{"id":601250,"date":"2023-12-15T18:14:39","date_gmt":"2023-12-15T15:14:39","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/deepminds-ai-finds-new-solution-to-decades-old-math-puzzle\/"},"modified":"2023-12-15T18:14:39","modified_gmt":"2023-12-15T15:14:39","slug":"deepminds-ai-finds-new-solution-to-decades-old-math-puzzle","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/deepminds-ai-finds-new-solution-to-decades-old-math-puzzle\/","title":{"rendered":"#DeepMind’s AI finds new solution to decades-old math puzzle"},"content":{"rendered":"
\n DeepMind has used a large language model (LLM) to generate a novel solution to one of humanity\u2019s toughest math problems \u2014 in a breakthrough that could herald a new era in AI development.\u00a0<\/span><\/p>\n

The model, known as FunSearch, discovered a solution to the so-called \u201ccap set puzzle.\u201d The decades-old math conundrum essentially comes down to <\/span>how many dots you can joint down on a page while drawing lines between them, without three of them ever forming a straight line.<\/span><\/p>\n

If that gave you a migraine, don\u2019t worry. What\u2019s important to note is that the problem has never been solved, and researchers have only ever found solutions for small dimensions. Until now.\u00a0<\/span><\/p>\n

FunSearch successfully discovered <\/span>new constructions for large cap sets that far exceeded the best-known ones. <\/span>While the LLM didn\u2019t solve the cap set problem once and for all (contrary to some of the news<\/a> headlines swirling around), <\/span>it did find <\/span>facts new to science<\/a>.<\/span><\/p>\n

\u201cTo the best of our knowledge, this shows the first scientific discovery \u2013 a new piece of verifiable knowledge about a notorious scientific problem \u2014 using an LLM,\u201d wrote the researchers in a paper published in <\/span>Nature<\/span><\/a> this week.<\/span><\/p>\n

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In <\/span>previous experiments<\/span><\/a>, researchers have used large language models to solve maths problems<\/span> with known solutions.<\/span><\/p>\n

FunSearch works by combining a pre-trained LLM, in this case a version of Google\u2019s PaLM 2, with an automated \u201cevaluator.\u201d This fact-checker guards against the production of false information.\u00a0<\/span><\/p>\n

LLMs have been shown to regularly produce so-called \u201c<\/span>hallucinations<\/span>\u201d \u2014 basically when they just make shit up and present it as fact. This has, naturally, limited their usefulness in making verifiable scientific discoveries. However, researchers at the London-based lab claim that the use of an in-built fact-checker makes FunSearch different.\u00a0\u00a0<\/span><\/p>\n

FunSearch engages in a continuous back-and-forth dance between the LLM and the evaluator. This process transforms initial solutions into new knowledge.\u00a0<\/span><\/p>\n

What also makes the tool quite promising for scientists is that <\/span>it outputs programs that reveal <\/span>how<\/span><\/i> its solutions are constructed, rather than just what the solutions are.\u00a0<\/span><\/p>\n

\u201cWe hope this can inspire further insights in the scientists who use FunSearch, driving a virtuous cycle of improvement and discovery,\u201d said the researchers.<\/span>\n <\/div>\n

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Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

DeepMind has used a large language model (LLM) to generate a novel solution to one of humanity\u2019s toughest math problems \u2014 in a breakthrough that could herald a new era in AI development.\u00a0 The model, known as FunSearch, discovered a solution to the so-called \u201ccap set puzzle.\u201d The decades-old math conundrum essentially comes down to…<\/p>\n","protected":false},"author":1,"featured_media":601251,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/img-cdn.tnwcdn.com\/image\/tnw-blurple?filter_last=1&fit=1280,640&url=https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2023\/12\/math-code-science-AI.jpg&signature=c7d51f05d2f90d69e7dd1049a3691f58","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[],"class_list":["post-601250","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/601250","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=601250"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/601250\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/601251"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=601250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=601250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=601250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}