Boston Dynamics: AI In the Machines

Mention robotics or artificial intelligence (AI) and the first image that’s likely to come to people’s minds would be the robots from Boston Dynamics. We’ve all looked in utter disbelief at their choreographed dance moves. We all have been mesmerized by their ability to synchronize their movements for extended periods without any outside interference.

But this is just the tip of the iceberg. This is only a peek at the power of artificial intelligence and machine learning to create a future where most production and distribution processes would be automated.

?What we’re seeing is only a glimpse of the current capacity of these technologies. The future, at this pace, will see robotics in all spheres, from retail to healthcare to transport.

?The significance of robotics

?With machine learning and advanced spatial awareness through computer vision, robots will evolve to perform tasks that are either too monotonous, expensive, specialized, or dangerous for human beings. That’ll be powered by the improvements in their movements.

?What makes this stage of the growth in robotics special is the ability of the robots to learn and adapt in real-time. The improvisational element works with pre-determined instructions. This means that these robots can dance to the initial instructions while still maintaining balance in their bodily movement.

?What we’re seeing is the ability of the robots to not only respond accurately to precise movement instructions but also improvise without external input. That autonomous decision-making and adaptability open the door for robotics outside academics and research.

?The capacity

?The initial hesitancy over the deployment of robots was partially due to the limited flexibility and the lack of nuanced movements. But that’s increasingly changing. Robots that are more dynamic in their movement characteristics will be able to execute tasks that up to this point could not be performed by robots.

In the automotive industry, for example, robots can now assemble components on non-specialized assembly lines. Generalized but simplistic tasks can now be performed with an improved level of software coordination. With improved maneuverability, robots will be more nimble, and capable of performing tasks that were previously carried out by humans.

?The future implementations

?Machine learning and its implied heuristics will ensure that robots will be able to move beyond these predictable and repetitive tasks with limited risks. Once they’re equipped with object recognition, these robots will be able to do almost anything that needed humans.

?Eventually paired with more sensors, these robots can be used in more precise generalized tasks to do almost any task that would have required manual labor. Retail and e-commerce giants have already started using robots in their warehouses to sort, carry, and distribute boxes of different sizes.

?This isn’t the last we’ll hear of Boston Dynamics’ software being used in these instances. If the focus until now was on research and advancement, the next steps would be on iterations and acclimatization enabled by machine learning. From invasive surgeries to human-less retail, what we may see in the future would be pragmatic implementations of their technology.