Making or Breaking AI: Grand Challenges, Opportunities and What We Might be Missing
Speaker: Eren Kurshan – New York, NY, United StatesTopic(s): Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing , Hardware, Power and Energy , Architecture, Embedded Systems and Electronics, Robotics
Abstract
Artificial Intelligence solutions face 3 Grand Challenges: (1) The Energy Challenge: An unprecedented growth in the training energy consumption is on the path to becoming ‘the limiting factor in AI progress’; (2) The Alignment Challenge: Despite the numerous guardrails and security features, jailbroken and misaligned AI is posing serious threats to the society; (3) The AGI Challenge: Making the leap to Artificial General Intelligence is considered to be a more difficult problem than narrow AI and requires novel approaches.
In this talk, we argue that system design is the key to finding solutions to all 3 seemingly unrelated grand challenges. Energy efficiency requires a paradigm shift from
the way we built AI as a software-level tool running on general purpose hardware to achieve orders of magnitude improvement needed. Similarly, one of the fundamental challenges in alignment is the fact that the human brain relies heavily on its system architecture for moral decisions. Without a system and its specialized components, feedback mechanisms, control and regulatory functions it may never be possible to achieve alignment. System design is essential in building AGI solutions from the current state of narrow AI capabilities. However, our current vision of AI lacks system-level thinking. Fixing this not only requires a paradigm shift in AI, but also a cultural shift to incorporate the learning from other computer science disciplines into the narrow AI community.
About this Lecture
Number of Slides: 60Duration: 60 minutes
Languages Available: English
Last Updated:
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