MoE is a machine-learning approach that divides an AI model into separate sub-networks, or experts – each focused on a subset of the input data – to jointly perform a task. This is said to greatly reduce computation costs during pre-training and achieve faster performance during inference time. In machine learning, parameters are the variables present in an AI system during training, which helps establish how data prompts yield the desired output.
02:51 South Korea says DeepSeek sent data to ByteDance-owned servers in China without consent.
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DeepSeek speculation swirls online over Chinese AI start-up’s much-anticipated R2 model

The latest speculation includes R2’s imminent launch and the new benchmarks that it set in terms of cost-efficiency and performance.