{"id":6851,"date":"2023-10-27T19:21:39","date_gmt":"2023-10-27T19:21:39","guid":{"rendered":"https:\/\/dailyai.com\/?p=6851"},"modified":"2023-10-27T22:55:24","modified_gmt":"2023-10-27T22:55:24","slug":"ai-subjected-to-tests-on-theory-of-mind-and-systematic-generalization","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/10\/ai-subjected-to-tests-on-theory-of-mind-and-systematic-generalization\/","title":{"rendered":"AI utsettes for tester av Theory of Mind og systematisk generalisering"},"content":{"rendered":"<p><b>Forskere har introdusert FANToM, en ny benchmark som er utviklet for \u00e5 teste og evaluere store spr\u00e5kmodellers (LLM) forst\u00e5else og anvendelse av Theory of Mind (ToM).<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Theory of Mind refererer til evnen til \u00e5 tillegge seg selv og andre oppfatninger, \u00f8nsker og kunnskap, og til \u00e5 forst\u00e5 at andre har andre oppfatninger og perspektiver enn en selv.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">ToM anses som grunnleggende for den bevisstheten som intelligente dyr besitter. I tillegg til mennesker anses primater som orangutanger, gorillaer og sjimpanser \u00e5 ha ToM, i tillegg til enkelte ikke-primater som papeg\u00f8yer og medlemmer av kragefuglfamilien.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Etter hvert som AI-modellene blir mer komplekse, s\u00f8ker AI-forskere etter nye metoder for \u00e5 evaluere evner som ToM.<\/span><\/p>\n<p><a href=\"https:\/\/hyunw.kim\/fantom\/\"><span style=\"font-weight: 400;\">En ny m\u00e5lestokk kalt FANToM<\/span><\/a><span style=\"font-weight: 400;\">som er utviklet av forskere fra Allen Institute for AI, University of Washington, Carnegie Mellon University og Seoul National University, utsetter maskinl\u00e6ringsmodeller for dynamiske scenarier som gjenspeiler interaksjoner i det virkelige liv.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Med FANToM g\u00e5r karakterer inn og ut av samtaler, noe som utfordrer AI-modellene til \u00e5 opprettholde en n\u00f8yaktig forst\u00e5else av hvem som vet hva til enhver tid.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ved \u00e5 utsette store spr\u00e5kmodeller (LLM-er) for FANToM viste det seg at selv de mest avanserte modellene sliter med \u00e5 opprettholde en konsistent ToM.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Modellenes prestasjoner var betydelig lavere enn de menneskelige deltakernes, noe som understreker AIs begrensninger n\u00e5r det gjelder \u00e5 forst\u00e5 og navigere i komplekse sosiale interaksjoner.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Faktisk dominerte menneskene alle kategorier, som vist nedenfor.\u00a0<\/span><\/p>\n<figure id=\"attachment_6852\" aria-describedby=\"caption-attachment-6852\" style=\"width: 1024px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-6852 size-large\" src=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-1024x213.png\" alt=\"AI ToM\" width=\"1024\" height=\"213\" srcset=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-1024x213.png 1024w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-300x63.png 300w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-768x160.png 768w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-370x77.png 370w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-800x167.png 800w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-740x154.png 740w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-20x4.png 20w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-1320x275.png 1320w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart-230x48.png 230w, https:\/\/dailyai.com\/wp-content\/uploads\/2023\/10\/scores_barchart.png 1367w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption id=\"caption-attachment-6852\" class=\"wp-caption-text\">Mennesker var langt bedre til \u00e5 svare p\u00e5 ToM-relaterte sp\u00f8rsm\u00e5l sammenlignet med popul\u00e6re LLM-er. Kilde: <a href=\"https:\/\/hyunw.kim\/fantom\/\">FANToM<\/a>.<\/figcaption><\/figure>\n<p><span style=\"font-weight: 400;\">Et interessant sidepoeng er at oktoberversjonen av GPT-4-modellen ble utkonkurrert av en tidligere juni-versjon, noe som kan underbygge nylige anekdoter blant brukerne om at <\/span><a href=\"https:\/\/dailyai.com\/nb\/2023\/07\/is-chatgpt-getting-worse-heres-everything-we-know-so-far\/\"><span style=\"font-weight: 400;\">ChatGPT blir stadig verre<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">FANToM avsl\u00f8rte ogs\u00e5 teknikker for \u00e5 forbedre LLM ToM, for eksempel tankekjederesonnement og andre finjusteringsmetoder. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Men gapet mellom AI og menneskelige ToM-ferdigheter er fortsatt stort.