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Dr. Leif-Nissen Lundbæk & Andreas Grün | Responsible AI for carbon neutrality | Rise of AI 2023
Discover how responsible AI can drive carbon neutrality, reducing energy consumption and improving user engagement through personalized recommendations, efficient models, and transparent algorithms.
- AI can reduce energy consumption of platforms by 98%
- Looking at individual user interactions, rather than masses of data, can help reduce data processing and energy consumption
- Specialized algorithms and data structures can make a significant impact on energy efficiency
- The concept of “green recommendations” prioritizes user preferences over popular content to reduce energy consumption
- The team used a sequential model that is highly adaptive to user behavior, and a minimalist approach to achieve better results
- Carbon neutrality is a sustainability goal for platforms
- The cold start problem is a major challenge in recommendation systems, where AI can help with user profile generation
- Explainability is key in AI systems, allowing users to understand what drives recommendations
- Zero-shot learning and few-shot learning can help solve data scarcity and quality issues
- Efficient models can process a large volume of data while reducing energy consumption and computational resources
- Public service media broadcasting platforms, such as MediaTick, aim to reduce energy consumption through AI-driven solutions
- AI-powered systems can improve user engagement by 20%, reducing the fear of recommendation algorithms
- Sustainability is a priority in AI development, with focuses on transparency, explainability, and efficiency
- Personalization through AI can increase user engagement and energy efficiency, but also requires careful management of user data
- Language models are key to AI development, allowing for more efficient and accurate processing of large volumes of data