Artificial Intelligence 3 min read

Application and Practice of Large Models in Intelligent Electric Vehicles

The presentation by NIO senior technology planning expert Chen Jiong explores the development trends of intelligent electric vehicles, showcases how large AI models empower various automotive scenarios, and shares NIO's practical implementations, offering insights on industry-focused solutions, problem‑driven application, and unified architecture design.

DataFunSummit
DataFunSummit
DataFunSummit
Application and Practice of Large Models in Intelligent Electric Vehicles

Chen Jiong – Senior Research Expert, NIO Technology Planning Department

Chen Jiong holds a Ph.D. in Electronic Engineering from Tsinghua University, serves as a committee member of the Chinese Computer Society’s Intelligent Vehicle branch and the Chinese Society of Automotive Engineers’ Sensor branch, mentors graduate students at Fudan and Hefei University of Technology, and has led numerous forward‑looking research and product‑conversion projects, accumulating over 60 patents and 17 journal papers.

Talk Title: Application and Practice of Large Models in Intelligent Electric Vehicles

Talk Outline:

1. Development trends of intelligent electric vehicles

2. Scenarios where large models empower intelligent electric vehicles

3. NIO’s applications and practice

Audience Benefits:

1. How to combine scenarios and deeply cultivate the industry

2. How to drive applications to precisely locate and solve problems

3. How to design a unified architecture that supports applications

system architectureArtificial IntelligenceNIOLarge Modelsautonomous drivingelectric vehicles
DataFunSummit
Written by

DataFunSummit

Official account of the DataFun community, dedicated to sharing big data and AI industry summit news and speaker talks, with regular downloadable resource packs.

0 followers
Reader feedback

How this landed with the community

login Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.