Cost Implications of Increasing AI Usage

The increasing prevalence of AI applications has led to greater costs associated with both training and inference. Initial assumptions from tech companies, such as Google, suggested that costs would plateau as optimizations were made; however, the reality is that as models proliferate, training and operational costs become more substantial. The rapid user growth of platforms like OpenAI highlights the mounting computational demands, particularly as they seek to push enterprise sales and expand usage among clients. This ongoing expansion creates cumulative costs that strain energy resources and raise concerns about sustainability in the AI industry.