A Deep Dive in the Venture Landscape of Artificial Intelligence and Machine Learning Ajit Nazre & Rahul Garg Artificial Intelligence (AI) has been around since the term was coined in 1955 by John McCarthy. AI is on its third life after the first one ending in the 70s when funding from US federal sources dried up and the second one ending after the crash of the LISP machine market. It appears that in its third reincarnation that started in the 90s, AI is here to stay for the long run. The field of AI has expanded to various fields as shown in the classification (chart 1). Thanks to advances in computing, networks, storage, big data, and neuroscience AI is getting more accurate in prediction. Its applications are ubiquitous in both consumer and industrial settings. We use it daily on our smart phone in the form of automatic word completion in the text editor and face recognition to log on. It is seen in toy drones, home help robots and self-parking cars. Industrial applications are common place from aerospace and agriculture to recruiting and wealth-management. The US has become the hotbed of innovation in AI and has captured a leadership position in terms of university research, patents, startups funded, commercial and military use. In 2014, IBM and Microsoft had more patents granted in AI and ML in 2014 than all other tech companies (chart 2). Chart 1: Classification of AI
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A Deep Dive in the Venture Landscape of Artificial Intelligence and Machine Learning
Ajit Nazre amp Rahul Garg
Artificial Intelligence (AI) has been around since the term was coined in 1955 by John McCarthy AI is on
its third life after the first one ending in the 70s when funding from US federal sources dried up and the
second one ending after the crash of the LISP machine market It appears that in its third reincarnation
that started in the 90s AI is here to stay for the long run The field of AI has expanded to various fields
as shown in the classification (chart 1)
Thanks to advances in computing networks storage big data and neuroscience AI is getting more
accurate in prediction Its applications are ubiquitous in both consumer and industrial settings We use it
daily on our smart phone in the form of automatic word completion in the text editor and face
recognition to log on It is seen in toy drones home help robots and self-parking cars Industrial
applications are common place from aerospace and agriculture to recruiting and wealth-management
The US has become the hotbed of innovation in AI and has captured a leadership position in terms of
university research patents startups funded commercial and military use In 2014 IBM and Microsoft
had more patents granted in AI and ML in 2014 than all other tech companies (chart 2)
Chart 1 Classification of AI
In order to better understand which areas within AI are seeing most disruption we created a database of
2800 companies that are innovating in all the areas (as shown in chart 1)of AI and ML (machine
learning) For the study we also included areas that span multiple fields such as drones image
recognition and augmented reality We winnowed the 2800 companies down to 1781 active companies
depending on whether they were acquired closed down or went bankrupt More than half of the active
1781 companies are located in the US (chart 3)
Chart 2 Patents Granted in 2014 by USPTO
Chart 3 Active AI Companies by Country 2015
We further narrowed the list of companies based on who had received funding Only 18 (312
companies) of the 1781 active companies have funding gt$100k Out of the 312 funded companies
nearly 40 are located in the San Francisco Bay area with more than 70 in North America (chart 4)
A vast majority of the funded companies are still pre series A or in other words in early stages of
development (chart 5)
Chart 4 Funded Companies by Location
Chart 5 Funded Companies by stage of Funding
Venture funding in AI ML companies increased 300 in 2014 as compared to 2013 (chart 6)
Intel Capital Google Ventures Khosla Ventures and Two Sigma Ventures are the most active VCs
investing in the area (chart 7)
Chart 6 Venture Funding in AI and ML over time
Chart 7 Most Active Venture Firms in AI and ML
Machine learning drones robotics augmented reality and image recognition are the most actively
funded areas (chart 8)
70 of AI and ML innovation is targeted toward enterprise applications (chart 9) across a wide range of
industries from Aerospace to Wealth management (chart 10)Surprisingly ldquoAI ML as a servicerdquo is the
second most prevalent application area after industrial automation
Chart 8 Funded Companies in AI ML by Field of Innovation
Chart 9 Funded Companies by Application Focus
Acquisitions are also happening at a brisk pace and Google is the most acquisitive tech company in the
space (21 acquisitions) followed by Facebook (10) and Apple (6) (chart 11)
Chart 10 Funded Companies in AI ML by Application Vertical
Chart 11 Acquisition Activity in AI ML
There is a lot of literature and press covering various uses of AI and ML We have compiled a list of
companies that we thought stood out in the following verticals
Aerospace Atheer Labs Augmate Infinity AR Total Immersion Vuzix
Agriculture Blue River Farmlogs Greensight Mavrx Pulsepod Terravion
Background Checks Onfido
Communications Lexifone
Customer Care Agnitio DigitalGenius Expect Labs Verbio Voicebase Voiceitt VoiceVault