Google adds AI language skills to its helper robots to better understand humans
Google has dubbed the resulting system PaLM-SayCan, the name capturing how the model combines the language understanding skills of LLMs with the “affordance grounding” of its robots .
Google says that by integrating PaLM-SayCan into its robots, the bots were able to plan correct responses to 101 user–instructions 84 percent of the time and successfully execute them 74 percent of the time. That’s a solid hit rate, but those numbers should be taken with a pinch of salt. We don’t have the full list of 101 commands so it’s not clear how constrained these instructions were.
It’s why the only home robot this century to achieve even a modicum of success — the robot vacuum cleaner — has but one purpose in life: suckin’ dirt. As AI delivers improvements in skills like vision and navigation, we are now seeing new types of bots enter the market, but these are still purposefully limited in what they can do. Look at Labrador Systems’ Retriever bot, for example. It’s basically athat moves items from one part of the house to another.
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