Google DeepMind has published a research article in the journal Nature outlining their new approach to solving mathematical and computer science problems, called FunSearch. FunSearch is a combination of the words “Function” and “Search” and stands out for its use of LLM, or AI based on Large Language Models, that are pretrained and then used to solve problems alongside computer code. This helps ensure the accuracy of the answers provided.
The results obtained are functions in computer code format, but they come with innovative thinking methods derived from the LLM process. One example presented in this research is the use of FunSearch to find algorithms for the bin packing problem, which involves packing items into specified volumes.
DeepMind highlights that the strength of this AI model lies in its ability to accurately solve mathematical problems, which has been a challenge for previous AI LLM models. Additionally, the out-of-the-box thinking capabilities of LLM open up opportunities for discovering new methods for solving long-standing mathematical problems or addressing problems that currently don’t have a known solution.
TLDR: Google DeepMind has introduced FunSearch, an innovative approach that combines AI and computer code to solve mathematical and computer science problems. Using a Large Language Model, FunSearch ensures accurate answers while also promoting creative problem-solving methods. This has the potential to revolutionize problem-solving in mathematics and tackle previously unsolvable problems.
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