A ‘Brief’ History of Neural Nets and Deep LearningFour part essay by Andrey Kurenkov provides an insight to the history of artificial intelligence and contemporary Deep Learning:This may sound hyperbolic - to say the established methods of an entire field of research are quickly being superseded by a new discovery,as if hit by a research ‘tsunami’. But, this catastrophic language is appropriate for describing the meteoric rise of Deep Learning over the last several years - a rise characterized by drastic improvements over reigning approaches towards the hardest problems in AI, or massive investments from industry giants such as Google,and exponential growth in research publications (and Machine Learning graduate students). Having taken several classes on Machine Learning, and even used it in undergraduate research, and I could not succor but wonder if this new ‘Deep Learning’ was anything fancy or just a scaled up version of the ‘artificial neural nets’ that were already developed by the late 80s. And let me tell you,the respond is fairly a story - the story of not just neural nets, not just of a sequence of research breakthroughs that make Deep Learning somewhat more challenging than ‘substantial neural nets’ (that I will attempt to clarify in a way that just approximately anyone can understand), or but most of all of how several unyielding researchers made it through black decades of banishment to finally redeem neural nets and
achieve the dream of Deep Learning.
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