Artificial Intelligence Q1 Update in 15 Visuals

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We at Venture Scanner are tracking 957 Artificial Intelligence companies across 13 categories, with a combined funding amount of $4.8 Billion. The 15 visuals below summarize the current state of Artificial Intelligence.

1. Artificial Intelligence Market Overview

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We organize Artificial Intelligence into the 13 categories listed below:

Deep Learning/Machine Learning (General): 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 (General): 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.

Natural Language Processing (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 (General): 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 Personal 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.

Recommendation Engines and Collaborative Filtering: 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.

2. Company Count by Artificial Intelligence Category

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The above graph summarizes the number of companies in each Artificial Intelligence category to show which categories are dominating the current market. The Machine Learning (Applications) category is leading the way with 263 companies, followed by the Natural Language Processing category with 154 companies.

3. Funding by Artificial Intelligence Category

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The above graph summarizes the total amount of funding in each Artificial Intelligence category. The Machine Learning (Applications) category is leading the market with over $2B in total funding, which is 3X the total funding of the second highest category, Natural Language Processing with $662M.

4. Venture Investing in Artificial Intelligence

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The above graph compares the total venture funding in each Artificial Intelligence category to the number of companies in the category. The Machine Learning (Applications) category is leading in both stats with over $2B in funding and 263 companies. Natural Language Processing is the runner-up in both stats with $662M in funding and 154 companies.

5. Artificial Intelligence Total Funding by Year

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The above graph summarizes the total funding raised by Artificial Intelligence companies each year. 2015 was the best year in Artificial Intelligence funding with almost $1.2B raised, with 2014 in the second place with a total of $1B raised.

6. Average Funding by Artificial Intelligence Category

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The above graph summarizes the average company funding in each Artificial Intelligence category. The Machine Learning (Applications) category leads the market with $17M in funding per company, followed by the Smart Robots and Gesture Control categories each with about $14M in funding per company.

7. Average Age by Artificial Intelligence Category

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The above graph summarizes the average age of companies in each Artificial Intelligence category. Speech to Speech Translation ranks as the most mature Artificial Intelligence category with an average age of 13 years per company, which is more than 1.5X the average age of the three runner-up categories (Gesture Control, Video Content Recognition, and Speech Recognition, each with an average age of about 8 years per company).

8. Median Age by Artificial Intelligence Category

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The above graph summarizes the median age of companies in each Artificial Intelligence category. Video Content Recognition ranks as the most mature Artificial Intelligence category with a median age of 7.8 years per company, followed by Speech to Speech Translation with a median age of 7.2 years per company.

9. Artificial Intelligence Company Count by Country

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The above map shows the number of Artificial Intelligence companies located in different countries. The United States ranks as the top country with 499 Artificial Intelligence companies, with the United Kingdom at a distant second with 60.

10. Artificial Intelligence VC Funding by Country

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The above map shows the amount of Artificial Intelligence venture capital funding in different countries. The United States has the most Artificial Intelligence VC funding at $4.2B, followed by Switzerland at $234M.

11. Artificial Intelligence Companies Founded by Year

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The above graph summarizes the number of Artificial Intelligence companies founded in a certain year. 2013 ranks as the top year with 118 Artificial Intelligence companies founded, followed by 2012 with 103 companies founded.

12. Artificial Intelligence Funding by Vintage Year

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The above graph summarizes the total amount of funding raised by the Artificial Intelligence companies founded in a certain year. Artificial Intelligence companies founded in 2010 have raised the most funding at $566M, with those founded in 2012 at a close second with $556M.

13. Artificial Intelligence Headcount Distribution

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The above graph summarizes the percentage of Artificial Intelligence companies with a certain employee headcount range. Companies with 1–50 employees make up almost 90% of the market.

14. Number of Artificial Intelligence Investments by Selected Investors

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The above graph summarizes the total number of investment rounds Artificial Intelligence investors participated in. Accel outperform all of its peers, having made 23 investments into Artificial Intelligence companies. New Enterprise Associates is the runner-up with 18 investments.

