During the past year, there have been major implosions of robot startups, such as with Jibo, Anki and Rethink Robotics. They all raised substantial amounts of capital from top-tier investors and had strong teams.
So why the failure? One of the main reasons is the extreme complexities of melding software and movable hardware. As a result, the technology often does not live up to expectations.
Even with the strides in AI – such as deep learning — there is still much to do. “Deep learning and robotics is difficult for a variety of reasons,” said Carmine Rimi, who is a Product Manager for AI at Canonical, “For instance, simultaneous localization and mapping (SLAM) in unknown environments, while simultaneously keeping track of an agent’s location within it in tractable time, is a challenge. In real-time it is at least a magnitude more difficult. Research into advanced algorithms, that deliver better accuracy faster and at lower power consumption, along with quantum-like parallel states and processing, are some of the areas that will help. And this part of why it is difficult.”
But there is much more than this. Dr. Alex Wong, who is the Chief Scientist and co-founder of DarwinAI, has this to say: “One of the primary difficulties with AI in this context is that learning to manipulate physical objects with a high level of dexterity in dynamic and ‘noisy’ real-world environments is extremely challenging, as it must take into account an incredible number of environmental factors to make complex decisions in real-time. Additional complexities in this area are issues associated with ‘data sparsity’ and training speed.”
And finally, AI is still fairly narrow. The fact is that we are years away from some type of general intelligence. “The challenge of replicating the capabilities of a human being, whether it be on a production line or in a medical facility – is very difficult,” said Ran Poliakine, who is the co-founder of Musashi AI. “For example, the ability to imitate the function of the brain when looking at an image is incredibly complicated. This is why until now, even with all of the robotics and advanced hardware available, the ability to make a decision or imitate a human reaction was nearly impossible.”
Now all this is not to imply that the situation is hopeless. If anything, there are enormous opportunities with robots and AI. Yet there must be different approaches to the technology, especially when compared to software-only AI.
So what to do? Well, Erik Schluntz, who is the CTO of Cobalt Robotics, is someone who has been able to find lots of success – primarily because his approach is not about achieving moonshots. His company develops robots that provide security services in the workplace.
When Schluntz started Cobalt, he first talked to a range of companies across several industries so as to find real-world problems to focus on. “We did not want to come up with an idea in a vacuum,” he said.
But the Cobalt robot would not be a replacement for people. “Marrying the benefits of robotics with the unique capabilities of humans means creating something that is greater than the sum of its parts,” said Schluntz. “The reliability of robots for tasks that require unwavering attention or precise repetition is unmatched. When you expand the capabilities of a robot by integrating its work with that of a human for flexible decision-making, you’re enabling a greater level of effectiveness for roles that are more than just the dirty, dull or dangerous. In this sense, the sweet spot for robotics applications is greatly expanded. A robot can detect leaks and spills in a building before a human, and working with a human to address the leak or spill can correct the anomaly. We let the robot to do the dull part – tirelessly patrol in search of water leaks, and save the interesting response to a human.”
True, it’s not necessarily sexy. But hey, Cobalt has turned into a solid company that has customers like Yelp and Slack.
“To enable the proliferation of robots and AI, robots need to be friendly, functional and easy to be around,” said Schluntz. “Success will rely on key players in the robotics space being intellectually honest and realistic—identifying clear use-cases, demonstrating clear ROI, operating in an inherently safe and secure manner (both physical and cyber context), and creating future roadmaps.”