["MIT新创公司Liquid AI近日完成了一轮接近4千万美元的种子轮融资，目标是构建一种新型液态神经网络人工智能。","液态神经网络是基于液态神经网络架构的创新技术，具有小巧、可解释和动态适应性。","融资动向显示Liquid AI估值达到3.03亿美元。","Liquid AI计划商业化液态神经网络技术，应用领域包括自动驾驶、气象预测和医疗数据分析等。"]
silx-ai
TARS-1B是一个拥有10亿参数的非Transformer液态神经网络语言模型，完全从头构建，采用创新的液态神经网络架构，专为连续时间推理和高效泛化而设计。该模型仅使用3亿个令牌进行预训练，在多个基准测试中展现出令人印象深刻的性能。
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