As an undergraduate, I was initially exposed to neural networks in 1990. Many individuals in the AI field were enthused about the possibilities of neural networks at the time, which were remarkable but could not yet do crucial, real-world tasks. I was ecstatic as well! My senior thesis focused on leveraging parallel computation to train neural networks, with the assumption that we only required 32X more computational power to get there. I was completely wrong. We required a million times the processing power at the time.