Summit

The Role of AI and Machine Learning in the Shift to More Workforce Robotics

Within the manufacturing and Warehousing landscape, businesses are embracing robotic systems and automation within their workforce. At the epicenter of this paradigm shift is AI/ML, bestowing robotics with cognitive capabilities. These technologies enable machines to learn from data, adapt to new situations, and make decisions with minimal human intervention. The result? Enhanced productivity, accuracy, and agility in the manufacturing processes. Watch the panel discussion on the role of AI and machine learning in moving towards workforce robotics, joined by James Kinsey, CEO of Humatics Corporation, Rajshekhar Aikat, Chief Product and Technology Officer at iMerit, Dipal Pal, Founder of Voaige Inc., and the session moderator, Chris Baker from CBC.

“Automation does not eliminate the operator but makes their job much easier, resulting in longer shifts, higher efficiency, 5x-10x or sometimes, even higher accuracy is what we have seen.”

– Rajshekhar Aikat, iMerit

“Programming the robot very quickly is almost impossible right now, and it is not easy to do if it is in such a small period for a particular part. But AI lets you do that, and suddenly the SMB market, which is the largest in the US in terms of their market share, tends to see some growth, and that sees some adoption coming in that is going to transform the economy as well.” 

– Dipan Pal, Founder, Voyage Inc.

Get Valuable Insights on:

  • The evolution of different robotics functionalities and their biggest enablers – How have these functionalities evolved over the years
  • How to address everyday tasks with robotics while advancing capabilities and gaining market exposure for faster product development
  • Current state and future trajectory of transition in factories conducting robotic activities
  • The three Ds – Dull, Dirty, Dangerous – AI and Robotics targeting mundane tasks to enhance efficiency for human operators without replacing them
  • Automation challenges in the food industry
  • Significance of edge cases in different scenarios and the role of human expertise

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