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Google CEO Sundar Pichai announced at a launch event that Google has open-sourced its latest multimodal large model, Gemma-3. This model is attracting significant attention for its low cost and high performance. Gemma-3 offers four different parameter scale options: 1 billion, 4 billion, 12 billion, and 27 billion parameters. Surprisingly, the largest 27 billion parameter model only requires a single H100 GPU for efficient inference, while similar models often require ten times the computing power.

Google's DeepMind, in collaboration with the Massachusetts Institute of Technology (MIT), recently announced a significant research breakthrough. The research team developed a new autoregressive model called 'Fluid', which has made groundbreaking progress in the field of text-to-image generation. After scaling up to 10.5 billion parameters, the model has demonstrated outstanding performance. This research overturns the industry's common perception; while autoregressive models have dominated the language processing domain, they have traditionally been seen as inferior to Stable Diffusion and Goog.