{"id":7415,"date":"2023-11-15T09:23:17","date_gmt":"2023-11-15T09:23:17","guid":{"rendered":"https:\/\/dailyai.com\/?p=7415"},"modified":"2023-11-15T11:28:59","modified_gmt":"2023-11-15T11:28:59","slug":"googles-graphcast-model-predicts-weather-better-than-the-rest","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/","title":{"rendered":"Googles GraphCast-modell forutsier v\u00e6ret bedre enn resten"},"content":{"rendered":"<p><strong>Google DeepMinds maskinl\u00e6ringsmodell, GraphCast, slo tradisjonelle v\u00e6rvarslingsmetoder med god margin i tidlige tester.<\/strong><\/p>\n<p>\u00c5 forutsi v\u00e6ret n\u00f8yaktig er en vanskelig oppgave som blir eksponentielt mer kompleks jo flere dager frem i tid vi \u00f8nsker \u00e5 forutsi.<\/p>\n<p>Det er derfor meteorologiske organisasjoner er avhengige av verdens kraftigste superdatamaskiner for \u00e5 knuse de komplekse prediksjonsalgoritmene som forteller oss om det kommer til \u00e5 regne i morgen eller ikke.<\/p>\n<p>IFS-modellen (Integrated Forecasting System) som European Centre for Medium-Range Weather Forecasts (ECMWF) bruker, regnes som den mest n\u00f8yaktige europeiske v\u00e6rmodellen. Og GraphCast slo den nettopp med god margin.<\/p>\n<p><a href=\"https:\/\/deepmind.google\/discover\/blog\/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting\/\" target=\"_blank\" rel=\"noopener\">GraphCast<\/a> var i stand til \u00e5 forutsi v\u00e6ret 10 dager i forveien raskere og mer n\u00f8yaktig enn ECMWF i mer enn 90% av 1380 verifikasjonsm\u00e5l.<\/p>\n<p>Det er praktisk \u00e5 vite om du b\u00f8r ta med deg paraplyen p\u00e5 jobb, men det er n\u00e5r det gjelder \u00e5 forutsi ekstreme v\u00e6rhendelser at GraphCast kan gj\u00f8re en betydelig forskjell.<\/p>\n<p>I september, da orkanen Lee var ni dager fra \u00e5 treffe land, jobbet v\u00e6rkontorene hardt for \u00e5 forutsi hvilken by som ville bli hardest rammet av stormen.<\/p>\n<p>IFS-modellen ga en grov sp\u00e5dom om at orkanen ville treffe noen byer i nord\u00f8st, eller muligens ikke treffe dem i det hele tatt. I mellomtiden sp\u00e5dde GraphCast at orkanen Lee ville treffe Nova Scotia.<\/p>\n<p>F\u00f8rst tre dager senere kom IFS til samme konklusjon, som til slutt viste seg \u00e5 v\u00e6re korrekt. Tenk deg hvor mye bedre ressursutnyttelse og beredskap som ville v\u00e6rt mulig med tre dager ekstra.<\/p>\n<p>Pushmeet Kohli, VP for forskning hos Google DeepMind, sa: \"V\u00e6rvarsling er et av de mest utfordrende problemene som menneskeheten har jobbet med i lang, lang tid. Og hvis du ser p\u00e5 hva som har skjedd de siste \u00e5rene med klimaendringene, er dette et utrolig viktig problem.\"<\/p>\n<blockquote class=\"twitter-tweet\">\n<p dir=\"ltr\" lang=\"en\" style=\"text-align: center;\">Vi presenterer GraphCast: v\u00e5r toppmoderne AI-modell som leverer 10-dagers v\u00e6rvarsler med enest\u00e5ende n\u00f8yaktighet p\u00e5 under ett minutt. \ud83c\udf26\ufe0f<\/p>\n<p>Den kan til og med bidra til \u00e5 forutsi syklonenes potensielle baner lenger frem i tid.<\/p>\n<p>Her er hvordan det fungerer. \ud83e\uddf5 <a href=\"https:\/\/t.co\/ygughpkdeP\">https:\/\/t.co\/ygughpkdeP<\/a> <a href=\"https:\/\/t.co\/0Y6DyBXDow\">pic.twitter.com\/0Y6DyBXDow<\/a><\/p>\n<p style=\"text-align: center;\">- Google DeepMind (@GoogleDeepMind) <a href=\"https:\/\/twitter.com\/GoogleDeepMind\/status\/1724443443873624115?ref_src=twsrc%5Etfw\">14. november 2023<\/a><\/p>\n<\/blockquote>\n<p><script async src=\"https:\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script><\/p>\n<h2>Hvordan fungerer det?<\/h2>\n<p>Tradisjonelle modeller som IFS bruker \"numerisk v\u00e6rvarsling\" (NWP). Dette inneb\u00e6rer innsamling av enorme mengder data fra v\u00e6rsensorer, som deretter legges inn i komplekse ligninger som superdatamaskiner behandler.<\/p>\n<p>Ligningene finjusteres av ekspertteam og har blitt stadig mer n\u00f8yaktige, men de krever fortsatt mye databehandlingskraft og tar lang tid \u00e5 komme frem til en prediksjon.<\/p>\n<p>NWP g\u00e5r i hovedsak ut p\u00e5 \u00e5 bruke algoritmer til \u00e5 modellere hvordan atmosf\u00e6ren fungerer for \u00e5 forutsi hva som vil skje videre.