AI in the Enterprise Lessons from seven frontier companiesContents A new way to work 3 Executive summary 5 Seven lessons for enterprise AI adoption Start with evals 6 Embed AI into your products new models and capabilities. Our Applied Team turns those models into products, like ChatGPT Enterprise and our API. And our Deployment Team takes these products into companies to address their most shapes future products and models. 4 AI in the EnterpriseExecutive summary Seven lessons for enterprise AI adoption 01 Start with evals Use a systematic evaluation process to measure how 
 models perform

challengers are racing to build and deploy the next layers of AI infrastructure: agentic interfaces, enterprise copilots, real-world autonomous systems, and sovereign models. Rapid advances in artificial intelligence smartphones, IOT devices, robotics, etc. Source: Weiss et al. ‘AI Index: Mapping the $4 Trillion Enterprise Impact’ via Morgan Stanley (10/23) Enabling Infrastructure CPUs Big Data / Cloud GPUs Computing NVIDIA Co-Founder & CEO Jensen Huang @ COMPUTEX 2025 – 5/2567 ‘Traditional’ Enterprise AI Adoption = Rising Priority68 Enterprise AI Focus – S&P 500 Companies = 50% & Rising Talking-the-Talk . Source:

workflows effectively. While it’s tempting to immediately build a fully autonomous agent with complex architecture, customers typically achieve greater success with an incremental approach. In general, orchestration technical issues, system outages, or product troubleshooting." "Sales Assistant Agent" "You help enterprise clients browse the product catalog, recommend suitable solutions, and facilitate purchase transactions guide to building agents More resources API Platform OpenAI for Business OpenAI Stories ChatGPT Enterprise OpenAI and Safety Developer Docs OpenAI is an AI research and deployment company. Our mission

TensorFlow 和 PyTorch 和 Hugging Face Transformers 等。 TensorFlow 架构图 (图源：https://www.geeksforgeeks.org/architecture-of- tensorflow/) 12 / 32 LLM 基础设施：编程语言 LLM 的训练和应用通常使用多种编程语言，取决于任务的需求和团 队的偏好。 。它的广泛使用得 益于其简洁的语法、强大的库支持（如 渐司空见惯。 分析公司 O’Reilly 日前发布一份 《2023 Generative AI in the Enterprise》报告， 报告中指出， 。 图源：https://www.oreilly.com/radar/generative-ai-in-the-enterprise/ 21 / 32 AI 编程工具：插件、IDE、终端 目前最常见的 AI 编程工具大多以插件、IDE 和终端

and inference efficiency of DeepSeek 67B (Dense) and DeepSeek-V2. Contents 1 Introduction 4 2 Architecture 6 2.1 Multi-Head Latent Attention: Boosting Inference Efficiency . . . . . . . . . . . . . 6 DeepSeekMoE: Training Strong Models at Economical Costs . . . . . . . . . . . . 9 2.2.1 Basic Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2 Device-Limited Routing characterized by economical training and efficient inference through an innovative Transformer architecture. It is equipped with a total of 236B parameters, of which 21B are activated for each token, and

delivering generalized performance 2 Why TVM? XTVM for Speech Synthesis - WaveRNN-style model architecture - Autoregressive sampling net running at faster than real-time - Compute split between GRU

the accuracy from there. Adapt to model updates It’s important for you to stay on top of model architecture changes, added data, and capabilities. Try out newer model versions and adjust your prompts to