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">AI tar store sprang mot menneskelignende spr\u00e5kferdigheter<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">I en noe relatert, men separat <\/span><a href=\"https:\/\/www.nature.com\/articles\/d41586-023-03272-3\"><span style=\"font-weight: 400;\">studie publisert i Nature<\/span><\/a><span style=\"font-weight: 400;\">utviklet forskere et nevralt nettverk som er i stand til \u00e5 generalisere spr\u00e5k p\u00e5 samme m\u00e5te som mennesker.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dette nye nevrale nettverket viste en imponerende evne til \u00e5 integrere nyinnl\u00e6rte ord i sitt eksisterende vokabular. Deretter kunne det bruke disse ordene i ulike sammenhenger, en kognitiv ferdighet som kalles systematisk generalisering.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Mennesker har en naturlig evne til systematisk generalisering, slik at de s\u00f8ml\u00f8st innlemmer nye ord i repertoaret sitt.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">N\u00e5r noen for eksempel har l\u00e6rt seg begrepet \"photobomb\", kan de bruke det i ulike situasjoner nesten umiddelbart. Det dukker hele tiden opp nye slanguttrykk, og mennesker tar dem naturlig inn i ordforr\u00e5det sitt.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Forskerne utsatte b\u00e5de sitt eget tilpassede nevrale nettverk og ChatGPT for en rekke tester, og fant ut at ChatGPT l\u00e5 etter den tilpassede modellen i ytelse.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Mens LLM-er som ChatGPT utmerker seg i mange samtalescenarier, viser de merkbare inkonsekvenser og mangler i andre, et problem som dette nye nevrale nettverket tar tak i.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For \u00e5 unders\u00f8ke dette aspektet ved spr\u00e5klig kommunikasjon gjennomf\u00f8rte forskerne et eksperiment med 25 deltakere, der de vurderte deres evne til \u00e5 bruke nyinnl\u00e6rte ord i ulike sammenhenger. <\/span><span style=\"font-weight: 400;\">Fors\u00f8kspersonene ble introdusert for et pseudospr\u00e5k best\u00e5ende av nonsensord som representerte ulike handlinger og regler.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Etter en oppl\u00e6ringsfase utmerket deltakerne seg ved \u00e5 anvende disse abstrakte reglene p\u00e5 nye situasjoner, noe som viste systematisk generalisering.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Da det nyutviklede nevrale nettverket ble eksponert for denne oppgaven, speilet det den menneskelige prestasjonen. <\/span><span style=\"font-weight: 400;\">N\u00e5r ChatGPT ble utsatt for den samme utfordringen, slet den imidlertid betydelig, og mislyktes mellom 42 og 86% av tiden, avhengig av den spesifikke oppgaven.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Dette er viktig av to grunner. For det f\u00f8rste kan man hevde at dette nye nevrale nettverket effektivt utkonkurrerte GPT-4 p\u00e5 denne spesifikke oppgaven - noe som er imponerende nok. For det andre viser denne studien nye metoder for \u00e5 l\u00e6re AI-modeller \u00e5 generalisere nytt spr\u00e5k p\u00e5 samme m\u00e5te som mennesker.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Elia Bruni, spesialist p\u00e5 naturlig spr\u00e5kprosessering ved universitetet i Osnabr\u00fcck i Tyskland, beskriver det slik: \"Det \u00e5 tilf\u00f8re systematikk til nevrale nettverk er en stor sak.\"<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Til sammen tilbyr disse to studiene nye tiln\u00e6rminger til oppl\u00e6ring av mer intelligente AI-modeller som kan konkurrere med mennesker p\u00e5 kritiske omr\u00e5der som lingvistikk og Theory of Mind. <\/span><\/p>","protected":false},"excerpt":{"rendered":"<p>Forskere har introdusert FANToM, en ny benchmark som er utviklet for \u00e5 teste og evaluere store spr\u00e5kmodellers (LLM) forst\u00e5else og anvendelse av Theory of Mind (ToM). Theory of Mind refererer til evnen til \u00e5 tillegge seg selv og andre oppfatninger, \u00f8nsker og kunnskap, og til \u00e5 forst\u00e5 at andre har oppfatninger og perspektiver som er forskjellige fra ens egne.  ToM anses som grunnleggende for den bevisstheten intelligente dyr besitter. I tillegg til mennesker anses ogs\u00e5 primater som orangutanger, gorillaer og sjimpanser \u00e5 ha ToM, i tillegg til enkelte ikke-primater som papeg\u00f8yer og medlemmer av kr\u00e5kefuglfamilien.  Som AI-modeller<\/p>","protected":false},"author":2,"featured_media":6853,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[404,115,105,93],"class_list":["post-6851","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-agi","tag-chatgpt","tag-machine-learning","tag-openai"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI subjected to tests on Theory of Mind and systematic generalization | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers have introduced FANToM, a novel benchmark designed to rigorously test and evaluate large language models\u2019 (LLMs) understanding and application of Theory of Mind (ToM).\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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