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The company said its FunSearch AI model has an automated ‘evaluator’ to prevent hallucinations, allowing the model to find the best answers for advanced problems.
Google-owned DeepMind claims one of its AI models found a new answer for an unsolved mathematical problem, by tackling one of the biggest issues in large language models (LLMs).
This key issue is the tendency for these AI models to share factually incorrect information, which is commonly referred to as ‘hallucinations’. This issue has been noted in many popular AI models, such as ChatGPT which has faced lawsuits for defaming individuals.
DeepMind claims its AI model – FunSearch – tackles this issue by including an automated “evaluator” that protects against hallucinations and incorrect ideas.
The company tested this model on an unsolved maths problem known as the cap set problem, which involves finding the largest size of a certain type of set. DeepMind claims FunSearch discovered new constructions of large cap sets that go beyond the best known ones.
“In addition, to demonstrate the practical usefulness of FunSearch, we used it to discover more effective algorithms for the ‘bin-packing’ problem, which has ubiquitous applications such as making data centres more efficient,” DeepMind said in a blogpost.
The AI model contains the automated evaluator and a pre-trained LLM that aims to provide “creative solutions” to problems. DeepMind claims the “back-and-forth” of these two components creates an “evolutionary method” of finding the best ways to solve a problem.
Problems are presented to the AI model in the form of code, which includes a procedure to evaluate programs and a seed program used to “initialise a pool of programs”. DeepMind said FunSearch then selects some programs and “creatively builds” upon them.
The results are evaluated and the best ones are added back to the pool of existing programs, which creates a “self-improving loop” according to DeepMind.
“FunSearch demonstrates that if we safeguard against LLMs’ hallucinations, the power of these models can be harnessed not only to produce new mathematical discoveries, but also to reveal potentially impactful solutions to important real-world problems,” DeepMind said.
DeepMind has claimed to hit multiple breakthroughs with the power of AI. Last year, DeepMind claimed its AlphaFold model predicted the structure of nearly every protein known to science – more than 200m in total.
At the end of October, DeepMind claimed the next version of AlphaFold can predict nearly all molecules in the Protein Data Bank – a database for the 3D structures of various biological molecules.
DeepMind also claims that one of its AI models – GraphCast – can predict weather conditions up to 10 days in advance and in a more accurate way than standard industry methods. Meanwhile, the company claims one of its AI models has been used by researchers to create hundreds of new materials in laboratory settings.
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