Intern Large Models

@intern_lm

Intern-series large models by Shanghai AI Laboratory.

github.com/InternLM

Joined June 2023

Intern Large Models
@intern_lm
Aug 6
🔥Shanghai AI Lab open-sourced Mobius, whose transformation from Transformer bears a striking parallel to the RNN → Transformer shift: (A) Token-level recurrence → full connectivity. (B) Knowledge-level recurrence → full connectivity. 🤠The last revolution pushed foundation
Intern Large Models
@intern_lm
Aug 5
Bowen Zhou, distilled the consensus into three operational principles: AI can act on behalf of humans, but it cannot assume responsibility on their behalf. Every authorization humans give to AI should be revocable, and every action should be accountable. The pace at which agency
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Intern Large Models
@intern_lm
Aug 4
Bowen Zhou, Director and Chief Scientist of Shanghai AI Laboratory，asked Nicholas B. Dirks whether external evaluations, red teaming, and third-party verification were enough to justify handing real-world authority to AI. "No," Nitzberg replied. He compared AI systems to
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Intern Large Models
@intern_lm
Aug 3
The word "agent" carries two very different meanings. In AI, an agent is a system that can perceive, plan, and act. In law, an agent receives authority but also assumes a duty of loyalty and can be held accountable. Today's AI agents can receive the first of those things. They
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Intern Large Models
@intern_lm
Jul 28
🔥Introducing Visual Pretraining (VP) 👀: a new, scalable pretraining paradigm for foundation models. 😉It enables models to learn directly from visual documents 📖 and outperforms text-only pretraining across backbones and benchmarks. 📈 Explore the paper and our most