Artificial Intelligence: Market Overview
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.
The Rise of Robots: Market Overview
- Social: Startups here are building consumer-focused companion and entertainment robots. The most well-funded startup on this list is Anki, with $157M in equity funding from investors including Andreessen Horowitz, Two Sigma Ventures, and JPMorgan Chase & Co. China-based humanoid robotics startup UBTECH raised a $100M Series B round in Q3’16 and joined the Unicorn Club with a $1B valuation. More recently, UK-based Olly, which focused on building a personal, interactive robot, raised $10M in Series A funding from Alliance Capital Ventures and China-based Lightning Capital. Social robots differ from service robots (listed below), which perform household chores.
- Bionics/Rehab: Startups in this sector include those building exoskeletons, a type of body armor that aids in movement, as well as aiding patients with rehabilitation services. One of the more well-funded companies is California-based AlterG, which has raised over $35M in equity funding so far from investors including Oxford Finance, Silicon Valley Bank, and Versant Ventures, and has developed a wearable bionic leg.
- Surgical: This category includes startups building robotics surgery-assistance technology. Auris Surgical Robots is one of the most well-funded robotics companies, having raised over $230M in growth equity from investors including Lux Capital, Highland Capital Partners, and Mithril Capital Management. This year, they also made a public-to-private acquisition of Hansen Medical, a medical robotics startup that was previously funded by VCs including Skyline Ventures, Prospect Venture Partners, and De Novo Ventures.
- Industrial: Our industrial robotics category includes manufacturing, warehouse, packaging, sorting, inspection, and quality testing robotics. Industrial robotics is the most crowded category, as we mentioned in our market map of 80+ robotics startups. Pittsburgh-based Seegrid raised a $14M round this year, followed by $12M corporate minority round from Pittsburgh-based supermarket Giant Eagle. Other startups that raised equity funds this year include Japan-based Life Robotics and China-based Quotient Kinematics Machine.
- Drones/UAVs: This category includes drones for inspection and delivery. Some of the most well-funded drone startups are 3D Robotics, which built the site scanning drone Solo for site inspections, and China-based DJI Innovations, which caters to industries including agriculture and filmmaking.
- Education: Robots in this category are focused on teaching children how to code. California-based Wonder Workshop raised $20M in Series B in Q3’16 from VCs including CRV, Learn Capital, and Madrona Venture Group. With $40M in equity funding, it is the most well-funded educational robotics startup, with backing from VCs from China (TCL Capital) and Hong Kong (Bright Success Capital) as well.
- Service (Consumer): Startups here include those developing consumer-focused service robots that perform household chores like cleaning and cooking. It also includes China-based personal transportation robot Ninebot (which acquired US-based Segway), and robotic infant seat maker 4Moms (which raised over $40M in Series F in Q3’14 from investors including Bain Capital Ventures and Castanea Partners).
- Service (Medical): This category includes hospital cleaning robot Xenex Disinfection Services, and Pennsylvania-based Aethon, which has developed a transportation robot for hospitals.
- Service (Other): This category includes Intel Capital-backed Savioke, which has developed a service robot for the hospitality industry; robotic restaurant Spyce Kitchen, which raised $2.6M this year from Rough Draft Ventures; and ground delivery robot Marble, which was seed-funded this year by Eclipse Ventures, Lemnos Labs and Promus Ventures.
- Security: Rapyuta Robotics is building a “multi-robotic system” with machines that can interact with each other to prevent crime. It is backed by corporate venture capital group Fuji Startup Ventures in Japan, and recently raised $10M in Series A from Japan-based asset management firm SBI Investment. Another startup, California-based Knightscope, raised $5M in Series B funding in Q4’15.
- VC-backed exits: This category only includes 1st exits since 2012. Amazon acquired Kiva Systems in 2012. The same year, the SoftBank Group acquired a majority stake in France’s Aldebaran Robotics. A detailed timeline of major robotics M&A can be found here.
