In the field of natural language processing, the development of large language models (LLMs) has progressed rapidly and achieved significant advancements across various domains. However, as the complexity of these models increases, accurately evaluating their outputs becomes crucial. Traditionally, we have relied on human evaluations, but this method is both time-consuming and difficult to scale, struggling to keep pace with the rapid advancements of models. To change this situation, the Salesforce AI research team has introduced SFR-Judge, which consists of three large language models.

Salesforce has released an open source multimodal AI model named xGen-MM, designed to simultaneously understand and generate various data types such as text and images, significantly changing the way AI research and applications are conducted. The model performs exceptionally well in multiple benchmark tests, demonstrating strong performance compared to similar open source models, and includes pretrained models, datasets, and fine-tuning code. The largest model boasts 4 billion parameters and can handle 'interleaved data,' enabling multitasking, such as answering questions about multiple images at once. The diverse options available in the model reflect the potential of AI.