<\/p>\n<p>Det GraphCast gj\u00f8r, er mye enklere, men kan ikke gj\u00f8res med tradisjonelle ligninger.<\/p>\n<p>GraphCast-modellen bruker maskinl\u00e6ringsbasert v\u00e6rvarsling (MLWP) og er trent p\u00e5 historiske v\u00e6rdata fra omtrent 50 \u00e5r.<\/p>\n<p>Deretter tar den dataene, og i stedet for \u00e5 lage en modell av atmosf\u00e6ren v\u00e5r, ser den etter m\u00f8nstre i dataene. En AI-modell er god til \u00e5 finne subtile m\u00f8nstre som det er umulig for faste ligninger \u00e5 oppdage.<\/p>\n<p>GraphCast ser i utgangspunktet p\u00e5 de aktuelle v\u00e6rdataene og sier: \"Sist gang jeg s\u00e5 disse forholdene, var det neste som skjedde ...\", og kommer deretter med en sp\u00e5dom.<\/p>\n<p>Detaljniv\u00e5et, eller oppl\u00f8sningen, i GraphCast-sp\u00e5dommene er ikke like god som i tradisjonelle modeller, men den er mye mer n\u00f8yaktig og mye raskere.<\/p>\n<p>Mens en superdatamaskin m\u00e5 bruke timevis p\u00e5 \u00e5 knuse v\u00e6rdata for \u00e5 komme med en sp\u00e5dom, kan GraphCast produsere et resultat p\u00e5 mindre enn ett minutt p\u00e5 en enkelt Google TPU v4-maskin.<\/p>\n<p>MLWP er i stor grad avhengig av historiske data produsert av tradisjonelle NWP-modeller, s\u00e5 den vil ikke erstatte dem helt enn\u00e5.<\/p>\n<p>Ved \u00e5 bruke et verkt\u00f8y som GraphCast sammen med dagens metoder vil man imidlertid kunne forutsi ekstreme v\u00e6rhendelser raskere og mer n\u00f8yaktig.<\/p>\n<p>Google DeepMind gj\u00f8r GraphCast til \u00e5pen kildekode, og det brukes allerede av ECMWF.<\/p>","protected":false},"excerpt":{"rendered":"<p>Google DeepMinds maskinl\u00e6ringsmodell, GraphCast, slo tradisjonelle v\u00e6rvarslingsmetoder med god margin i tidlige tester. \u00c5 forutsi v\u00e6ret n\u00f8yaktig er en vanskelig oppgave som blir eksponentielt mer kompleks jo flere dager inn i fremtiden vi \u00f8nsker \u00e5 forutsi. Derfor bruker meteorologiske organisasjoner verdens kraftigste superdatamaskiner til \u00e5 knuse de komplekse algoritmene som forteller oss om det vil regne i morgen eller ikke. IFS-modellen (Integrated Forecasting System) som European Centre for Medium-Range Weather Forecasts (ECMWF) bruker, regnes som den mest n\u00f8yaktige europeiske v\u00e6rmodellen. Og GraphCast slo den nettopp med god margin.<\/p>","protected":false},"author":6,"featured_media":7417,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[83],"tags":[102,105],"class_list":["post-7415","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product","tag-google","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Google\u2019s GraphCast model predicts weather better than the rest | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nb\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Google\u2019s GraphCast model predicts weather better than the rest | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Google DeepMind\u2019s machine learning model, GraphCast, beat traditional weather forecasting methods by some distance in early testing. Predicting the weather accurately is a difficult task that becomes exponentially complex the more days into the future we want to predict. This is why meteorological organizations rely on the world\u2019s most powerful supercomputers to crunch the complex predictive algorithms that tell us if it will rain tomorrow or not. The Integrated Forecasting System (IFS) model that the European Centre for Medium-Range Weather Forecasts (ECMWF) uses is considered the most accurate European weather model. And GraphCast just beat it by a long way.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/nb\/2023\/11\/googles-graphcast-model-predicts-weather-better-than-the-rest\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2023-11-15T09:23:17+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-15T11:28:59+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/11\/weather-prediction.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"373\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Eugene van der Watt\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta 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