Can Llama 8B Outsmart GPT-4o Using Search Engines?
Recently, a new study has brought excitement, demonstrating that Large Language Models (LLMs) can significantly enhance their performance through search functionalities. Notably, the Llama3.1 model with only 800 million parameters, after 100 searches, performed on par with GPT-4o in Python code generation tasks.
This idea seems reminiscent of Rich Sutton's pioneering work in reinforcement learning, particularly his 2019 classic blog post, "The Bitter Lesson." He emphasized the power of general methods as computational capabilities improve, highlighting "search" and "learning" as excellent choices that can continue to scale.
Recently, a new study has brought excitement, demonstrating that Large Language Models (LLMs) can significantly enhance their performance through search functionalities. Notably, the Llama3.1 model with only 800 million parameters, after 100 searches, performed on par with GPT-4o in Python code generation tasks.
This idea seems reminiscent of Rich Sutton's pioneering work in reinforcement learning, particularly his 2019 classic blog post, "The Bitter Lesson." He emphasized the power of general methods as computational capabilities improve, highlighting "search" and "learning" as excellent choices that can continue to scale.