate what the company learns with all by sharing reference playbooks that can be utilized within the AI factory.
Dell's AI strategy is anchored on five tenants:
- Data is the differentiator.
- Data gravity matters -- building models where your data already lives is more efficient, effective, and secure.
- No one-size-fits-all.
- Things are moving fast, so using an open, modular architecture is the only practical approach to leverage all the knowledge and available innovation.
- A broad and open ecosystem is required to keep up.
Dell believes most enterprises will ultimately end up using their own small language models that combine their own data, augmentation and publicly available data. These models will be optimized over time, fueled by intelligent data pipelines to ensure the models are primed with fresh data.
But Dell says the traditional data center is simply not equipped to support all this. A different scale of computational compute power is necessary, together with high-speed I/O for files and object data stores; data storage and management subsystems to prepare, clean and validate data used to build models; and a high-throughput, low-latency network backplane to enable a massively distributed compute environment.
AI workloads, referred to as "elephant workloads," require massive processing, power, cooling and network capabilities. The first three weren't a surprise to me, but I hadn't thought much yet about the network requirements needed to support the massive parallelization needed to scale up a cluster to build large language models. This distributed computing architecture can only work if the backend network can enable these systems to work together. Dell is partnering with Broadcom to tackle this problem.
Much focus was on the AI data pipeline that fuels the AI rocket ship. Dell made it clear that keeping the data close to the source is the best approach, versus pushing massive amounts of data into the cloud for processing. In a customer session I attended, this proved to be true, as they found that moving the data to the cloud for processing created delays that resulted in longer build times for models. They reported that moving the processing on premises where the data resides delivered up to five times improvement in the speed of model creation. This of course is powered by Dell PowerEdge XE servers.
As Dell pivots its agenda to an all-in AI strategy, a new opportunity to repatriate data and on-premises processing has the potential to dramatically change the growth trajectory for Dell, leaving me to wonder if this will cause IT leaders to reconsider cloud strategies, or will this be a net add in spending, further growing overall IT spend in support of the AI revolution.
Dell has also added professional services offerings to support customers' AI journeys, including strategy development, use case definitions, help with building the models, including preparing and cleansing the data, education to build out internal knowledge to enable self-sufficiency, and infrastructure planning and design.
Will AI redefine how we think about applications?
Reimagining applications in an AI world is an important agenda for us all. We have opportunities to utilize AI to accelerate growth, optimize current operations, improve experiences and create new opportunities. As we move fast, we must also consider how and where we are introducing risk and prioritize architecting in security from the beginning.
As developers use AI in software development, surely new opportunity will arise for adversaries to exploit advancements before risk and vulnerabilities are understood. We must be diligent in keeping security in the conversation as development teams learn how to use AI to redefine how software is created.
There were some interesting discussions around topics such as AI bias, harkening back to the importance of establishing well thought out data management and governance models, and the importance of cleansing and validating the data used to build models. Also noted were the nation-state governance initiatives underway, with some hesitation on how effective they can be as the AI revolution is moving so much faster than governance programs can.
Dell AI and cybersecurity
Dell is making a big play and staking its claim as the leader in enabling companies to accelerate their AI journeys. Its big message to customers was to ramp up AI investment now or be left behind playing catch-up to competitors. This, of course, nicely supports the acquisition and consumption of more Dell products and services. The company urged customers to get engaged, be curious, be AI proficient and become a practitioner -- plenty of sound advice here.
While I'd give Dell's conference an A+ this year, I feel like the company fell short in weaving in the importance of cybersecurity within the AI journey. Sure, it is still early days, but as John Roese, global chief technology officer of Dell Technologies pointed out, in the past, cybersecurity was bolted onto an existing IT infrastructure, putting security behind the eight ball from the beginning. Roese took the opportunity to declare that there is a real opportunity to architect and build a new operating infrastructure with security in mind, ensuring zero-trust principles are built in from the beginning.
We have an opportunity to do things differently as we develop and transform systems to use AI. Even with Dell not delivering AI security software, I would have liked to have seen a panel of security providers on the main stage to cement the importance of security in early AI strategy development. Despite an all-IT audience attending the conference, reinforcing the importance of architecting in security from the beginning will be core to successful AI strategies.
Dave Gruber is principal analyst at TechTarget's Enterprise Strategy Group where he covers ransomware, SecOps and security services.
Enterprise Strategy Group is a division of TechTarget. Its analysts have business relationships with technology vendors.
