Google Takes Leap Forward in Robotics with RT-2

It showed emergent robotic skills that were not present in the data due to knowledge transfer from web pre-training
Google DeepMind introduced a successor to its Robotics Transformer model 1 called RT-2, a Transformer-based model trained on text and images from the web, enabling it to directly produce robotic actions.  Unlike chatbots, robots face real-world challenges, requiring a grounding in the physical environment and complex tasks. However, RT-2 is a significant step towards creating more capable and helpful robots, addressing the challenges of time-consuming and expensive training methods used previously. Similar to how language models learn from web data to understand general concepts, RT-2 employs web data to inform and guide robot behaviour.  It is an advancement that extends the capabilities of vision-language models (VLMs), which take images as input and generate text. It builds
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Picture of Shyam Nandan Upadhyay
Shyam Nandan Upadhyay
Shyam is a tech journalist with expertise in policy and politics, and exhibits a fervent interest in scrutinising the convergence of AI and analytics in society. In his leisure time, he indulges in anime binges and mountain hikes.
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