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The Robots Are Coming! The Robots Are Coming!

With robots on the rise, they'll be infiltrating our businesses faster than most people think -- and not just for industrial use cases such as we already see in industries such as mining, manufacturing, agriculture, and logistics. With today's technologies, it's not hard to imagine autonomous machines learning to do a much wider variety of tasks, such as requesting that Joanne in marketing "tell all humans" ASAP about Sprint's 50% off deal.

While the Sprint TV ad was meant to be satirical, it's a great example of how we might be interacting with robots in the future. They can analyze data, scan images, look through inventory, and do a bunch of things faster than people can do.

Some examples of emerging use cases for robots in the workplace are:

  • Hard-to-do manual tasks -- People today undertake many extremely difficult tasks, such as inspecting equipment in snow conditions and going deep into mines. Former Cisco CEO John Chambers recently invested in a company that uses robots to improve the accuracy of feeding crickets, an emerging source of protein that he believes could help curb world hunger
  • In-store customer service -- Some retailers have conducted trials in which robots roam around stores and help people find products. A robot is ideally suited for such use cases since it would know the location and inventory of every item in stock
  • Improved meetings -- In the future we might be sitting around tables collaborating with robots in meetings, enabling us to find information and make decisions faster. For example, a robot could go into a commercial building and map it out for a group of investors. In the meeting, the robot could quickly display images based on audible queues. If an investor would start to talk about the lobby, the robot could display the images it took, alleviating the people from tasks. With enough data, the robot could be part of the evaluation process
  • Healthcare -- A robot could handle a wide range of activities, including inspecting MRIs, delivering precisely focused radiation therapy, giving out medications without making dosage mistakes, and diagnosing basic problems by taking pictures and analyzing images
  • Childcare -- Having The Terminator watch kids might seem a bit far-fetched, but this is an excellent use case for robots. Years ago, I talked with NEC about using its cute PaPeRo robot to mingle with kids. Robots can make pleasing sounds, play games, and, through the use of facial recognition, sense if a child is sad. Also, a robot with video conferencing capabilities could allow children and parents to video call with each other

Many of the early uses cases have robots working alone, but more and more they'll be collaborating with people. If you're not sure what "collaborate" means with respect to robots, the International Organization for Standardization (ISO) has defined a number of criteria in TS 15066; many revolve around safety. For example, the technical specification includes a measure for decreasing speed automatically as a person approaches a robot. Imagine being in a hardware store and having a robot run into you while you're asking it for help -- not good for customer service! ISO also specifies that a robot should cease operations should a person enter its zone while it's performing dangerous tasks.

One of the biggest challenges in using robots is the amount of time required for training. For example, teaching a robot to do something simple, like walk, involves a number of different scenarios from which it "learns" -- uphill, downhill, uneven terrain, and a variety of surfaces, for example. Training environments can take months to set up and for the robot to complete.

Nvidia's Isaac simulator, introduced earlier this week, is designed to shorten the time a robot needs to learn. It does so having the training take place in a virtual world, and then uploading the data into the robot, which will then function as expected. Reconfiguring a virtual environment takes a fraction of the time of reconfiguring a physical space, and allows for thousands of simulations instead of 10s, thus greatly increasing accuracy.

To demonstrate this, Nvidia built "Carter" (a robot that reminds me of one of the droids in the original Star Wars movie). Nvidia wanted Carter to move around its new building, Endeavor, without bumping into people, plants, desks, tables, or other physical objects. The company built out a fully simulated version of Endeavor, complete with people moving about and other hazards Carter might encounter.

After training virtual Carter in the virtual Endeavor, Nvidia uploaded the data into physical Carter, which was able to roam around the building flawlessly and prove the value of using simulated, virtual environment for training.

Included with the Isaac launch are:

  • Jetson Xavier -- A low-power GPU computer designed specifically for robots. It's capable of delivering over 30 trillion operations per second (TOPS) while using less than 30 Watts of power
  • Isaac software development kit -- The SDK is a collection of APIs and tools such as for debugging, profiling, and simulation. Developers can use these to create robotic algorithms and runtime frameworks
  • Isaac autonomous machine acceleration (AMX) libraries -- a collection of Nvidia-developed algorithms, specifically for robots
  • Isaac simulator -- This is a realistic virtual simulator, where all the laws of physics apply to train robots

Isaac is the latest product launch from Nvidia, a company that only a couple of years ago was considered a niche supplier to the larger video gaming industry. Today, it is arguably the single most important company to the advancement of artificial intelligence and related technologies. In the past two years, its stock price has almost quadrupled as technologies such as robots, AI, and virtual reality have moved out of the shadows and into the mainstream.

Robots are coming... and coming fast -- and will change the workplace in ways we have never imagined. Nvidia's Isaac simulator makes it possible to accelerate the training and deployment of robots in a safer, more reliable way.

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