主题：这几天大火的Deepseek没有人讨论吗 -- 俺本懒人

深度自己的介绍：

V3: We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient inference and cost-effective training, DeepSeek-V3 adopts Multi-head Latent Attention (MLA) and DeepSeekMoE architectures, which were thoroughly validated in DeepSeek-V2. Furthermore, DeepSeek-V3 pioneers an auxiliary-loss-free strategy for load balancing and sets a multi-token prediction training objective for stronger performance. We pre-train DeepSeek-V3 on 14.8 trillion diverse and high-quality tokens, followed by Supervised Fine-Tuning and Reinforcement Learning stages to fully harness its capabilities. Comprehensive evaluations reveal that DeepSeek-V3 outperforms other open-source models and achieves performance comparable to leading closed-source models.

R1 是基于 V3 的。一样是671B total parameters with 37B activated for each token.。而Meta的羊驼3也不过 15 trillion training tokens，和DeepSeek 基本相当。而训练结果是最大 405B total parameters ，8B 和 70B active。

DeepSeek 主要的突破有两个：

1. 降低了训练成本，缩短了训练时间

2.显示 AI 的思索过程