What Does it Take to Get Started with AI?

Print Friendly, PDF & Email
AI

This article is part of a special insideHPC report that explores trends in machine learning and deep learning. The complete report covers how businesses are using machine learning and deep learning, differentiating between AI, machine learning and deep learning, what it takes to get started and more. 

We’ll start off by providing a handy five-step enterprise AI strategy designed to ensure your early AI deployment projects are a success. We’ll also highlight several hardware and software tracks that will assist you along the way.

  1. Get familiar with the technology – Take the time to become familiar with what modern AI can do. A good way to acquire this knowledge is to develop a close partnership with your chosen technology vendor.
  2. Identify the problems you want AI to solve – Once you’re up to speed on the basics, the next step for any business is to begin exploring different ideas. Think about how you can add AI capabilities to your existing products and services. More importantly, your company should have goals in mind of specific use cases in which AI could solve business problems or provide demonstrable value.
  3. Prioritize concrete value – Next, you need to assess the potential business and financial value of the various possible AI implementations you’ve identified. It’s easy to get lost in “pie in the sky” AI discussions and it’s important to tie your initiatives directly to business value.
  4. Acknowledge the internal capability gap – There’s a stark difference between what you want to accomplish and what you have the organizational ability to actually achieve within a given time frame. A business should know what it’s capable of and what it’s not from a technological and business process perspective before launching into a full- blown AI implementation.
  5. Bring in experts and set-up a pilot project – Once your business is ready from an organizational and technological standpoint, then it’s time to start building and integrating. The most important factors here are to start small, have project goals in mind, and especially to be aware of what you know and what you don’t know about AI. This is where bringing in outside experts or AI consultants from a technology partner can be invaluable.

You can download the complete report, “insideHPC Research Report on Riding the Wave of Machine Learning & Deep Learning,” courtesy of Dell EMC and Nvidia.