Part 6/14:
Frank Rosenblatt’s introduction of artificial neuronal networks in 1958 exemplifies attempts to replicate this structure. His work used transistors in a layered architecture that learned to identify patterns through trial and error. The consistency of this model paved the way for future innovations in machine learning. In subsequent years, researchers like Yann LeCun expanded on this methodology to tackle real-world tasks, enabling networks to discern handwritten digits through hierarchical layers detecting edges and increasingly complex patterns.