Innovative Framework Advances AI Tech
By Mat Dirjish
At CES, LG reveals what it describes as a new framework for advancing artificial intelligence (AI) technology. The framework is in the form of a presentation, delivered by LG Electronics President and Chief Technology Officer Dr. I.P. Park.
Dr. Park unveils the framework for the future of AI development in a presentation titled, “Levels of AI Experience: the Future of AI and the Human Experience.” The conceptual framework is an ambitious vision of transforming daily experiences by connecting all aspects of people’s lives with intelligent touchpoints.
The plan described by Dr. Park creates a clear roadmap for AI where the ultimate destination is a cohesive system comprising products and services that can make anywhere feel like home. He explains that, amidst a wave of AI-related ideas and concepts, it is important to share a structured framework for the development of AI across the industry so that designers create a meaningful impact on the lives of users.
Dr. Park is joined by Jean-François Gagné, co-founder and CEO of Element AI, a Montreal-based company noted for effective AI implementation. Together, they explain four levels of AI experience (AIX): efficiency, personalization, reasoning, and exploration.
- Efficiency is where specific device and system functions can be automated through simple commands. At this level, AI automatically adjusts performance in relation to pre-established sensory input parameters, maximizing efficiency in user interactions.
- Personalization focuses on pattern learning to optimize and personalize device functions.
- Reasoning envisions an AI that uses causality learning through the collective intelligence of a system made up of different devices and services. By perceiving the cause of certain patterns and behaviors, AI at this level can better predict and promote positive outcomes.
- Exploration, though still far in the future, is the ultimate destination for AI. Using a concept called Experimental Learning based on the scientific method, AI-enabled systems will be able to develop new capabilities through forming and testing hypotheses to uncover new inferences, enabling them to learn and improve.
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