Sharing insights on data architecture, governance, and middle platforms, exploring AI in data, and linking data with business scenarios.
Amid a global digital surge, 45% of China’s central state‑owned enterprises have deployed the DeepSeek large‑model platform, rapidly integrating AI across energy, power, telecom, construction and other sectors to boost intelligent transformation and operational efficiency.
Compiled by Tsinghua University experts, this guide systematically analyzes the DeepSeek‑R1 inference model and DeepResearch platform, offering multi‑model comparisons, real‑world case studies, and end‑to‑end AI‑driven solutions from data collection to report generation for researchers.
During DeepSeek’s Open‑Source Week (Feb 24‑28), five production‑tested projects were released, spanning GPU‑optimized MLA kernels, MoE communication libraries, high‑performance FP8 GEMM, dual‑pipeline parallelism, and a AI‑focused distributed file system, each delivering significant performance and efficiency gains for large‑scale AI workloads.
The National Data Bureau reviews its 2024 achievements in data policy, infrastructure, and ecosystem development, and outlines an ambitious 2025 roadmap to strengthen data governance, marketization, digital economy growth, and international cooperation, aiming to boost China’s digital transformation.
This article provides a comprehensive tutorial on locally deploying the 671‑billion‑parameter DeepSeek R1 model using Ollama, covering model selection, hardware requirements, dynamic quantization, detailed installation steps, performance observations, and practical recommendations for consumer‑grade hardware.
This article examines DeepSeek’s various versions, detailing their core modules, underlying principles, architecture diagrams, and performance metrics, while illustrating the internal logic and advantages of each model to guide enthusiasts, professionals, and practitioners toward deeper AI innovation insights.
This article offers a comprehensive, multi‑angle analysis of constructing and applying data indicator systems, detailing their necessity, principles, and processes, and presenting concrete case studies from finance and e‑commerce, while also addressing common challenges such as data quality, organizational coordination, sustainability, and strategies to overcome them.
Facing frequent “service busy” errors on DeepSeek’s website, this guide shows how to bypass those limits by pairing a local client such as Cherry Studio or Chatbox with cloud‑based API services from providers like Alibaba Cloud, Huawei, ByteDance, Tencent, or Baidu, enabling smooth, cost‑aware access to the top‑tier DeepSeek‑R1‑671B model.
This article analyzes DeepSeek's V3 and R1 large language models, detailing their low‑cost Mixture‑of‑Experts architecture, Multi‑Head Latent Attention redesign, distributed training optimizations, and reasoning‑focused innovations that together challenge traditional GPU/NPU compute demands.
This document, authored by a postdoctoral team at Tsinghua University's New Media Research Center, provides a detailed, image‑rich tutorial on using the DeepSeek AI model, aiming to help users better understand and apply the technology through clear visual instructions.
