{"id":11227,"date":"2024-04-03T10:42:20","date_gmt":"2024-04-03T10:42:20","guid":{"rendered":"https:\/\/dailyai.com\/?p=11227"},"modified":"2024-04-03T10:42:20","modified_gmt":"2024-04-03T10:42:20","slug":"apples-realm-sees-on-screen-visuals-better-than-gpt-4","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2024\/04\/apples-realm-sees-on-screen-visuals-better-than-gpt-4\/","title":{"rendered":"Apples ReALM \"ser\" bilder p\u00e5 sk\u00e4rmen b\u00e4ttre \u00e4n GPT-4"},"content":{"rendered":"

Apples ingenj\u00f6rer har utvecklat ett AI-system som l\u00f6ser komplexa referenser till enheter p\u00e5 sk\u00e4rmen och anv\u00e4ndarkonversationer. Den l\u00e4tta modellen skulle kunna vara en idealisk l\u00f6sning f\u00f6r virtuella assistenter p\u00e5 enheter.<\/strong><\/p>\n

M\u00e4nniskor \u00e4r bra p\u00e5 att l\u00f6sa referenser i konversationer med varandra. N\u00e4r vi anv\u00e4nder termer som \"den understa\" eller \"han\" f\u00f6rst\u00e5r vi vad personen syftar p\u00e5 utifr\u00e5n konversationens sammanhang och saker vi kan se.<\/p>\n

Det \u00e4r mycket sv\u00e5rare f\u00f6r en AI-modell att g\u00f6ra detta. Multimodala LLM:er som GPT-4 \u00e4r bra p\u00e5 att svara p\u00e5 fr\u00e5gor om bilder, men de \u00e4r dyra att tr\u00e4na och kr\u00e4ver mycket datorkostnader f\u00f6r att bearbeta varje fr\u00e5ga om en bild.<\/p>\n

Apples ingenj\u00f6rer anv\u00e4nde ett annat tillv\u00e4gag\u00e5ngss\u00e4tt med sitt system, som kallas ReALM (Reference Resolution As Language Modeling). Tidningen<\/a> \u00e4r v\u00e4rt att l\u00e4sa f\u00f6r mer information om deras utvecklings- och testprocess.<\/p>\n

ReALM anv\u00e4nder en LLM f\u00f6r att bearbeta samtals-, sk\u00e4rm- och bakgrundsenheter (larm, bakgrundsmusik) som utg\u00f6r en anv\u00e4ndares interaktion med en virtuell AI-agent.<\/p>\n

H\u00e4r \u00e4r ett exempel p\u00e5 den typ av interaktion som en anv\u00e4ndare kan ha med en AI-agent.<\/p>\n

\"\"
Exempel p\u00e5 hur en anv\u00e4ndare interagerar med en virtuell assistent. K\u00e4lla: arXiv<\/figcaption><\/figure>\n

Agenten m\u00e5ste f\u00f6rst\u00e5 konversationsenheter som att n\u00e4r anv\u00e4ndaren s\u00e4ger \"den d\u00e4r\" syftar han eller hon p\u00e5 telefonnumret till apoteket.<\/p>\n

Den m\u00e5ste ocks\u00e5 f\u00f6rst\u00e5 det visuella sammanhanget n\u00e4r anv\u00e4ndaren s\u00e4ger \"den nedersta\", och det \u00e4r h\u00e4r ReALM:s metod skiljer sig fr\u00e5n modeller som GPT-4.<\/p>\n

ReALM f\u00f6rlitar sig p\u00e5 uppstr\u00f6ms kodare f\u00f6r att f\u00f6rst analysera elementen p\u00e5 sk\u00e4rmen och deras positioner. ReALM rekonstruerar sedan sk\u00e4rmen i rent textuella representationer fr\u00e5n v\u00e4nster till h\u00f6ger och uppifr\u00e5n och ned.<\/p>\n

Enkelt uttryckt anv\u00e4nds naturligt spr\u00e5k f\u00f6r att sammanfatta anv\u00e4ndarens sk\u00e4rm.<\/p>\n

