Google Alphabet Launches New Initiative

Google Alphabet  has announced that it is working on a new project which is fully focused on helping human with their daily living activities. The project which is spearheaded by The company’s R&D lab, dubbed Alphabet X, is a big step for Google Alphabet when considering its history in the robotic field.  

With this new line, the kind of robots that are being designed are such that they can learn new tasks, rather than be programmed into performing them. The project88 is considered as an initiative called the “Everyday Robot Project” because, as its name implies, it wants to build robots that can assist humans in simple tasks of everyday life especially in the type of world we currently live in.

Hans Peter Brondmo, who is the leader of this particular project, when explaining about this project made it known that this designed robots are stereotyped to a particular design and structure and as such will be incapable of adapting to strange and unexpected situations that differs from the one it was originally created for.

According to him, “Where humans naturally combine seeing, understanding, navigating, and acting to achieve their goals, robots need careful instruction and coding to do each of these things, it gets very complicated for robots to perform tasks in highly changeable environments. We have concluded that you need to teach machines to perform helpful tasks; you cannot program them.”

As such, the team has been working on how to get these robots to learn and perform new functions and capabilities through various testing techniques over the past few years. This has recorded a bit of progress over the years as the company’s researchers found that, much like humans, robots could be given a simple task to practice over and over again, and that this can lead to the development of new learnings. 

“It proved that it’s possible for robots to learn how to perform new tasks in the real world just through practice, rather than have engineers ‘hand code’ every new task, exception, or improvement,” said Brondmo

Major among this testing techniques include the process of simulating a task in the cloud, it has been discovered that these algorithms are able to learn much faster while needing up to 100 times less real-world data; and the virtual training can then be integrated back into robots to refine their skills.

This was practically tested by teaching robots how to sort through waste to reduce contamination, which happens when employees accidentally choose the wrong bin for trash items. With cloud simulation, tens of thousands of virtual robots spent each night sorting through cups, bottles and snack wrappers; then by day, the cloud training was integrated back into the office’s real robots.

The project’s lead, however, clarified that just because Alphabet X’s robots are capable of sorting through waste, doesn’t mean that they can learn any other task anytime soon. “This could prove to be impossible,” he said, “but we’ll give it a shot.