sponsored

Going from AI-possible to AI-ready with new Ready Solutions

New Ready Solutions for AI make it easier than ever before to shift the discussion from talk to action.

aihair1000x6301
Dell EMC

We’ve all read countless stories about the possibilities created by artificial intelligence. Chances are your organization is considering new processes and products that could be enabled by AI, when the time is right. Well, that time has come. It’s now a new day, in which we are moving from AI-possible to AI-ready.

The time is right for AI deployments for multiple reasons. We’ve seen huge advances in AI and its enablers, particularly machine learning and its subfield of deep learning. In a parallel trend, we’ve seen big leaps forward in high-performance computing systems, in terms of both processing power and affordability. HPC is now accessible to virtually all sizes of organizations. And, finally, we’ve got an ever-ballooning supply of data to use to train the machine and deep learning models that enable AI.

If your organization is on the path to AI readiness, Dell EMC has already done a lot of the heavy lifting for you. We’ve invested in a portfolio of Ready Solutions for AI that takes a lot of the complexity out of AI deployments. This portfolio of solutions gives you ready access to validated hardware and software stacks optimized to accelerate AI initiatives.

In a Total Economic Impact™ study commissioned by Dell EMC and Intel, Forrester Research found that Dell EMC Ready Solutions for AI can reduce the time required to architect a new solution by up to a year when compared to implementing a solution on your own.[1] This TEI study focused on the impact of Dell EMC Ready Solutions for AI, Machine Learning with Hadoop, with Intel inside.

“Dell EMC’s Ready Solutions made implementation of the Hadoop environment relatively quick and easy,” the study noted. “Organizations speculated that if they had tried to implement on their own, it would have taken six to 12 months longer to hire the expertise, figure out the correct configurations, and deploy the platform.”

The same study found that Ready Solutions help organizations achieve high performance even in initial AI deployments. One principal architect interviewed for the study explained that Dell EMC did the due diligence, taking a load off the organization: “Because they … understood what works, what types of workloads are optimized, and what are good use cases for different hardware configurations, we didn’t have to be experts at hardware. That was huge.”

The benefits don’t stop there. If you peek under the hood, you’ll see that Dell EMC Ready Solutions for AI increase data scientist productivity by offering self‑service workspaces that allow individual data scientists to configure their environments from a library of AI models and frameworks in just five clicks. Think about that: a self-service AI environment in just five clicks.[2]

The Forrester study found that the Dell EMC Ready Solutions for AI, Machine Learning with Hadoop enable near-real-time data analysis and slash the time required to build and run reports, ultimately improving the productivity of data scientists by 30 percent.

“Data scientists can spend less time loading and structuring data, enabling them to devote a larger portion of their time to value-add work,” the study noted. “Workloads run in a fraction of the time and systems function better, with failure rates for reports dropping from 10% to 2%.”

The higher-level point here should be perfectly clear: New solutions are available to make AI easier than ever for your organization. With these solutions, you can shift to focus from AI-possible to AI-ready.

To learn more about going from AI-possible to AI-ready, visit dellemc.com/readyforai and see the product overview video.

[1] Forrester research commission by Dell EMC and Intel, “The Total Economic Impact™ of Dell EMC Ready Solutions for AI, Machine Learning with Hadoop,” August 2018.

[2] ESG Technical Review, “Accelerating the Artificial Intelligence Journey with Dell EMC Ready Solutions for AI,” August 2018.