Limits and Innovations in Deep Learning

This chapter explores the limitations and computational demands of deep learning advancements, emphasizing the need for more efficient models. It also critiques the notion that deep learning is nearing its limits, showcasing ongoing innovations and the varying accuracy of human versus machine classifications in tasks like image recognition and translation.