Reflection Techniques of Open-Source Model Tuning from Llama Outperform Every Major Model Including GPT-4o

The AI world saw an intriguing shift last night when Matt Shumer, the founder of HyperWrite startup, introduced the new large language model (LLM) Reflection 70B, which outperformed all other models in the market such as GPT-4o, Claude 3.5, Gemini 1.5 Pro, and Llama 3.1 405B.

An interesting aspect of Reflection 70B is that it wasn’t developed from scratch but fine-tuned from the open-source Llama 3.1 70B model, and yet it managed to surpass the much larger Llama 3.1 405B.

The key feature of the Reflection model that led to its victory is its tuning technique that enables the model to “know when it’s wrong” and correct its own answers before releasing them to the outside world (hence the name reflection).

Moreover, the Reflection model separates the planning and chain of thought processes, resulting in more accurate and easily understandable answers.

Shumer revealed that the tuning of the Reflection model was done using a tuning tool from the startup Glaive, known for its expertise in fine-tuning specific models. He also plans to use Glaive with other models in the future.

The Reflection 70B model is open-source and available on Hugging Face, with the Reflection 405B model expected to be released soon.

TLDR: Reflection 70B, a top open-source LLM, outperformed other models with its unique tuning technique, and a larger model, Reflection 405B, is on the way. Built with GlaiveAI.