Here is our Q2 2019 summary report on the artificial intelligence startup sector. The following report includes a sector overview and recent activity.
We cover many emerging markets in the startup ecosystem. Previously, we published posts that summarized Financial Technology, Internet of Things, Bitcoin, and MarTech in six visuals. This week, we do the same with Artificial Intelligence (AI). At this time, we are tracking 855 AI companies across 13 categories, with a combined funding amount of $8.75 billion. To see the full list of 855 Artificial Intelligence startups, contact us using the form on www.venturescanner.com.
The six Artificial Intelligence visuals below help make sense of this dynamic market:
- Market Overview: Breakdown of Artificial Intelligence startup list into categories.
- Number of Companies Per Category: Bar graph summarizing the number of companies in each Artificial Intelligence category.
- Average Funding By Category: Bar graph summarizing average company funding per Artificial Intelligence category.
- Venture Funding in Artificial Intelligence: Graph comparing total venture funding in Artificial Intelligence to the number of companies in each category.
- Global Breakdown of Artificial Intelligence: Heat map indicating where Artificial Intelligence companies exist.
- Median Age of Artificial Intelligence Categories: Bar graph of each Artificial Intelligence category by median age.
1. Artificial Intelligence Market Overview
Deep Learning/Machine Learning Applications: Machine learning is the technology of computer algorithms that operate based on its learnings from existing data. Deep learning is a subset of machine learning that focuses on deeply layered neural networks. The following companies utilize deep learning/machine learning technology in a specific way or use-case in their products.
Computer Vision/Image Recognition: Computer vision is the method of processing and analyzing images to understand and produce information from them. Image recognition is the process of scanning images to identify objects and faces. The following companies either build computer vision/image recognition technology or utilize it as the core offering in their products.
Deep Learning/Machine Learning (General): Machine learning is the technology of computer algorithms that operate based on its learning from existing data. Deep learning is a subset of machine learning that focuses on deeply layered neural networks. The following companies either build deep learning/machine learning technology or utilize it as the core offering of their products.
Natural Language Processing: Natural language processing is the method through which computers process human language input and convert into understandable representations to derive meaning from them. The following companies either build natural language processing technology or utilize it as the core offering in their products (excluding all speech recognition companies).
Smart Robots: Smart robot companies build robots that can learn from their experience and act and react autonomously based on the conditions of their environment.
Virtual Personal Assistants: Virtual personal assistants are software agents that use artificial intelligence to perform tasks and services for an individual, such as customer service, etc.
Natural Language Processing (Speech Recognition): Speech recognition is a subset of natural language processing that focuses on processing a sound clip of human speech and deriving meaning from it.
Computer Vision/Image Recognition: Computer vision is the method of processing and analyzing images to understand and produce information from them. Image recognition is the process of scanning images to identify objects and faces. The following companies utilize computer vision/image recognition technology in a specific way or use-case in their products.
Recommendation Engines and Collaborative Filtering: Recommendation engines are systems that predict the preferences and interests of users for certain items (movies, restaurants) and deliver personalized recommendations to them. Collaborative filtering is a method of predicting a user’s preferences and interests by collecting the preference information from many other similar users.
Gesture Control: Gesture control is the process through which humans interact and communicate with computers with their gestures, which are recognized and interpreted by the computers.
Video Automatic Content Recognition: Video automatic content recognition is the process through which the computer compares a sampling of video content with a source content file to identify what the content is through its unique characteristics.
Context Aware Computing: Context aware computing is the process through which computers become aware of their environment and their context of use, such as location, orientation, lighting and adapt their behavior accordingly.
Speech to Speech Translation: Speech to speech translation is the process through which human speech in one language is processed by the computer and translated into another language instantly.
2. Number of Companies Per Category
The bar graph above summarizes the number of companies in each Artificial Intelligence category to show which are dominating the current market. Currently, the “Deep Learning/Machine Learning Applications” category is leading the way with a total of 200 companies, followed by “Natural Language Processing (Speech Recognition)” with 130 companies.
