The last decade of tech was to a large part defined by the advent of Deep Supervised Learning (DL). The availability of cheap data at scale, computational power, and researcher interest have made it the de-facto school of algorithms used for most pattern recognition problems. Face recognition on social media, product recommendations on sites, voice assistants like Google Assistant, Alexa, and Siri are some examples largely powered by DL. The issue with deep learning is that the resources that led to its rise are also giving rise to inequities. Today, it is tough for startups to beat'big tech' like Apple, Google, Amazon, and Microsoft in deep learning through better research capabilities or better data.