- Most active VCs: The most active VC in robotics since 2012 has been High-Tech Gruenderfonds. The Germany-based VC has backed more than 5 unique companies during this period, including rehabilitation robot Reactive Robotics and industrial robots REVOBOTIK and Bionic Robotics. Eclipse Ventures is the 2nd most active VC on our list, having backed companies like Modbot, Rise Robotics, and Clearpath Robotics.
See also
How to build a robot that “sees” with $100 and TensorFlow
Architecture of the object-recognizing robot. Image courtesy of Lukas Biewald.
This is the first Adidas shoe made almost entirely by robots
[youtube https://www.youtube.com/watch?v=FVpfVdXxcCA]
Forrester’s Top Emerging Technologies To Watch: 2017-2021
As a refresh to my 2014 blog and report, here are the next 15 emerging technologies Forrester thinks you need to follow closely. We organize this year’s list into three groups — systems of engagement technologies will help you become customer-led, systems of insight technologies will help you become insights-driven, and supporting technologies will help you become fast and connected.
Why these 15? You might have noticed a few glaring omissions. Certainly blockchain has garnered a lot of attention; and 3D printing is on most of our competitors’ lists. The answer goes back to being customer led, insights driven, fast, and connected. Those of you that follow our research will recognize these as the four principles of customer obsessed operations. The technologies we selected will have the biggest impact on your ability to win, serve and retain customers whose expectations of service through technology are only going up. Furthermore, our list focuses on those technologies that will have the biggest business impact in the next five years. We think blockchain’s big impact outside of financial services, for example, is further out so it didn’t make our list, even though it is important. Maybe by 2018, when I update our list next.
Since I don’t have room here for details about all of our technologies, I’ll focus on five that we think have the potential to change the world. That’s ? of our list by the way – which means a lot of change is coming; it’s time to make your technology bets.
- IoT software and solutions bring customer engagement potential within reach. Theses software platforms and solutions act as a bridge between highly specialized sensor, actuator, compute, and networking technology for real-world objects and related business software. This technology gives firms visibility into and control of customer and operational realities. By 2021, technology for specific use cases will be mature, but protocol diversity, immature standards and the need for organizational changes will still stymie or delay many firms. …
- Intelligent agents coupled with AI/cogntive technologies will automate engagement and solve tasks. Intelligent agents represent a set of AI-powered solutions that understand users’ behavior and are discerning enough to interpret needs and make decisions on their behalf. By 2021, we think that automation, supported by intelligent software agents drivng by an evolution in AI and cogntive technology will have eliminated an net 6% of US jobs. But the loss won’t be uniform. There will be an 11% loss of jobs that are vulnerable and a 5% creation of jobs in industries that stand to benefit. …
- Augmented reality overlays digital information and experiences on the physical world using combinations of cameras and displays. While we cover both VR and AR, we find that while a lot of attention has been placed on VR, AR has more play, for enteprises in the short term and eventually for consumers as well. By 2021, we will be fully into a transition period between separated and tightly blended physical and digital experiences in our work and lives. …
- Hybrid wireless technology will eventually ereate connected cverything. Hybrid wireless technologies are the interfaces and software that allow devices to simultaneously leverage and translate between two or more different wireless providers, protocols, and frequency bands, such as light, radio, Wi-Fi, cellular, and Sigfox. By 2021, a virtual network infrastructure will emerge to weave together wireless technologies that globally connect IoT and customer engagement platforms.
What AI Researchers Say About When Superintelligence will Arrive
To get a more accurate assessment of the opinion of leading researchers in the field, I turned to the Fellows of the American Association for Artificial Intelligence, a group of researchers who are recognized as having made significant, sustained contributions to the field.
In early March 2016, AAAI sent out an anonymous survey on my behalf, posing the following question to 193 fellows:
“In his book, Nick Bostrom has defined Superintelligence as ‘an intellect that is much smarter than the best human brains in practically every field, including scientific creativity, general wisdom and social skills.’ When do you think we will achieve Superintelligence?”
…In essence, according to 92.5 percent of the respondents, superintelligence is beyond the foreseeable horizon.
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