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19min chapter
"AI should NOT be regulated at all!" - Prof. Pedro Domingos
Machine Learning Street Talk (MLST)
Mastering Machine Learning: The Quest for a Universal Algorithm
This chapter explores the concept of a 'master algorithm' in machine learning, likening it to a universal solution capable of addressing diverse problems. The discussion contrasts symbolic AI with other learning paradigms, emphasizing the need for a formal foundation and integration of logic with statistical methods. Additionally, the chapter highlights the evolution of AI architecture and introduces symmetry-based learning as a framework to enhance understanding of language complexities.
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