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The Hidden Costs of AI
In the rush to stay at the forefront of technology, businesses are increasingly integrating Artificial Intelligence (AI) into their operations. While AI promises enhanced efficiency and groundbreaking capabilities, it also brings significant challenges, notably in terms of power consumption and the quality of design decisions. This article explores the hidden costs of AI, focusing on its impact on power infrastructure and the potential pitfalls of using AI to appear “cutting edge” without sufficient justification.
Escalating Power Needs
AI technologies, particularly during the inferencing phase, can be exceedingly power-hungry. Inferencing, the process of applying a trained AI model to new data, requires substantial computational resources, especially for complex models such as deep neural networks. This high demand for power does not merely translate to increased electricity costs but leads to increased strain on our energy infrastructure. In talking with data centers across the nation, there is a lack of power that is available to customers due to the heightened demand brought on by increased AI workloads.
As AI becomes ubiquitous, the aggregate impact could lead to an overwhelming demand on power grids, necessitating substantial upgrades to accommodate this new technology wave. I thought Electric cars were straining the power…
