Introduction to GPUs for Data Analytics

Chapter 7. Cognitive Computing: The Future of Analytics

Cognitive computing, which seeks to simulate human thought and reasoning in real time, could be considered the ultimate goal of business intelligence (BI), and IBM’s Watson supercomputer has demonstrated that this goal can indeed be achieved with existing technology.

The real question is this: when will cognitive computing become practical and affordable for most organizations?

With the advent of the GPU, the Cognitive Era of computing is now upon us. Converging streaming analytics with artificial intelligence (AI) and other analytical processes in various ways holds the potential to make real-time, human-like cognition a reality. Such “speed of thought” analyses would not be practical—or even possible—were it not for the unprecedented price and performance afforded by massively parallel processing of the GPU.

The GPU’s Role in Cognitive Computing

If cognitive computing is not real-time, it’s not really cognitive computing. After all, without the ability to chime in on Jeopardy! before its opponents did (sometimes before the answer was read fully), Watson could not have scored a single point, let alone win. And the most cost-effective way to make cognitive computing real-time today is to use GPU acceleration.

Cognitive computing applications will need to utilize the full spectrum of analytical processes-business intelligence, AI, machine learning, deep learning, natural-language processing, text search and analytics, pattern ...