On the Measure of Intelligence

The paper challenges conventional approaches to measuring intelligence in machines, arguing for a focus on generalization and adaptability rather than narrow task-specific skills. It introduces a new benchmark called ARC, designed to measure human-like general intelligence and program synthesis through tasks requiring abstract reasoning and problem-solving abilities.

Key takeaways for engineers/specialists include the importance of skill-acquisition efficiency in measuring intelligence, the emphasis on building systems with adaptability and generalization capabilities, and the potential impact of such research on areas like education, healthcare, and robotics.

Read full paper: https://arxiv.org/abs/1911.01547

Tags: Artificial Intelligence, Machine Learning, Explainable AI