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ReMEmbR combines LLMs, VLMs, and retrieval-augmented generation to enable robots to reason and take action. They can also be integrated with live data sources and tools, to request more information if they don’t know the answer or take action when they do. But how can you apply these advances to perception and autonomy in robotics?
Digital transformation insights Digital transformation initiatives are on the rise in many manufacturing and industrial facilities, but long-term support and maintenance is a key part of the plan. Understanding where the data is coming from and how to retrieve it are some of the overlapping abilities required.
Eliminating the need for large and expensive safety cells, which in term mandate complex systems for moving work in and out of the cell, is one of their biggest benefits. With AI though, a robot can acquire information about how tight or loose an assembly feels through attached sensors, and either change parts or make adjustments as needed.
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