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'' ' TRICKY JOBS TRUTH ' '' :
ROBOTS
THE BITTER TRUTH IS THAT THE DEVELOPED WORLD :
Has begun realizing how much it is likely to depend on robots and automation for the tricky stuff. And it is never going to wait or worry for the growing population or unemployment in the developing world.
Advances in sciences, ageing population, efficient systems, cost considerations, will bring the robots marching forward. Soon, very soon, the businesses will reconsider all their future needs to re-ignite all engines of growth.
The Developing World doesn't have a clue. Global Dependence on robots will soon emerge as the real test.
REMEMBER : ''A robot doesn't smoke, is always in good health, isn't chatting with its neighbors, no toilet breaks, needs no holidays, can work around the clock. It's super, super efficient.''
''But If you want to advance artificial intelligence, you don't just do it in a lab,'' said Peter Chen, Covariant's chief executive and co-founder. ''There's a huge gap in bringing it to the real world''.
WAREHOUSES ARE ALREADY HIGHLY AUTOMATED.
At the facility outside Berlin, inside a fenced-off room larger than a football field, other robots have long been used to fetch large boxes from shelves several stories high.
But this is relatively easy task for a machine. Engineers can program a robot to perform the same motion over and over again. the boxes are uniform. A robot can pick them up with the same motion every time.
Picking through a bin of random items is different. Shapes vary, as do surfaces. One light switch maybe upside down, the other right-side up. The most electrical gadget might be in a plastic bag that reflects light in ways a robot has never seen. A human touch has been needed.
Programming a robotic arm to deal with every situation, one rule at a time, is impossible. At Knapp, Mr. Puchwein and his partners had tried and failed for years to create a robot with the dexterity and flexibility needed for the job.
Covariant, which is working with Knapp, build software that could learn through trial and error. First the system learned from digital stimulation of the task - a virtual recreation of a bin filled random items.
Has begun realizing how much it is likely to depend on robots and automation for the tricky stuff. And it is never going to wait or worry for the growing population or unemployment in the developing world.
Advances in sciences, ageing population, efficient systems, cost considerations, will bring the robots marching forward. Soon, very soon, the businesses will reconsider all their future needs to re-ignite all engines of growth.
The Developing World doesn't have a clue. Global Dependence on robots will soon emerge as the real test.
REMEMBER : ''A robot doesn't smoke, is always in good health, isn't chatting with its neighbors, no toilet breaks, needs no holidays, can work around the clock. It's super, super efficient.''
''But If you want to advance artificial intelligence, you don't just do it in a lab,'' said Peter Chen, Covariant's chief executive and co-founder. ''There's a huge gap in bringing it to the real world''.
WAREHOUSES ARE ALREADY HIGHLY AUTOMATED.
At the facility outside Berlin, inside a fenced-off room larger than a football field, other robots have long been used to fetch large boxes from shelves several stories high.
But this is relatively easy task for a machine. Engineers can program a robot to perform the same motion over and over again. the boxes are uniform. A robot can pick them up with the same motion every time.
Picking through a bin of random items is different. Shapes vary, as do surfaces. One light switch maybe upside down, the other right-side up. The most electrical gadget might be in a plastic bag that reflects light in ways a robot has never seen. A human touch has been needed.
Programming a robotic arm to deal with every situation, one rule at a time, is impossible. At Knapp, Mr. Puchwein and his partners had tried and failed for years to create a robot with the dexterity and flexibility needed for the job.
Covariant, which is working with Knapp, build software that could learn through trial and error. First the system learned from digital stimulation of the task - a virtual recreation of a bin filled random items.
Then when Mr. Chen and his colleagues transferred this software to a robot, it could pack up items in the real world.
The robot continued to learn as it sorted through items it had never seen before. Inside the German warehouse, the robot can pick and sort more than 10,000 different items with accuracy according to Covariant.
This represents a significant change for the online retail and logistics industries.
LATE last year, the international robot maker ABB ran a contest. It invited 20 companies to design software for its robot arms that could sort through bins of random items, like cubes or plastic bags filled with other objects.
Ten of the companies were based in Europe, and the other half were in the United States. Most came nowhere close to passing the test. A few could handle most tasks but failed on the trickier cases.
Covariant was the only company that could handle every task as swift and efficiently as a human.
''We were trying to find weaknesses,'' said Marc Segura, managing director of service robotics of ABB. ''It is easy to reach certain levels on these tests, but it is super difficult not to show any weaknesses.''
Knapp, which helped deploy the system outside Berlin, and ABB believes this technology can be used in similar warehouses.
Covariant engineers believe that their robots will improve with practice. As a robot in one warehouse learns better ways to pick up certain items, the information feeds back to what is essentially a central brain run by Covariant that will help operate machines.
The Honor and Serving of the Latest Global Operational Research on Automation, Jobs and Robotics, continues.
With respectful dedication to the Students, Professors and Teachers of the world. See Ya all prepare and register for Great Global Elections on The World Students Society : wssciw.blogspot.com and Twitter - !E-WOW! - The Ecosystem 2011:
''' Crippling Future Crowing '''
The robot continued to learn as it sorted through items it had never seen before. Inside the German warehouse, the robot can pick and sort more than 10,000 different items with accuracy according to Covariant.
This represents a significant change for the online retail and logistics industries.
LATE last year, the international robot maker ABB ran a contest. It invited 20 companies to design software for its robot arms that could sort through bins of random items, like cubes or plastic bags filled with other objects.
Ten of the companies were based in Europe, and the other half were in the United States. Most came nowhere close to passing the test. A few could handle most tasks but failed on the trickier cases.
Covariant was the only company that could handle every task as swift and efficiently as a human.
''We were trying to find weaknesses,'' said Marc Segura, managing director of service robotics of ABB. ''It is easy to reach certain levels on these tests, but it is super difficult not to show any weaknesses.''
Knapp, which helped deploy the system outside Berlin, and ABB believes this technology can be used in similar warehouses.
Covariant engineers believe that their robots will improve with practice. As a robot in one warehouse learns better ways to pick up certain items, the information feeds back to what is essentially a central brain run by Covariant that will help operate machines.
The Honor and Serving of the Latest Global Operational Research on Automation, Jobs and Robotics, continues.
With respectful dedication to the Students, Professors and Teachers of the world. See Ya all prepare and register for Great Global Elections on The World Students Society : wssciw.blogspot.com and Twitter - !E-WOW! - The Ecosystem 2011:
''' Crippling Future Crowing '''
Good Night and God Bless
SAM Daily Times - the Voice of the Voiceless
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