15. Number of Artificial Intelligence Companies Backed by Selected Investors

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The above graph summarizes the number of unique Artificial Intelligence companies funded by selected investors. Accel takes the top spot by having invested in a total of 20 unique Artificial Intelligence companies, which is almost 1.5X the number of companies invested by the runner-up, Intel Capital (14 companies).

As Artificial Intelligence continues to grow, so too will its moving parts. We hope this post provides some big picture clarity on this booming industry.

Note: If you missed it, you can also read our FinTech Q1 Update in 15 Visuals.

Venture Scanner is your platform for startup landscapes, data, and research. If you would like access to the full Artificial Intelligence landscape and dataset, visit www.venturescanner.com/artificial-intelligence or reach out to info@venturescanner.com.

Number of Investments by Top Artificial Intelligence Investors

The following infographic summarizes the number of companies invested by the top Artificial Intelligence investors. You could see that Intel Capital is in the lead by having invested in 16 companies, followed by Techstars which invested in 14 companies. At Venture Scanner, we are currently tracking over 897 Artificial Intelligence companies in 13 categories across 66 countries, with a total of $3.98 Billion in funding. To see the full list of 897 Artificial Intelligence companies, contact us using the form on www.venturescanner.com.

Artificial Intelligence investor count

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 info@venturescanner.com.

Artificial Intelligence At a Glance

The following infographic summarizes the Artificial Intelligence market and all of its key metrics at a glance. You could see that it has 13 categories, 910 companies, and an average funding of $10 Million per company. At Venture Scanner, we are currently tracking over 910 Artificial Intelligence companies in 13 categories across 63 countries, with a total of $3.68 Billion in funding. To see the full list of 910 Artificial Intelligence startups, contact us using the form on www.venturescanner.com.

Artificial Intelligence At a Glance
Artificial Intelligence At a Glance

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 info@venturescanner.com.

Artificial Intelligence Company Total Funding By Vintage Year

The following infographic summarizes Artificial Intelligence companies’ total funding by the vintage year they were founded in. You could see that Artificial Intelligence companies founded in 2007 and 2008 are in the lead by raising a total of $504 Million funding up to date. At Venture Scanner, we are currently tracking over 880 Artificial Intelligence companies in 13 categories across 62 countries, with a total of $3.07 Billion in funding. To see the full list of 880 Artificial Intelligence companies, contact us using the form on www.venturescanner.com.

Artificial Intelligence Vintage Year Graph
Artificial Intelligence Vintage Year Graph

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 info@venturescanner.com.

The State of Artificial Intelligence in Six Visuals

We cover many emerging markets in the startup ecosystem. Previously, we published posts that summarized Financial Technology, Internet of ThingsBitcoin, 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:

  1. Market Overview: Breakdown of Artificial Intelligence startup list into categories.
  2. Number of Companies Per Category: Bar graph summarizing the number of companies in each Artificial Intelligence category.
  3. Average Funding By Category: Bar graph summarizing average company funding per Artificial Intelligence category.
  4. Venture Funding in Artificial Intelligence: Graph comparing total venture funding in Artificial Intelligence to the number of companies in each category.
  5. Global Breakdown of Artificial Intelligence: Heat map indicating where Artificial Intelligence companies exist.
  6. Median Age of Artificial Intelligence Categories: Bar graph of each Artificial Intelligence category by median age.

1. Artificial Intelligence Market Overview

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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

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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

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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

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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

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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

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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 info@venturescanner.com.

Where in the World is 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. We are currently tracking over 857 Artificial Intelligence companies in 13 categories, with a total of $2.75 Billion in funding. To get a better understanding of the AI sector check out our post entitled “Making Sense of the Artificial Intelligence Ecosystem,” which includes a category breakdown of AI! To see the full list of Artificial Intelligence companies, contact us using the form on www.venturescanner.com.

AI Heat Map
AI Heat Map

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 info@venturescanner.com.

Making Sense of the Artificial Intelligence Ecosystem

At this time, we are tracking 855 Artificial Intelligence companies across 13 categories, with a combined funding amount of $2.73B. These are companies and categories that involve anything and everything that is Artificial Intelligence. Below you’ll find our AI sector map as well as the categorical breakdown of the sector.

Artificial Intelligence Sector Map
Artificial Intelligence Sector Map

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 Transition: 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.

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 info@venturescanner.com.