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AI today: Data, training and inferencing
In my last blog, I discussed artificial intelligence, machine learning and deep learning and some of the terms used when discussing them. Today, I’ll focus on how data, training and inferencing are key aspects to those solutions. The large amounts ...
A future of powerful clouds
In a very good way, the future is filled with clouds. In the realm of information technology, this statement is especially true. Already, the majority of organizations worldwide are taking advantage of more than one cloud provider.[1] IBM calls this ...
AI, machine learning and deep learning: What’s the difference?
It’s not unusual today to see people talking about artificial intelligence (AI). It’s in the ...
Accelerating data for NVIDIA GPUs
These days, most AI and big data workloads need more compute power and memory than one node can provide. As both the number of computing nodes and the horsepower of processors and GPUs increases, so does the demand for I/O bandwidth. What was once a ...
Game-changing innovation for AI and big data from IBM Storage
Artificial intelligence (AI) is already a world-changing driver of business today and will ...
Storage made simple for modern data
When we speak with clients, their top storage priorities are very consistent: Storing dramatically more data from novel sources, gaining new business insight and increasing revenue through the use of AI and big data technologies applied to that data...
Exploring the motivation for hybrid cloud–an industry perspective
This is part 2 in a 6-part series on storage for hybrid cloud. In Part 1 I set the stage–...
Empowering development productivity with easier and secure infrastructure
From time to time, we invite industry thought leaders to share their opinions and insights on ...
Top IBM Power Systems myths: “IBM AIX is dead and Unix isn’t relevant in today’s market” (part 2)
In part 1 of this series, we started to look at the myth that IBM AIX and Unix are no longer ...