{"id":2000106173,"date":"2026-03-24T09:36:59","date_gmt":"2026-03-24T07:36:59","guid":{"rendered":"https:\/\/new.igihe.com\/?p=2000106173"},"modified":"2026-03-24T09:38:02","modified_gmt":"2026-03-24T07:38:02","slug":"new-study-finds-brain-inspired-computers-can-solve-advanced-math-efficiently","status":"publish","type":"post","link":"https:\/\/new.igihe.com\/english\/new-study-finds-brain-inspired-computers-can-solve-advanced-math-efficiently\/","title":{"rendered":"New study finds brain\u2011inspired computers can solve advanced math efficiently"},"content":{"rendered":"\n

This research involved a type of computing hardware known as neuromorphic computers, which are built to imitate how the human brain processes information. <\/p>\n\n\n\n

Scientists have now shown that these machines can successfully solve partial differential equations (PDEs), a class of problems that are foundational to physics simulations, weather forecasting, fluid dynamics, and engineering tasks.<\/p>\n\n\n\n

Until now, solving these equations typically required massive supercomputers that use enormous amounts of energy. <\/p>\n\n\n\n

In contrast, the brain\u2011inspired systems demonstrated similar capabilities while using only a fraction of the power, suggesting a path toward far more energy\u2011efficient computing for scientific research and national security applications.<\/p>\n\n\n\n

Researchers Bradley H. Theilman and James B. Aimone developed a new algorithm that allows this neuromorphic hardware to tackle such advanced calculations. <\/p>\n\n\n\n

According to the team, the structure of this algorithm reflects how the brain might perform complex computations naturally, offering insight into both computing and brain function.<\/p>\n\n\n\n

The study also highlights that these findings could greatly impact efforts to build the next generation of low\u2011energy computational systems. <\/p>\n\n\n\n

If further developed, brain\u2011inspired computing could provide powerful alternatives to current systems used in high\u2011performance research, all while reducing electrical power demands. <\/p>\n\n\n\n

\"\"
Brain inspired machines are better at math than expected.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"

Researchers in the U.S. Department of Energy\u2019s Sandia National Laboratories have discovered that computers modeled after the human brain can handle very complex mathematical problems traditionally reserved for supercomputers. <\/p>\n","protected":false},"author":139,"featured_media":2000106174,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[151,69],"byline":[201],"hashtag":[],"class_list":["post-2000106173","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science-technology","tag-editors-choice","tag-homehighlights","byline-rania-umutoni"],"bylines":[{"id":201,"name":"Rania Umutoni","slug":"rania-umutoni","description":"","image":{"id":0,"url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&f=y&r=g","alt":"Default avatar","title":"Default avatar","caption":"","mime_type":"image\/jpeg","sizes":[]},"user_id":139}],"contributors":[{"id":201,"name":"Rania Umutoni","slug":"rania-umutoni","description":"","image":{"id":0,"url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&f=y&r=g","alt":"Default avatar","title":"Default avatar","caption":"","mime_type":"image\/jpeg","sizes":[]},"user_id":139}],"featured_image":{"id":2000106174,"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","alt":"","caption":"","mime_type":"image\/jpeg","width":1920,"height":1080,"sizes":{"thumbnail":{"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","width":150,"height":84},"medium":{"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","width":300,"height":169},"medium_large":{"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","width":768,"height":432},"large":{"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","width":1024,"height":576},"full":{"url":"https:\/\/new.igihe.com\/english\/wp-content\/uploads\/2026\/03\/brain-cpu-chip-motherboard.jpg","width":1920,"height":1080}}},"_links":{"self":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000106173","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/users\/139"}],"replies":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/comments?post=2000106173"}],"version-history":[{"count":3,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000106173\/revisions"}],"predecessor-version":[{"id":2000106318,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000106173\/revisions\/2000106318"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/media\/2000106174"}],"wp:attachment":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/media?parent=2000106173"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/categories?post=2000106173"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/tags?post=2000106173"},{"taxonomy":"byline","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/byline?post=2000106173"},{"taxonomy":"hashtag","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/hashtag?post=2000106173"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}