“We then use these labels to fine-tune a discriminator to detect and remove unsafe responses.” Groundedness That labeled data was used to train LaMDA: The official research paper was published later, in February 2022 ( LaMDA: Language Models for Dialog Applications PDF). Google published its announcement of LaMDA in May 2021. Satisfying responses also tend to be specific, by relating clearly to the context of the conversation.” LaMDA is Based on Algorithms Basically: Does the response to a given conversational context make sense? During its training, it picked up on several of the nuances that distinguish open-ended conversation from other forms of language. “…unlike most other language models, LaMDA was trained on dialogue. It’s trained to understand if a response makes sense for the context, or if the response is specific to that context. This quality of understanding the context allows LaMDA to keep up with the flow of conversation and provide the feeling that it’s listening and responding precisely to what is being said. LaMDA is a model trained to understand the context of the dialogue. “That architecture produces a model that can be trained to read many words (a sentence or paragraph, for example), pay attention to how those words relate to one another and then predict what words it thinks will come next.” Why LaMDA Seems To Understand ConversationīERT is a model that is trained to understand what vague phrases mean. Similar to other language models (like MUM and GPT-3), LaMDA is built on top of the Transformer neural network architecture for language understanding. What makes LaMDA a notable breakthrough is that it can generate conversation in a freeform manner that the parameters of task-based responses don’t constrain.Ī conversational language model must understand things like Multimodal user intent, reinforcement learning, and recommendations so that the conversation can jump around between unrelated topics. LaMDA is different from other language models because it was trained on dialogue, not text.Īs GPT-3 is focused on generating language text, LaMDA is focused on generating dialogue.
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