{"id":3464,"date":"2023-08-01T16:34:30","date_gmt":"2023-08-01T16:34:30","guid":{"rendered":"https:\/\/dailyai.com\/?p=3464"},"modified":"2023-08-02T15:13:13","modified_gmt":"2023-08-02T15:13:13","slug":"ai-matches-college-undergrads-solving-reasoning-problems","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2023\/08\/ai-matches-college-undergrads-solving-reasoning-problems\/","title":{"rendered":"AI matcher studenter som l\u00f8ser resonneringsproblemer"},"content":{"rendered":"

En studie utf\u00f8rt av psykologer ved UCLA har vist at GPT-3 er omtrent like gode til \u00e5 l\u00f8se resonnementsproblemer som studenter p\u00e5 universitetsniv\u00e5.<\/strong><\/p>\n

Vi vet at LLM-er som GPT-3 er gode til \u00e5 generere responser basert p\u00e5 dataene de er oppl\u00e6rt p\u00e5, men deres evne til \u00e5 resonnere er tvilsom. Analogisk resonnering er menneskets evne til \u00e5 ta det vi l\u00e6rer fra en erfaring som ikke er relatert til noe annet, og anvende det p\u00e5 et problem vi ikke har st\u00e5tt overfor f\u00f8r.<\/span><\/p>\n

Det er den evnen du har n\u00e5r du skal svare p\u00e5 et sp\u00f8rsm\u00e5l du aldri har sett f\u00f8r. Du kan resonnere deg gjennom det basert p\u00e5 tidligere problemer du har l\u00f8st. Og ut fra forskningen ser det ut til at GPT-3 ogs\u00e5 har utviklet den evnen.<\/span><\/p>\n

Den <\/span>UCLA-forskere<\/span><\/a> sette GPT-3 til \u00e5 jobbe med et sett problemer som ligner p\u00e5 <\/span>Raven's Progressive Matrices<\/span><\/a> som g\u00e5r ut p\u00e5 \u00e5 forutsi neste bilde i en bildeserie. Her er en enkel oppgave du kan pr\u00f8ve.<\/span><\/p>\n

\"Eksempel
Eksempel p\u00e5 Raven Progressive Matrix - Kilde: Wikipedia<\/a><\/figcaption><\/figure>\n

GPT-3 klarte seg godt sammenlignet med de 40 UCLA-studentene som ble bedt om \u00e5 ta den samme testen. Den kunstige intelligensen svarte riktig i 80% av tilfellene, mens de 40 studentene i gjennomsnitt fikk rundt 60%. Toppstudentene fikk omtrent samme poengsum som GPT-3.<\/span><\/p>\n

Professor i psykologi ved UCLA, Hongjing Lu, som er hovedforfatter av studien, sier: \"Overraskende nok klarte GPT-3 seg ikke bare omtrent like bra som mennesker, men den gjorde ogs\u00e5 lignende feil.\"<\/span><\/p>\n

Forskerne ba ogs\u00e5 GPT-3 om \u00e5 l\u00f8se noen ordassosiasjonsoppgaver. For eksempel: \"'Bil' er til 'vei' som 'b\u00e5t' er til hvilket ord?\". Svaret er \u00e5penbart \"vann\", men denne typen sp\u00f8rsm\u00e5l kan v\u00e6re vanskelige for en kunstig intelligens.<\/span><\/p>\n

Forskerne trodde i hvert fall at det kunne v\u00e6re vanskelig. Det viser seg at GPT-3 presterte bedre enn gjennomsnittet av college-s\u00f8kere gjorde p\u00e5 SAT-pr\u00f8vene.<\/span><\/p>\n

GPT-3 sliter med problemer som er enkle for mennesker<\/h2>\n

Det AI-modeller sliter med, er problemer som krever en visuell forst\u00e5else av det fysiske rommet. Hvis du gir GPT-3 en liste med verkt\u00f8y, for eksempel en hammer, en spiker og et bilde, er den ikke i stand til \u00e5 komme opp med den \u00e5penbare l\u00f8sningen for \u00e5 henge opp bildet p\u00e5 veggen.<\/span><\/p>\n

Den typen problemer er enkle for mennesker \u00e5 l\u00f8se fordi vi kan se, holde og f\u00f8le fysiske gjenstander i et rom vi opptar. Disse erfaringene gj\u00f8r det enkelt for hjernen v\u00e5r \u00e5 l\u00e6re og l\u00f8se problemer p\u00e5 en m\u00e5te som AI-modeller ikke kan. N\u00e5r det er sagt, er GPT-4 i ferd med \u00e5 bli bedre p\u00e5 denne typen resonnementer n\u00e5.<\/span><\/p>\n

Selv om forskerne kunne m\u00e5le ytelsen til GPT-3, har de ingen anelse om \"tankeprosessen\" den f\u00f8lger for \u00e5 komme frem til svarene. F\u00f8lger den en lignende tankeprosess som mennesker gj\u00f8r, eller gj\u00f8r den noe helt annet? Siden GPT-3 er en lukket modell, er det ikke mulig \u00e5 se under panseret for \u00e5 finne ut hva som skjer.\u00a0<\/span><\/p>\n

Det overraskende resultatet av denne forskningen er at GPT-3 ser ut til \u00e5 v\u00e6re i stand til \u00e5 l\u00f8se nye problemer uten direkte trening. Det er helt i tr\u00e5d med hvordan mennesker l\u00f8ser nye problemer. GPT-4 forventes \u00e5 prestere enda bedre p\u00e5 disse problemene, og hvem vet hvilke andre \"tenkeevner\" som kan dukke opp med mer testing.<\/span><\/p>\n

Selv om romlig resonnering er en utfordring for LLM-er, kan disse utfordringene l\u00f8ses ved hjelp av visuelle modeller som Googles RT-2<\/a> som nylig ble kunngjort. N\u00e5r AI-modeller kan begynne \u00e5 \"se\" og samhandle fysisk med omgivelsene sine, vil probleml\u00f8sningsevnen deres bli eksponentielt forbedret.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

En studie utf\u00f8rt av psykologer ved UCLA har vist at GPT-3 er omtrent like gode til \u00e5 l\u00f8se resonnementsproblemer som studenter p\u00e5 universitetsniv\u00e5. Vi vet at LLM-er som GPT-3 er gode til \u00e5 generere svar basert p\u00e5 dataene de er oppl\u00e6rt p\u00e5, men deres evne til \u00e5 resonnere er tvilsom. Analogisk resonnering er evnen mennesker har til \u00e5 ta det vi l\u00e6rer fra en erfaring som ikke er relatert til noe annet, og anvende det p\u00e5 et problem vi ikke har st\u00e5tt overfor f\u00f8r. Det er denne evnen du er avhengig av n\u00e5r du skal svare p\u00e5 et sp\u00f8rsm\u00e5l du aldri har sett f\u00f8r. Du kan resonnere deg gjennom det basert p\u00e5<\/p>","protected":false},"author":6,"featured_media":3467,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[266,207,105,93],"class_list":["post-3464","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-gpt","tag-llm","tag-machine-learning","tag-openai"],"yoast_head":"\nAI matches college undergrads solving reasoning problems | 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\/08\/ai-matches-college-undergrads-solving-reasoning-problems\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI matches college undergrads solving reasoning problems | DailyAI\" \/>\n<meta property=\"og:description\" content=\"A study by psychologists at UCLA has shown that GPT-3 is about as good as college undergraduate students at solving reasoning problems. 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