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AI technology is known for its significant energy consumption, comparable to that of small countries. However, not all AI systems have the same power demands; industrial AI, in particular, operates with much lower energy requirements. This efficiency is crucial as companies increasingly adopt AI to optimize processes and enhance sustainability efforts.
The article highlights the stark contrast between generalized AI models, like large language models, and industrial AI applications. While the former can consume vast amounts of energy, industrial AI leverages domain expertise to minimize power usage and improve operational efficiency. This shift not only aids in reducing costs but also contributes to lower carbon emissions, aligning with global sustainability goals.
• Industrial AI has significantly lower power demands than generalized AI models.
• AI's energy consumption could rise dramatically, impacting carbon emissions.
Industrial AI focuses on specific applications, requiring less data and power for training.
Energy efficiency in AI applications is crucial for reducing operational costs and emissions.
Large language models, like GPT, demand extensive energy for training and operation.
AspenTech specializes in industrial AI solutions that enhance energy efficiency and operational performance.
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