模型，该架构相比传统的 RNN（递归神经网络）和 LSTM（长短时记忆网络）具有更高的训练效率和 更强的长距离依赖建模能力。Transformer 由多个关键组件组成：1. 自注意 力机制（Self-Attention）：模型在处理文本时，会自动关注句子中的重要单 词，理解不同词语间的联系。2. 多头注意力（Multi-Head Attention）：使用 多个注意力头同时分析不同的语义信息，使得模型的理解能力更强。3

will introduce the details of MLA and DeepSeekMoE in this section. For other tiny details (e.g., layer normalization and the activation function in FFNs), unless specifically stated, DeepSeek-V2 follows be the dimension per head, and h? ∈ R? be the attention input of the ?-th token at an attention layer. Standard MHA first produces q?, k?, v? ∈ R?ℎ?ℎ through three matrices ??,? ?,?? ∈ R?ℎ?ℎ×?, respectively: expert; ??,? is the token- to-expert affinity; e? is the centroid of the ?-th routed expert in this layer; and Topk(·, ?) denotes the set comprising ? highest scores among the affinity scores calculated for

tools, or orchestrating workflows across platforms, often using natural language as their command layer. This shift mirrors a broader historical pattern in technology. Just as the early 2000s saw static ecosystems around autonomous execution. What was once a messaging interface is becoming an action layer.90 Source: Google Trends via Glimpse (5/15/24), OpenAI (3/25) AI Agent Interest (Google Searches) usage increases – and as usage increases, so does demand for compute. We’re seeing it across every layer: more queries, more models, more tokens per task. The appetite for AI isn't slowing down. It’s growing

behavior). 
 You can set up guardrails that address risks you’ve already identified for your use case and layer 
 in additional ones as you uncover new vulnerabilities. Guardrails are a critical component of any guardrails Set up guardrails that address the risks you’ve already identified for your use case and layer in additional ones as you uncover new vulnerabilities. We’ve found the following heuristic to be

America’s largest ecommerce and fintech company, partnered with 
 OpenAI to build a development platform layer to solve that. It’s called Verdi, and it’s powered 
 by GPT-4o and GPT-4o mini. Today, it helps their

task or input, which is dynamic. • Role prompt: Frames the model’s output style and voice. It adds a layer of specificity and personality. Prompt Engineering February 2025 19 Distinguishing between system