ZhiYuan Releases the World's Largest Chinese-English Semantic Vector Model Training Dataset MTP


["ZhiYuan Research Institute has released the new generation multimodal foundation model Emu2, pushing the boundaries of multimodal contextual learning capabilities.", "Emu2 surpasses Flamingo-80B and IDEFICS-80B, demonstrating excellent performance in few-shot multimodal understanding tasks.", "Emu2 achieves optimal performance in multiple few-shot understanding, visual question answering, and image generation tasks.", "Emu2-Chat realizes accurate understanding of text-image instructions, while Emu2-Gen offers flexible, controllable, high-quality images."]
ZhiYuan Research Institute has open-sourced the JudgeLM evaluation model, which can efficiently assess various large models and provide scores. Compared to GPT-4, JudgeLM's cost is only 1/120, with a consistency rate of over 90% for evaluation results. JudgeLM can be applied in various assessment scenarios including pure text and multimodal contexts, generating scores and justifying reasons. The consistency of JudgeLM with reference answers exceeds 90%, approaching human performance. ZhiYuan Research Institute has also released datasets for training and validation samples for in-depth research on large models.
["ZhiYuan Research Institute has recently open-sourced the Uni3D model with 1 billion parameters, designed for general 3D vision tasks.", "The model can process point cloud data and has achieved breakthroughs in mainstream 3D vision tasks.", "Uni3D employs a unified Transformer architecture and introduces a multimodal alignment training method.", "The model has achieved state-of-the-art results across various 3D vision tasks.", "ZhiYuan Research Institute states that the open-source release of Uni3D will contribute to the future of 3D computing."]
ZhiYuan Research Institute has unveiled the new open-source bilingual model Wudao・Tianying 34 Billion Aquila2-34B, which excels in reasoning, generalization, and more. The institute has also released a comprehensive open-source toolkit to promote collaborative innovation in large model research. Aquila2-34B surpasses other open-source foundational models in overall capabilities, with the ZhiYuan team developing the NLPE method to enhance the model's extension capabilities.
Meta Intelligence OS is a startup founded by Bloomberg. It has developed a series of large models based on the open-source model RWKV and aims to become the Android in the era of large models. The RWKV model has superior performance and low cost in inference tasks, thus attracting customers from industries such as finance, law firms, and smart hardware. The business model of Meta Intelligence OS is model customization based on private data and internal AI Agent development. The company hopes to solve the problems of API call latency and data security by deploying large models on terminal devices. Currently, RWKV versions are available on Windows, Mac, and Linux computers, and Android and iOS versions are also in development. Meta Intelligence OS is raising funds and collaborating with chip companies and computing power platforms to create benchmark customers. Luo Xuan said that the decisive battlefield for large models is on hardware, and both terminal devices and the cloud require dedicated chips.