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HAL 9000. Samantha. KITT. Alexa. Siri. Bixby. Watson.

Movies, TV and companies have made artificial intelligence (AI) humanistic with catchy names, appealing voices and unique personalities. You have probably experienced AI via a virtual assistant, seen a Google self-driving car on the road or even implemented an IBM Watson* project in your organization.

You’ve probably also heard the terms machine learning, deep learning and cognitive computing. These terms have certain nuances. Machine learning uses algorithms to sift through data to learn and predict, while deep learning uses stacked neural networks. Deep learning is a subset of machine learning; machine learning is a subset of AI; and only cognitive can understand, reason, learn and interact. Whew—that’s a lot to digest.

At the end of the day, all you care about is understanding how AI can make your organization more profitable, more efficient and more disruptive. For insurance and financial companies, this means preventing fraud before it happens. For retail companies, this means optimizing your supply chain and inventory management. For consumer product companies, this means delivering real-time, customized content to your clients. These use cases are only limited by your imagination. If the business can dream it, IT can make it real with machine learning, deep learning (ML/DL), AI and cognitive solutions.

IBM enables you to implement AI your way. Sometimes a cloud-based solution or a Watson service consumed as an API might fit your needs, but in many cases you will also need to consider a do-it-yourself (DIY) approach to implementing an AI solution. DIY means creating a ML/DL environment for on-premises data, storing and managing on-premises data more efficiently, and creating a hybrid cloud data infrastructure that delivers the insights the business demands.

Your organization has substantial, critical data residing on premises, and that data is often the source of your competitive advantage. Running machine learning and deep learning close to where the data lives means you can build a more accurate model through rapid iteration of training. This setup also gives you more control and provides increased security for that critical data.

Ultimately, adding cognitive or AI capabilities to your business and IT strategy can enhance your digital transformation. We know that embarking on a journey to cognitive isn’t easy and it doesn’t happen overnight, but the IBM Power Systems* platform can help you take advantage of the data you already have and help you design the right on-premises AI solution to drive competitive advantage.