This blog post examines the different components of the artificial intelligence (AI) ecosystem. We will illustrate what the categories of innovation are and which categories have the most companies. We will also compare the categories in terms of their funding and maturity.
Let’s start off by looking at the Sector Map. We have classified 2497 AI startups into 13 categories. They have raised $60B from 3420 investors. The Sector Map highlights the number of companies in each category. It also shows a random sampling of companies in each category.
We see that Machine Learning Applications is the largest category with 943 companies. These companies utilize self-learning algorithms to optimize vertically-specific business operations. Examples include using machine learning to detect banking fraud or to identify relevant sales leads. Some example companies are Sift Science, SparkCognition, Sumo Logic, and BenevolentAI.
Let’s now look at our Innovation Quadrant to find out the funding and maturity of these categories in relation to one another.
Our Innovation Quadrant divides the AI categories into four different quadrants.
We see that both the Pioneers and Disruptors quadrants have the most number of AI categories at 6, each accounting for 46% of all AI categories. The Speech-to-Speech Translation category has the highest average age, and the Recommendation Engines category has the highest average funding. On the other hand, the Context Aware Computing and Virtual Assistants categories are low on both average funding and age.
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