3. Average Funding By Category
The bar graph above summarizes the average company funding per Artificial Intelligence category. Again, the “Deep Learning/Machine Learning Applications” category leads the way with an average of $13.8M per funded company. The SEM category includes companies that help marketers with managing and scaling their paid-search programs.
4. Venture Investing in Artificial Intelligence
The graph above compares total venture funding in Artificial Intelligence to the number of companies in each category. “Deep Learning/Machine Learning Applications” seems to be the category with the most traction.
5. Global Breakdown of Artificial Intelligence
The following infographic is an updated heat map indicating where Artificial Intelligence startups exist across 62 countries. Currently, the United States is leading the way with 415 companies. The United Kingdom is in second with 67 companies followed by Canada with 29.
6. Median Age of Artificial Intelligence Categories
The bar graph above summarizes Artificial Intelligence by median age of category. The “Speech Recognition” and “Video Content Recognition” categories have the highest median age at 8 years, followed by “Computer Vision (General)” at 6.5 years.
As Artificial Intelligence continues to develop, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.
Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you have any questions, reach out to email@example.com.
This series of articles examines innovation in the Artificial Intelligence (AI) space. Our first post provided an introduction to the Artificial Intelligence startup landscape, our second post reviewed the top trends and companies within the Smart Home Robots category, and our third post reviewed those within the Deep Learning/Machine Learning category.
We researched the Artificial Intelligence sector and identified 881 companies with $3.07 B in funding across 13 categories. To see the full list of 881 Artificial Intelligence companies, contact us using the form on www.venturescanner.com. This article demonstrates how our technology and analysts can help corporations exhaustively scan for all the relevant companies in a given sector, and provide deep dives into categories of interest to identify the best startups for them to work with.
This week we are going to examine the Image Recognition category within the Artificial Intelligence sector, which is comprised of 103 companies with $455M in funding. Image recognition is the method of processing and analyzing images to understand and produce information from them, as well as identifying objects and faces in those images.
Image Recognition Trends
Here are some of the major trends that we are seeing in the image recognition space:
- Multiple Object Recognition: Google researchers have developed a program twice as effective at locating and distinguishing multiple objects of various sizes in a single image, such as identifying different fruits in a fruit plate.
- Image Description: Teams at Stanford and Google have independently created technologies that are able to recognize and describe entire scenes of photographs and videos in prose with great accuracy.
- Gesture Recognition: NYU and Facebook AI Lab Director Yann LeCun has built a deep learning model capable of predicting the position of human limbs in images. This could lead to better gesture control and motion capture systems.
- Facial Recognition: Facebook developed a program called “DeepFace,” which could determine if two faces in photos are the same person with 97.25% accuracy.
Interesting Image Recognition Startups
We have selected a few companies to highlight, based upon our analysts’ evaluations of their traction, technology differentiation, funding amount, and founding team pedigree.
- Vicarious focuses on image recognition, segmentation, and scene parsing technologies. The company announced it can crack any type of CAPTCHA with at least 90% accuracy. It has raised $72M from notable investors including Vinod Khosla, Elon Musk, Mark Zuckerberg, and Aaron Levie.
- Clarifai specializes in deep learning algorithms for visual search. It is developing an API for developers to access its image search technology and plans to license its software to corporate users. Its notable investors include Google Ventures, Nvidia, and Qualcomm Ventures.
- Cortica specializes in deep learning image recognition technology that automatically extracts the core concept in images and videos and maps them to keywords. The company has over 100 patent applications and has raised $37.9M.
- AlchemyAPI focuses on deep-learning-based text analysis. It also offers deep-learning-based image recognition APIs for face detection/recognition, image tagging, and image link extraction. The company has raised $2M in February 2013.
- Superfish is building visual search technology focused on consumer applications. It has created 3 visual search mobile apps for animal, furniture, and product recognition. The company has raised $19.3M from notable investors including DFJ.
Venture Scanner enables corporations to research, identify, and connect with the most innovative technologies and companies. We do this through a unique combination of our data, technology, and expert analysts. If you would like to learn more about how Venture Scanner could help you research and analyze any sector, contact us at firstname.lastname@example.org