


Li Auto's Mind GPT large model has passed national registration, and the training data scale reaches 3 trillion Tokens
According to news from this website on March 28, Li Auto announced that its fully self-developed multi-model cognitive large model Mind GPT has officially passed the national "Interim Measures for Generative Artificial Intelligence Service Management" registration, becoming the first automobile manufacturer to pass the registration Self-developed large model.

According to reports, Mind GPT is a fully self-developed multi-modal cognitive large-scale model implemented in the automotive smart cockpit, with a training data scale of 30,000 Billion Tokens. Li Auto said:
Mind GPT is a large model that can be used. It is also the only large model in the industry that can be used without any command words. It is also the only large model in the industry that is truly built around automotive scenarios. Model.
It still has the concept of comprehensive evolution of hearing and execution capabilities, and supports the ability to speak freely in dialects, speak freely in commands, simple mode, and the ability to wake up the entire car at all times.
Starting from January 10, 2023, my country has begun to implement the "Regulations on the In-depth Synthesis Management of Internet Information Services", and from August 15, 2023, the "Interim Measures for the Management of Generative Artificial Intelligence Services" will be implemented 》.
The first and second batch of deep synthesis service algorithm registration information announcements were released on June 20 and September 1, 2023, and the third batch of announcements were released on January 5, 2024. 2 The fourth batch of announcements will be announced on March 18. You can view the currently online AI large model experience portal through the "AI Large Model Collection" on the App discovery page of this site.
The above is the detailed content of Li Auto's Mind GPT large model has passed national registration, and the training data scale reaches 3 trillion Tokens. For more information, please follow other related articles on the PHP Chinese website!

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