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Prof. Dr. Ralf Herbrich | Artificial Intelligence and Energy | Rise of AI Conference 2023
Explore the intersection of artificial intelligence and energy efficiency, discovering how designing energy-conscious AI systems can lead to significant long-term savings and reduced waste, while balancing accuracy, trust, and cost considerations.
- Artificial intelligence (AI) is not only about making mistakes, but also about being energy-efficient, and we need to consider this aspect when designing AI systems.
- Battery energy density is crucial, and the concept of energy density is not only important for electric vehicles but also for various applications.
- The traditional AI approach of trying to get the best possible accuracy is not necessarily the best approach, as it can lead to a waste of energy.
- Instead, we should focus on finding AI models that are energy-efficient, as this can lead to significant savings in the long run.
- There are three areas where AI can play a role in terms of energy: predicting where sunshine is, optimizing the lifetime of batteries, and improving the efficiency of energy storage solutions.
- In the context of energy efficiency, approximate computing can be a promising approach, as it can reduce the number of calculations needed to achieve a certain level of accuracy.
- Trust is a crucial aspect when it comes to AI, as we need to trust the predictions made by AI systems and be aware of the potential risks associated with these predictions.
- In terms of costs, it is important to consider not only the costs of energy but also the costs of storage solutions and the costs associated with maintaining and replacing batteries.
- When it comes to AI and energy, it is important to consider the long-term impact of our decisions, as the energy required to train AI models can be significant and can lead to a waste of resources.
- Finally, we need to think about the trade-offs between energy efficiency, accuracy, and trust when designing AI systems.