{"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\/it\/2023\/08\/ai-matches-college-undergrads-solving-reasoning-problems\/","title":{"rendered":"L'intelligenza artificiale abbina studenti universitari che risolvono problemi di ragionamento"},"content":{"rendered":"

Uno studio condotto da psicologi dell'UCLA ha dimostrato che il GPT-3 \u00e8 bravo quanto gli studenti universitari a risolvere problemi di ragionamento.<\/strong><\/p>\n

Sappiamo che i LLM come il GPT-3 sono bravi a generare risposte basate sui dati su cui sono stati addestrati, ma la loro capacit\u00e0 di ragionamento \u00e8 discutibile. Il ragionamento analogico \u00e8 la capacit\u00e0 degli esseri umani di prendere ci\u00f2 che impariamo da un'esperienza non correlata e applicarlo a un problema che non abbiamo mai affrontato prima.<\/span><\/p>\n

\u00c8 su questa capacit\u00e0 che si fa affidamento quando si deve rispondere a una domanda mai vista prima. Si pu\u00f2 ragionare sulla base di problemi precedenti che si sono risolti. Dalla ricerca, sembra che il GPT-3 abbia sviluppato anche questa capacit\u00e0.<\/span><\/p>\n

Il <\/span>Ricercatori dell'UCLA<\/span><\/a> mettere il GPT-3 al lavoro su un insieme di problemi simili a <\/span>Matrici progressive di Raven<\/span><\/a> che consiste nel prevedere l'immagine successiva di una serie di immagini. Eccone uno facile da provare.<\/span><\/p>\n

\"Esempio
Esempio di matrice progressiva Raven - Fonte: Wikipedia<\/a><\/figcaption><\/figure>\n

Il GPT-3 \u00e8 stato in grado di reggere il confronto con i 40 laureandi dell'UCLA a cui \u00e8 stato chiesto di fare lo stesso test. L'intelligenza artificiale ha azzeccato le risposte nell'80% delle volte, mentre i 40 studenti hanno ottenuto una media di circa 60%. I migliori studenti hanno ottenuto circa lo stesso punteggio del GPT-3.<\/span><\/p>\n

Il professore di psicologia dell'UCLA Hongjing Lu, autore senior dello studio, ha dichiarato: \"Sorprendentemente, non solo il GPT-3 si \u00e8 comportato bene come gli esseri umani, ma ha anche commesso errori simili\".<\/span><\/p>\n

I ricercatori hanno anche chiesto al GPT-3 di risolvere alcuni problemi di associazione di parole. Ad esempio, \"Auto\" sta a \"Strada\" come \"Barca\" sta a quale parola?\". La risposta \u00e8 ovviamente \"acqua\", ma questo tipo di domande pu\u00f2 essere difficile per un'intelligenza artificiale.<\/span><\/p>\n

Beh, almeno i ricercatori pensavano che potesse essere difficile. \u00c8 emerso che il GPT-3 ha ottenuto risultati migliori rispetto alla media dei candidati all'universit\u00e0 nei loro SAT.<\/span><\/p>\n

Il GPT-3 \u00e8 alle prese con problemi facili per gli esseri umani.<\/h2>\n

I problemi con cui i modelli di intelligenza artificiale hanno difficolt\u00e0 sono quelli che richiedono una comprensione visiva dello spazio fisico. Se si presenta a GPT-3 un elenco di strumenti come un martello, un chiodo e un quadro, non \u00e8 in grado di trovare la soluzione pi\u00f9 ovvia per appendere il quadro alla parete.<\/span><\/p>\n

Per gli esseri umani \u00e8 facile risolvere questo tipo di problemi perch\u00e9 possiamo vedere, tenere e sentire oggetti fisici in uno spazio che occupiamo. Queste esperienze rendono facile per il nostro cervello imparare e risolvere i problemi in un modo che i modelli di intelligenza artificiale non possono fare. Detto questo, il GPT-4 sta migliorando in questo tipo di ragionamento.<\/span><\/p>\n

Sebbene i ricercatori abbiano potuto misurare le prestazioni del GPT-3, non hanno idea del processo di \"pensiero\" che segue per ottenere le risposte. Segue un processo di pensiero simile a quello umano o fa qualcosa di completamente diverso? Essendo il GPT-3 un modello chiuso, non \u00e8 possibile guardare sotto il cofano per vedere cosa succede.\u00a0<\/span><\/p>\n

Il risultato sorprendente di questa ricerca \u00e8 che il GPT-3 sembra essere in grado di risolvere problemi nuovi senza alcun addestramento diretto. Questo \u00e8 strettamente in linea con il modo in cui gli esseri umani risolvono i nuovi problemi. Si prevede che il GPT-4 sia ancora pi\u00f9 bravo in questi problemi e chiss\u00e0 quali altre capacit\u00e0 di \"pensare\" potrebbero emergere con ulteriori test.<\/span><\/p>\n

Sebbene il ragionamento spaziale sia una sfida per i LLM, queste sfide potrebbero essere risolte da modelli visivi quali RT-2 di Google<\/a> che \u00e8 stato recentemente annunciato. Quando i modelli di intelligenza artificiale potranno iniziare a \"vedere\" e interagire fisicamente con l'ambiente circostante, le loro capacit\u00e0 di risoluzione dei problemi miglioreranno in modo esponenziale.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Uno studio condotto da psicologi dell'UCLA ha dimostrato che il GPT-3 \u00e8 bravo quanto gli studenti universitari a risolvere problemi di ragionamento. Sappiamo che i LLM come il GPT-3 sono bravi a generare risposte basate sui dati su cui sono stati addestrati, ma la loro capacit\u00e0 di ragionamento \u00e8 discutibile. Il ragionamento analogico \u00e8 la capacit\u00e0 degli esseri umani di prendere ci\u00f2 che impariamo da un'esperienza non correlata e applicarlo a un problema che non abbiamo mai affrontato prima. \u00c8 su questa capacit\u00e0 che ci si basa quando si deve rispondere a una domanda mai vista prima. Si pu\u00f2 ragionare sulla base<\/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\/it\/2023\/08\/ai-matches-college-undergrads-solving-reasoning-problems\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\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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