A Look at the Current State of Embodied AI Companies
After a recent seminar at Stanford, I had a chat with Adj. Prof. Jerry Kaplan about artificial intelligence embodiment. The question was — who are the thinkers and companies that are really pushing AI theory? Some experts believe that for artificial intelligence (AI) or artificial general intelligence (AGI) to function peacefully and effectively in society, it needs a body. Thoughts vary on the level of embodiment, the mortality of that body, and the complexity of sensing abilities and empathy needed.
So I did some research into the current state of robots and AI embodiment. What are the clusters and trends in this area of technology? Below is a short summary of what I found. It’s not complete, so please feel free to email me with suggested updates at bethanie@stanford.edu.
Using Quid, a research tool that visualizes company data and clusters it using natural language processing and some fun machine learning algorithms (disclosure, I used to work at Quid), I looked at companies that are using AI in robots, or AI embodiment in general.*
How can you use this? The leaders in each of these areas may be on the cutting edge of not only AI functionality, but also of AGI theory. Understanding how the fields interact, where interconnectedness is most dense (like between autonomous vehicles and future of work) or where there are gaps (like between process automation and environmental sensing), can help us understand areas for innovation and maybe even new AI theory.
Generally, embodied AI companies cluster into the following areas:
Personal companions / Child: companies like Jibo and Mabu from Catalia Labs provide companionship and care for kids and hospital patients. Because of the Natural Language Processing (NLP) requirements, the empathy sensing requirements, and the domain expertise needed for human interaction, a huge amount of innovation and money coincide in this area. And because a robot can never truly know if their goal of, say, making the patient feel peaceful, is 100% satisfied forever, growing AGI in these service settings may be an important way to control for catastrophic AGI takeover.
Operations / Movers: robots with advanced physical capacities. A focus on supply chain or operations, either in robots or enabling software and applications. The popular Roomba clusters in here — a widely used consumer robot for home cleaning. A lot of ‘old school’ labs like Charles River Analytics and Boston Dynamics work in this area, with their associated datasets, institutional knowledge, and existing theories.
Environmental Sensing Systems: these companies focus on interacting with the natural environment, and involve sensing and feedback between intelligent systems and the real world. Honda is working in this space developing systems for environmental sensing and adaption. Also fun is Gridbots, which makes robots for underwater military and industrial use. Mavrx uses high resolution crop imagery to create a connected and intelligent system for agriculture, and makes me wonder if the goals of sensing, balance, complex feedback and flexible reaction to extraneous events is not ‘fertile ground’ for AI theory.
Legal AI: AI companies focused on the legal system or applications for document management and analysis. At first glance this does not seem to really push the concepts of AI, and are more about practical use of machine learning (ML), but feel free to set me straight. Clearly there is a lot of money here, and where there is money and data, AI may flourish.
Virtual Reality / Future of Work: this cluster includes gaming software innovator Velan Studios, which provides software for the integration of VR and robotics. It also includes a number of AR, VR and ‘mixed reality’ companies using advanced ML to deliver their solutions, often for games. Sony Playstation and other gaming labs are looking at empathetic avatars. Will any of these companies ever get enough data to create AGI? Maybe not, but the novel combination of sensing, empathetic systems and feedback is rich ground for AI theory.
AI Software Developers: this cluster of companies is core to the field of AI and robotics, and develops solutions for AI, speech, and industrial processes. Companies include Pony AI, Curious AI, Osaro Inc., and my personal favorite name: Twenty Billion Neurons GmbH. Given time, I’d like to dive more into the promises and insights unique to each actor in this group.
Process Automation and Consulting: this robot-centric group of companies either develops in-house or consults on development products for industrial, financial, and manufacturing process automation using AI, but most often low-intelligence robots. As sophisticated robots are developed, AI theorists may need to look to this group to understand practical feedback mechanisms for AI dev.
Autonomous Vehicles: we see a cluster of companies, investors and funds newly set up to specialize in robotics and AI. Here we see Robik looking at last-mile delivery with intelligent robots, and Toyota developing and investing in autonomous vehicles. The theories these companies employ around dealing with ambiguity could be good input for AGI theory.
China / Manufacturing: a sub-cluster of industrial AI and robotics focuses on manufacturing tech developing in China & Russia, mostly in Shenzhen and Guangdong Province. Shanghai Huoshanshi is the most active investor, followed by Warburg Pincus and Banyan Capital.
Natural Language and Chat Tech: this cluster, as you’d expect from the name, is all about interactive dialogue with semi-intelligent AI and robot-embodied AI. If you’ve read much on singularity (e.g. the easily-digestible Avogadro Corp), you’d theorize on how AI in this space might be the most data-enabled for advanced sentience. However it’s the application of this sophisticated technology with embodiment that may inform a new set of theories for growing AI.
Security / Drones: with innovation focused mainly in San Francisco, this cluster of aerial drone companies used for security, rescue, and surveillance is small but growing. Companies include Neural Robotics, Iris Automation, and Aeroxo. The computer vision needed for this field may be an interesting addition to what we should assume robots can sense and react to.
Summary: Here is a quick heat-map of each cluster, which shows timeline, funding and number of company sums, and some summary statistics about the network.
The top cities for this area of technology are Beijing, San Francisco, London, New York, and Tokyo — in that order. The top funders, again in order, are Intel Capital, Andreessen Horowitz, GGV Capital, Samsung Ventures, Banyan Capital, and Fenox Venture Capital. The number of companies has grown exponentially since 2013.
Many thanks to Kate Montgomery for her help proofing, to Jerry Kaplan for the idea, and to Mark Sagar for the illuminating chat on embodiment theory in Auckland last year.
*My boolean search term was : ( ‘embodiment’ AND [AI](AI OR “artificial intelligence”) ) OR ( embodiment AND robot * ) OR ( “artificial intelligence” AND robot * )
