{"id":458,"date":"2019-03-30T11:16:28","date_gmt":"2019-03-30T11:16:28","guid":{"rendered":"https:\/\/www.livewireindia.com\/blog\/?p=458"},"modified":"2025-08-21T10:29:39","modified_gmt":"2025-08-21T10:29:39","slug":"machine-learning-classroom-training-2019","status":"publish","type":"post","link":"https:\/\/livewireindia.com\/blog\/machine-learning-classroom-training-2019\/","title":{"rendered":"Machine Learning Training | A Robot Hand to Future| Livewire Thrissur"},"content":{"rendered":"\n

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\"MACHINE<\/a><\/figure>\n\n\n\n

Why we need a Machine Learning Training<\/a>?<\/strong> Do you think before about this topic? I know everyone can have more than one reply to this. Because there are lots of technical examples and career opportunities are coming under Machine Learning and Artificial Intelligence<\/strong><\/a><\/em>. So there is no need to explain more about this. However, I just give a simple but effective example for Machine Learning. Just go through it and explore your career Machine Learning through a Machine Learning Training.<\/a><\/strong><\/p>\n\n\n\n

Magic Ball gripper system<\/h2>\n\n\n\n

Everyone is eagerly waiting to know about this Robot hand which is a technical asset for the future. The first industrial robot arm is called Unimate. There is a task is assigned after the development of this hand. ie to pick some simple breakfast items like\u00a0toast, coffee, and champagne. Because of unsatisfied results, this is not in current on stage. So, to acquire technical knowledge we need Machine Learning\u00a0Training<\/a><\/strong><\/em>.<\/p>\n\n\n\n

\"MACHINE<\/a><\/figure>\n\n\n\n

Today\u2019s robots are more intelligent and adaptive robots compared to previous years. But these task remains difficult for today’s machines with rigid hands.<\/p>\n\n\n\n

To overcome these issues, now the robots have fingers made with soft, flexible materials like rubber. So, these robots pick up anything like grapes to boxes and empty water bottles. But still, they could not able to handle large or heavy items.<\/p>\n\n\n\n

Technical Trend in AI<\/h2>\n\n\n\n

To overcome this issue, the researchers from MIT and Harvard University have developed a new gripper with soft and strong. So, It includes a cone-shaped origami structure to pick up items like soup cans, hammers, wine glasses etc. However, the Magic Ball gripper system<\/strong><\/em> can do pick-and-place tasks for a huge variety of items like wine bottles to broccoli, grapes and eggs. <\/p>\n\n\n\n

In some case, Softer robotic fingers cannot pick up heavier objects.
Magic Ball gripper system can pick different shapes like con-shape, hollow etc. Mainly three parts<\/strong> in this gripper.<\/p>\n\n\n\n