NVIDIA has been running pretty hard of late and CEO Jensen Huang has been on his game with regard to strategic planning. The firm’s move to corner the market on autonomous car technology was almost perfectly timed. Neither too early so that it ran out of money before the market emerged or too late, where some other firm was able to gain dominance before NVIDIA could enter. But the technology that goes into autonomous cars is nearly identical to what will be needed with general-purpose robots and, of the two, general-purpose robots will eventually be the larger market.
Last week, NVIDIA moved to open up its first dedicated robotics lab in Seattle and it suggests that, as with autonomous cars, NVIDIA has a good shot at cornering the core technology market for these. It is interesting to note that the first into both markets were generally automobile makers, who saw both opportunities long before any of the tech companies but couldn’t convert either in a timely manner to a significant market advantage.
Let’s talk about general-purpose robots this week.
General-Purpose Robots
The goal of a general-purpose robot is to be able to do what a human can do. The utility for such a device ranges from extra hands for someone who is disabled or ill, to being able to replace a human worker for a variety of tasks. There is an ongoing discussion about whether such a robot would need to look human but the issues with the uncanny valley, or the things that approach human appearance but clearly aren’t are too creepy for the market, will likely keep the human-appearing robots on movies but out of our homes.
Once you step away from the need to appear human, your time to market is reduced because you can use more off-the-shelf items like rolling chassis instead of legs, and existing mechanical arms, which are in wide use in labs and in manufacturing to get the device to market.
At CES this year, the robots that were being showcased generally lacked arms and, if they were mobile, they used some type of wheeled mobility technology, not legs. This made them more like rolling Amazon Echo products at various sizes and appropriate as guides, mobile information repositories, or mobile security cameras, but not very useful if you needed something to carry your bags from the store to your car.
The same kind of problems that stood in the way of self-driving cars largely stand in the way of general-purpose robots. They have to be able to accurately detect objects and take action based on what they detect with a high degree of accuracy. Granted, robots likely won’t have to worry that much about pot holes, and cars likely won’t have to read cereal boxes. And much like cars have to navigate roads, avoid pedestrians, and interoperate with other cars, general-purpose robots have to navigate homes, avoid pets, children, and adults, and interoperate with other robots, appliances, and yes, even more intelligent cars.
If used for delivery, they’ll even have to work with autonomous vehicles like automated UPS, or more likely in the near term, Amazon delivery trucks. Due to the amount of work that has already gone into developing the autonomous car, development for general-purpose robots should proceed far more quickly. And with 5G and its low latency advantage, intelligence doesn’t have to be in the robot but in the cloud and shared. Regardless of where the intelligence resides, security remains a major concern because these things could do a great deal of harm if they were to be hacked or were control lost to a hostile external force. Fortunately, here too, the work with autonomous cars comes into play because security has been a major development component of that platform.
So not only is NVIDIA one of the first firms to get that the opportunity for robots is huge, its work with autonomous cars will give it a significant development boost. What NVIDIA demonstrated during the opening was industrial robotic arms able to manipulate kitchen objects and evolved twin arm robots able to emulate humans (a faster way than programming for training).
Wrapping Up: NVIDIA Capitalizing on the Robotics Opportunity
Huang has once again anticipated a major market shift that other tech firms appear to have missed. The staffing and creation of a robotics lab is just part of a strategy that trails back to the firm’s autonomous car efforts and will undoubtedly allow it to again emerge as the leading provider of core technology for this new effort. And the idea of having a core technology provider raises all boats, because the defense and private robotic efforts that currently exist are highly proprietary and likely won’t scale beyond their initial target efforts. General robotics require an ecosystem and at the heart of that ecosystem, if NVIDIA executes (and it has a history of executing), it will be NVIDIA.
As a side note, Seattle is also home to the Science Fiction Museum, once owned by Paul Allen, the founder of Microsoft, who just passed. It strikes me that this exhibit would look really nice in the entry way.
Rob Enderle is President and Principal Analyst of the Enderle Group, a forward-looking emerging technology advisory firm. With over 30 years’ experience in emerging technologies, he has provided regional and global companies with guidance in how to better target customer needs; create new business opportunities; anticipate technology changes; select vendors and products; and present their products in the best possible light. Rob covers the technology industry broadly. Before founding the Enderle Group, Rob was the Senior Research Fellow for Forrester Research and the Giga Information Group, and held senior positions at IBM and ROLM. Follow Rob on Twitter @enderle, on Facebook and on Google+
