The Proof Is in the Preparation
Training an AI model might sound easy: give a neural network some data and bam, you got yourself an AI. This is far from the truth and there are numerous factors that go into developing the right model for the right job.
Developing a quality AI deployment is 90% in the prep coupled with continuous iterations and constant monitoring. Successfully developing and implementing AI systems is a complex process fraught with potential pitfalls. These shortcomings can lead to suboptimal outcomes, inefficient use of resources, and even significant challenges.