Our Innovation Quadrant provides a snapshot of the average funding and average age for the different Artificial Intelligence categories and how they compare with one another.
Heavyweights: Categories with high average funding and high average age. These categories are comprised of companies that have reached maturity with significant financing.
Established: Categories with low average funding and high average age. These categories are comprised of companies that have reached maturity with less financing.
Disruptors: Categories with high average funding and low average age. These categories are comprised of companies that are less mature with significant financing.
Pioneers: Categories with low average funding and low average age. These categories are comprised of companies that are less mature with earlier stages of financing.
The definitions of the Artificial Intelligence categories represented in the above Innovation Quadrant are as follows:
Deep Learning/Machine Learning (Platforms): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data.
Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases. Examples include using machine learning technology to detect banking fraud or to identify the top retail leads.
Natural Language Processing: Companies that build algorithms that process human language input and convert it into understandable representations. Examples include automated narrative generation and mining text into data.
Speech Recognition: Companies that process sound clips of human speech, identify the exact words, and derive meaning from them. Examples include software that detects voice commands and translates them into actionable data.
Computer Vision/Image Recognition (Platforms): Companies that build technology that process and analyze images to derive information and recognize objects from them. Examples include visual search platforms and image tagging APIs for developers.
Computer Vision/Image Recognition (Applications): Companies that utilize technology that process images in vertically specific use cases. Examples include software that recognizes faces or enables one to search for a retail item by taking a picture.
Gesture Control: Companies that enable one to interact and communicate with computers through their gestures. Examples include software that enables one to control video game avatars through body motion, or to operate computers and television through hand gestures alone.
Virtual Assistants: Software agents that perform everyday tasks and services for an individual based on feedback and commands. Examples include customer service agents on websites and personal assistant apps that help one with managing calendar events, etc.
Smart Robots: Robots that can learn from their experience and act autonomously based on the conditions of their environment. Examples include home robots that could react to people’s emotions in their interactions and retail robots that help customers find items in stores.
Personalized Recommendation Engines: Software that predicts the preferences and interests of users for items such as movies or restaurants, and delivers personalized recommendations to them. Examples include music recommendation apps and restaurant recommendation websites that deliver their recommendations based on one’s past selections.
Context Aware Computing: Software that automatically becomes aware of its environment and its context of use, such as location, orientation, lighting, and adapts its behavior accordingly. Examples include apps that light up when detecting darkness in the environment.
Speech to Speech Translation: Software which recognizes and translates human speech in one language into another language automatically and instantly. Examples include software that translates video chats and webinars into multiple languages automatically and in real-time.
Video Automatic Content Recognition: Software that compares a sampling of video content with a source content file to identify the content through its unique characteristics. Examples include software that detects copyrighted material in user-uploaded videos by comparing them against copyrighted material.
We are currently tracking 1498 Artificial Intelligence companies in 13 categories across 73 countries, with a total of $9 Billion in funding. Click hereto learn more about the full Artificial Intelligence landscape report and database.