{"id":69103,"date":"2024-09-14T09:00:00","date_gmt":"2024-09-14T14:00:00","guid":{"rendered":"https:\/\/blogs.uninter.edu.mx\/ESCAT\/?p=69103"},"modified":"2024-08-06T12:27:19","modified_gmt":"2024-08-06T17:27:19","slug":"alphaproof-mathematician-ai","status":"publish","type":"post","link":"https:\/\/blogs.uninter.edu.mx\/ESCAT\/index.php\/alphaproof-mathematician-ai\/","title":{"rendered":"AlphaProof and AlphaGeometry2: The new AI mathematician #ESCAT #Uninter"},"content":{"rendered":"
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\"Esta<\/a><\/figure>\n<\/div>\n\n\n

AlphaProof solved about 83% of math Olympiad problems from the past 25 years.<\/p>\n\n\n\n\n\n\n\n

As artificial intelligence (AI) models continue to develop, Google announces that two AI systems from Google DeepMind together solved four of the six problems in this year\u2019s International Mathematical Olympiad. According to Google the AI systems competed with two silver medalists high school students, eventually beating them.<\/p>\n\n\n\n

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During the competition AlphaProof and AlphaGeometry2 were able to solve a range of math problems step-by-step. This is expected to be a \u201cgrand challenge\u201d in machine learning and has been beyond the reach of other state-of-the-art AI systems. <\/p>\n\n\n\n

The \u2018DeepMind\u2019 behind AlphaProof and AlphaGeometry2<\/strong><\/h2>\n\n\n\n

Google explained that AlphaProof teaches itself by \u2018trial-and-error\u2019 method without human intervention. This method is known as reinforcement learning. The method is powered by DeepMind\u2019s Go-mastering AlphaGo, Starcraft-crushing AlphaStar and other AI systems developed by Google. <\/p>\n\n\n\n

According to sources, the team first fine-tuned Google\u2019s Gemini model to translate 1 million mathematics problem statements from English into a programming language called Lean. The difficult problems were then given to AlphaProof and AlphaGeometry2 so that they could generate potential solutions. Lastly, they were then checked against possible proof steps, initially made by experts. <\/p>\n\n\n\n

According to Google, the system solved about 83% of math Olympiad problems from the past 25 years compared to its predecessor that could only solve 53%. Moreover, both the AI systems AlphaProof and AlphaGeometry 2 scored 28 out of 42 possible points.<\/p>\n\n\n\n

\u201cThese are extremely hard mathematical problems, and no AI system has ever achieved a high success rate in these types of problems,\u201d Pushmeet Kohli, vice president of research focused on AI for science, DeepMind, highlighted in a press briefing.<\/p>\n\n\n

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AI solving math: Boon or Bane<\/strong><\/h2>\n\n\n\n

The success of AlphaProof and AlphaGeometry 2 in winning a silver medal at the International Mathematical Olympiad might mark a significant milestone in the development of AI. By automating repetitive and laborious tasks, artificial intelligence can help mathematicians focus on more theoretical and creative aspects of their work, thereby resulting in discoveries.<\/p>\n\n\n\n

However, it looks like this can also raise questions about the future of human intelligence. The growing concern in the global economy today is that AI might completely take over human jobs. Early reports suggest that to enhance productivity, enterprises are adopting AI-based technologies. Such initiatives are now replacing human jobs and making us more dependent on machine, It is expected that AI converting into perfectionists for \u2018logical reasoning\u2019 can add to these concerns.<\/p>\n\n\n\n

Another concern can be that the advancements of AI systems might result in increased \u2018cost structures\u2019 of companies. AI models mostly come at high-cost structures. This might lead companies to initiate \u2018cost-cutting\u2019 through reducing employee count.  <\/p>\n\n\n

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Industry reacts<\/strong><\/h2>\n\n\n\n

\u201cAlphaProof and AlphaGeometry2 highlights AI\u2019s growing capability to tackle complex mathematical problems. By successfully solving Olympiad-level problems, these systems demonstrate a remarkable combination of creativity and precise logical reasoning. This accomplishment underscores AI\u2019s potential to enhance human abilities across various scientific and engineering fields,\u201d Devroop Dhar, co-founder and managing director, Primus Partners, explained.<\/p>\n\n\n\n

\u201cThese models serve as a reminder of AI\u2019s enormous potential in advancing mathematics research and problem-solving skills. However, the idea that AI could surpass human mathematicians raises questions about the future of mathematics and how technology will affect our ability to comprehend complex problems,\u201d Heather Dawe, chief data scientist and head of Responsible AI, UK UST, said.<\/p>\n\n\n

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Source: Financial Express<\/a><\/h6>\n\n\n\n

Bachelor’s Degree in Computer Systems Engineering
<\/a>More news about Computer Systems Engineering<\/a><\/p>\n\n\n\n

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AlphaProof solved about 83% of math Olympiad problems from the past 25 years.<\/p>\n","protected":false},"author":22,"featured_media":69110,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[17,22],"tags":[5118,5117,5116,32,156,104,49,62,31,37],"class_list":["post-69103","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ingenieria-en-sistemas-computacionales","category-ingenierias","tag-alphageometry","tag-alphaproof","tag-deepmind","tag-escat","tag-google","tag-ingenierias","tag-sistemas-computacionales","tag-tecnologia","tag-uninter","tag-universidad-internacional"],"yoast_head":"\r\nAlphaProof: The new mathematician AI 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