1.2 Hardware Knowledge CPU VS GPU

·CPUs are often able to handle a wide variety of tasks at a reasonable speed.?

·GPUs are often focused on one specific type of task and optimized based on that single task type.?????

Examples:?

• CPUs are first come first serve where everyone gets a ticket at a deli line with a single workstation performing all functions.??
• GPUs can run multiple activities in parallel, like a deli setup with 3 or workstations specifically set up for task types, such as cutting meat, making a sandwich, or slicing cheese. There is no need to reconfigure the workstation for every customer, hence the wait time is significantly reduced.?
• Using the example below, picture one worker at each workstation. A CPU user may be capable of doing all the work but is slower if not optimized, however, a GPU format that is optimized would require one employee per workstation to run in parallel, hence the operation and maintenance costs are typically more expensive.?

This is an important concept to plan since the volume can be a significant driver when determining how to build an AI solution. Today there currently is only one true player.

SECTION 1.3 will focus on the Hardware and Platforms utilized