Source: Deep Learning on Medium
Over the last few years, the emergence of the machine intelligence in all spheres of human life became impossible to ignore. Today artificial intelligence powers the thermostats and voice assistants in our homes and phones, suggests us best routes while driving, and makes pictures we take look better. Moreover, we ourselves increasingly leverage various AI capabilities to augment our work and daily lives to become more productive. Many things that we take for granted, like receiving suggestions for similar items while shopping, translating texts, or simply searching the web, would not be possible without powerful machine learning algorithms running in the backend.
Still, while there have been a lot of exciting advancements in AI space, or maybe exactly because of how quickly it’s been evolving, it remains hard to familiarize oneself or to stay up-to-date with all the latest developments. While there is already a multitude of AI-related resources on the web, a comprehensive taxonomy of the industry, sliced by key products, people, institutions, and technologies, is yet to be developed. We find that creating such a taxonomy would go a long way to make it easier for industry professionals, technology evangelists, or simply anyone interested in learning more about machine intelligence, to navigate the field.
At Evolution One, we are inspired by this idea of building a comprehensive guide that would aggregate and structure the body of knowledge related to the industry, and serve the AI community. In this work, we focus on three areas: development of the clear-cut taxonomy of the field, constant monitoring of recent developments, and focused deep dives into specific topics.
Monthly newsletter, featuring editorial opinions on the top highlights structured by category (Products, People, Institutions, Technologies); first issue coming end of February 2019
- Best reads in AI of 2018; coming February 9th, 2019
- Key technological advancements in AI of the last 18 months; coming end of February 2019
- Key People & Technologies: we start building our taxonomy by mapping key contributors to the key technologies in computer vision (CV) and natural language processing (NLP)
- Products & Institutions: coming later
Originally published at evolutionone.ai.