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The sources describe the latest advancements in the field of large language models (LLMs) with a focus on multi-modality, meaning the models are able to process and understand both text and images. The first source details the release of Llama 3.2, a new family of LLMs from Meta AI, which includes models that are smaller in size and can be run on edge devices such as mobile phones, as well as larger models capable of understanding and reasoning about images. The second source discusses the Molmo family of LLMs, developed by the Allen Institute for AI, which are open-source and designed to be state-of-the-art in their class. These models are trained on new datasets of detailed image descriptions that were collected using a novel speech-based approach to avoid relying on synthetic data generated by other, proprietary LLMs. The research highlights the importance of open-source models and data in fostering innovation and advancing the field of AI.
The sources describe the latest advancements in the field of large language models (LLMs) with a focus on multi-modality, meaning the models are able to process and understand both text and images. The first source details the release of Llama 3.2, a new family of LLMs from Meta AI, which includes models that are smaller in size and can be run on edge devices such as mobile phones, as well as larger models capable of understanding and reasoning about images. The second source discusses the Molmo family of LLMs, developed by the Allen Institute for AI, which are open-source and designed to be state-of-the-art in their class. These models are trained on new datasets of detailed image descriptions that were collected using a novel speech-based approach to avoid relying on synthetic data generated by other, proprietary LLMs. The research highlights the importance of open-source models and data in fostering innovation and advancing the field of AI.