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PaLM-E is a decoder-only LLM that generates textual completions autoregressively given a prefix or prompt. It combines the power of visual models like ViT with language models like PaLM. It is an embodied LM built by injecting multi-modal information such as images into the embedding space of a pre-trained LLM. PaLM-E is a single general-purpose multimodal language model for embodied reasoning tasks, visual-language tasks, and language tasks. PaLM-E transfers knowledge from visual-language domains into embodied reasoning – from robot planning in environments with complex dynamics and physical constraints, to answering questions about the observable world. PaLM-E-562B can do zero-shot multimodal chain-of-thought reasoning, can tell visually-conditioned jokes given an image, and demonstrates an array of robot-relevant multimodal-informed capabilities including perception, visually-grounded dialogue, and planning. PaLM-E also generalizes, zero-shot, to multi-image prompts despite only being trained on single-image prompts. PaLM-E can also perform math given an image with textually-interleaved handwritten numbers. In addition, the model can perform, zero-shot, question and answering on temporally-annotated egocentric vision. Here is the agenda for this video: 00:00:00 What is PaLM-E? 00:03:34 What is the overall architecture of PaLM-E? 00:06:54 What is the input format for PaLM-E? 00:11:30 How are PaLM-E models trained? 00:16:03 How does PaLM-E perform on Task and Motion Planning (TAMP)? 00:22:27 How does PaLM-E perform on a table-top pushing environment? 00:28:05 How does PaLM-E perform in mobile manipulation domain? 00:32:45 How does PaLM-E perform on General Visual-Language Tasks, and General Lang Tasks? For more details, please look at https://arxiv.org/pdf/2303.03378.pdf https://palm-e.github.io/ https://ai.googleblog.com/2023/03/pal... Driess, Danny, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid et al. "Palm-e: An embodied multimodal language model." arXiv preprint arXiv:2303.03378 (2023).