<\/span><\/h2>\r\n\r\n\r\n\r\nThe power of AI doesn\u2019t lie in storing, labeling, and categorizing data. It lies in the ability to process a vast amount of data to make sense out of it. And for that to happen, algorithms need high computing power. So, the first requirement you need to meet is to arrange resources for computing power \u2014 which is the servers\u2019 hardware.<\/p>\r\n\r\n\r\n\r\n
The hardware consists of processors, motherboards, RAM, cooling fans, among other things. In terms of computing power, you need to zero in on the processors. That\u2019s because they largely determine how fast your AI will be.<\/p>\r\n\r\n\r\n\r\n
The two most common processors are CPU and GPU. CPUs are the most common processor since we have them on our laptops and computers. But even the best CPUs are incapable of handling complex calculations. They are reserved for the basic workload. The best processors for AI are GPUs or Graphics Processing Units. They can accelerate your AI processes by as much as 100X.<\/p>\r\n\r\n\r\n\r\n
You should look for processors with the label \u201cAI accelerator\u201d if your project demand capabilities like machine learning, neural networks, machine vision, robotics, and natural language processing.<\/p>\r\n\r\n\r\n\r\n