N\u00e4r en anv\u00e4ndare nu st\u00e4ller en fr\u00e5ga om n\u00e5got p\u00e5 sk\u00e4rmen bearbetar spr\u00e5kmodellen textbeskrivningen av sk\u00e4rmen i st\u00e4llet f\u00f6r att beh\u00f6va anv\u00e4nda en synmodell f\u00f6r att bearbeta bilden p\u00e5 sk\u00e4rmen.<\/p>\n

Forskarna skapade syntetiska dataset med enheter i samtal, p\u00e5 sk\u00e4rmen och i bakgrunden och testade ReALM och andra modeller f\u00f6r att se hur effektiva de \u00e4r n\u00e4r det g\u00e4ller att l\u00f6sa referenser i samtalssystem.<\/p>\n

ReALM:s mindre version (80M parametrar) presterade j\u00e4mf\u00f6rbart med GPT-4 och dess st\u00f6rre version (3B parametrar) presterade betydligt b\u00e4ttre \u00e4n GPT-4.<\/p>\n

ReALM \u00e4r en liten modell j\u00e4mf\u00f6rt med GPT-4. Dess \u00f6verl\u00e4gsna referensuppl\u00f6sning g\u00f6r den till ett perfekt val f\u00f6r en virtuell assistent som kan finnas p\u00e5 enheten utan att kompromissa med prestandan.<\/p>\n

ReALM fungerar inte lika bra med mer komplexa bilder eller nyanserade anv\u00e4ndarf\u00f6rfr\u00e5gningar, men det skulle kunna fungera bra som en virtuell assistent i en bil eller p\u00e5 en enhet. T\u00e4nk om Siri kunde \"se\" din iPhone-sk\u00e4rm och svara p\u00e5 h\u00e4nvisningar till element p\u00e5 sk\u00e4rmen.<\/p>\n

Apple har varit lite l\u00e5ngsamma i starten, men den senaste tidens utveckling, som MM1-modell<\/a> och ReALM visar att det h\u00e4nder mycket bakom st\u00e4ngda d\u00f6rrar.<\/p>","protected":false},"excerpt":{"rendered":"

Apples ingenj\u00f6rer har utvecklat ett AI-system som l\u00f6ser komplexa referenser till enheter p\u00e5 sk\u00e4rmen och anv\u00e4ndarkonversationer. Den l\u00e4tta modellen skulle kunna vara en idealisk l\u00f6sning f\u00f6r virtuella assistenter p\u00e5 enheter. M\u00e4nniskor \u00e4r bra p\u00e5 att l\u00f6sa referenser i konversationer med varandra. N\u00e4r vi anv\u00e4nder termer som \"den som \u00e4r l\u00e4ngst ner\" eller \"han\" f\u00f6rst\u00e5r vi vad personen syftar p\u00e5 utifr\u00e5n konversationens sammanhang och saker som vi kan se. Det \u00e4r mycket sv\u00e5rare f\u00f6r en AI-modell att g\u00f6ra detta. Multimodala LLM:er som GPT-4 \u00e4r bra p\u00e5 att svara p\u00e5 fr\u00e5gor om bilder, men de \u00e4r dyra att tr\u00e4na och kr\u00e4ver en<\/p>","protected":false},"author":6,"featured_media":11232,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[126,166,118],"class_list":["post-11227","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-apple","tag-computer-vision","tag-llms"],"yoast_head":"\nApple\u2019s ReALM \u2018sees\u2019 on-screen visuals better than GPT-4 | 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\/sv\/2024\/04\/apples-realm-sees-on-screen-visuals-better-than-gpt-4\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apple\u2019s ReALM \u2018sees\u2019 on-screen visuals better than GPT-4 | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Apple engineers developed an AI system that resolves complex references to on-screen entities and user conversations. The lightweight model could be an ideal solution for on-device virtual assistants. Humans are good at resolving references in conversations with each other. When we use terms like \u201cthe bottom one\u201d or \u201chim\u201d we understand what the person is referring to based on the context of the conversation and things we can see. It\u2019s a lot more difficult for an AI model to do this. 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