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Advancements in Deep Learning and the Journey towards Machine Intelligence
This chapter explores the evolution of neural nets and the advancements in deep learning, including pre-training, transfer learning, and zero-shot learning. It discusses the inductive bias imposed during inferencing and reflects on the growth of the field of deep learning over the past decade. The chapter also shares the authors' personal experience with a state-of-the-art foundation model, highlighting the emergence of sparks of human-level intelligence and the potential for real machine intelligence.