The AI Renaissance: From small starts to a Brave New World – Onur Karakaslar
In the 1960s, perceptrons took their first steps with Hinton and his colleagues through backpropagation. However, AlexNet was the first to show the world how powerful these methods could truly be.
ImageNet, a massive dataset compiled over years from millions of different objects, had been used until 2012 by extracting object features manually. Algorithms like SIFT, for instance, were widely utilized when I first encountered neural networks in 2015.
However, AlexNet completely overturned this approach. At the annual ImageNet competition in 2012, AlexNet revolutionized the field, halving the error rates of previous algorithms and winning the competition. It was a pivotal moment, marking the end of the quiet era for neural networks since the 1980s. Just one year later, all groups participating in the competition were using neural networks.
This caused a wake-up call for major companies, sparking a race to recruit machine learning and AI experts. Google acquired DeepMind and gave it autonomy, while Facebook (then known as Facebook Artificial Intelligence Research, or FAIR) established its own research division. Most companies began to focus on open-source research, realizing that open-source code fosters a self-sustaining ecosystem.
