As if robots weren't terrifying enough, a Japanese technology firm has created a humanoid machine capable of thinking and learning by itself. Tokyo's Institute of Technology unveiled the new robot that is capable of learning and making decisions based on prior experiences - in a manner not dissimilar to humans. Check out the future just below!
Using a technology called a self-replicating neural network, or SOINN(Self-Organizing Incremental Neural Network), it can think as humans do when taking on tasks that it has never done before. It can make educated guesses and decisions based on it's past experiences and knowledge.
In this experiment the robot will solve a problem by deciding what actions it should take and in what order. The robot will be told to pour a glass of water, make it cold, and give it to a person. The robot will decide how to do this while being aware of its surroundings and its own situation.
"So far, robots, including industrial robots, have been able to do specific tasks quickly and accurately. But if their environment changes slightly, robots like that can't respond. This robot remembers only basic knowledge, and it can apply that knowledge to its immediate situation. If it doesn't know enough, it stops, and reacts by saying, "I can't do this because I don't know how." So, if you teach this robot just the things that it can't do, it incorporates those things as new knowledge, and it can solve the problem overall, by including that knowledge."
In this experiment the robot will solve a problem by deciding what actions it should take and in what order. The robot will be told to pour a glass of water, make it cold, and give it to a person. The robot will decide how to do this while being aware of its surroundings and its own situation.
"So far, robots, including industrial robots, have been able to do specific tasks quickly and accurately. But if their environment changes slightly, robots like that can't respond. This robot remembers only basic knowledge, and it can apply that knowledge to its immediate situation. If it doesn't know enough, it stops, and reacts by saying, "I can't do this because I don't know how." So, if you teach this robot just the things that it can't do, it incorporates those things as new knowledge, and it can solve the problem overall, by including that knowledge."
If the robot is told that cold water is wanted, it recognizes that after pouring the water, it can't pick up ice straight away, because it's hands are already full with the glass and the bottle. So it chooses to put the bottle down, and then put the ice into the glass.
"Thinking about artificial intelligence in the real world, actual environments are inevitably more complex, and they change quickly. So it's necessary to have a learning mechanism that adapts to the situation. Also, because new situations emerge, it's also necessary to have the ability to keep learning new information on the spot.
As an algorithm for achieving that, we've created SOINN. SOINN is very light on computation, and it can learn while eliminating noise from the new information that comes in." As well as the robot's sensory information, in the form of visual, auditory, and tactile data, SOINN obtains information from other sources, including the Internet and other robots' experiences and knowledge. In this way, it gradually becomes smarter.
"Thinking about artificial intelligence in the real world, actual environments are inevitably more complex, and they change quickly. So it's necessary to have a learning mechanism that adapts to the situation. Also, because new situations emerge, it's also necessary to have the ability to keep learning new information on the spot.
As an algorithm for achieving that, we've created SOINN. SOINN is very light on computation, and it can learn while eliminating noise from the new information that comes in." As well as the robot's sensory information, in the form of visual, auditory, and tactile data, SOINN obtains information from other sources, including the Internet and other robots' experiences and knowledge. In this way, it gradually becomes smarter.
"For example, suppose this robot doesn't know how to make tea, and it's sent to an elderly person who lives alone. And suppose that person asks it to make a cup of green tea. The robot doesn't know how, so it asks robots around the world how to make tea. Suppose, for example, that a robot in the UK tells it how to make British-style tea. We think this robot will become able to transfer that knowledge to its immediate situation, and make green tea using a Japanese teapot." (DigInfo)
