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Allen AI’s Tülu 3 Just Became DeepSeek’s Unexpected Rival
- Allen AI has released the new Tülu 3 family of models that are matching or even beating DeepSeek on key benchmarks.
- Tülu 3 is open-source, with Allen AI releasing the complete training pipeline, code, and even their reinforcement learning method called Reinforcement Learning with Verifiable Rewards (RLVR) that made this possible.
- Tülu 3 is built using a unique four-stage training process, which involves strategic data selection, building better responses, learning from comparisons, and Reinforcement Learning with Verifiable Rewards.
- RLVR replaces subjective reward models with concrete verification, which is a technical breakthrough that deserves attention. This technique trains Tülu 3 on the correctness of its answers and results in binary feedback without any room for partial credit or fuzzy evaluation.
- Tülu 3's 405B parameter version performs well in competiting directly with top models in math, coding, and instruction following.
- Allen AI has released complete documentation of the development process including complete training pipelines, data processing tools, evaluation frameworks and implementation specifications.
- This open approach accelerates innovation across the field, enabling developers to build on proven approaches, and sparking a new wave of AI development.
- The success of Tülu 3 is a big moment for open AI development, which changes the industry when open source models match or exceed private alternatives.
- Allen AI's verifiable rewards and multi-stage training techniques pave the way for future AI development, providing a foundation for teams to build upon and push performance even higher.
- Tülu 3's breakthroughs in multiple stages training and verifiable rewards hint at what is coming, and a new wave of AI development has just begun.
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