{"id":10786,"date":"2024-03-18T09:35:31","date_gmt":"2024-03-18T09:35:31","guid":{"rendered":"https:\/\/dailyai.com\/?p=10786"},"modified":"2024-03-28T09:35:17","modified_gmt":"2024-03-28T09:35:17","slug":"apple-reveals-mm1-its-first-family-of-multimodal-llms","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2024\/03\/apple-reveals-mm1-its-first-family-of-multimodal-llms\/","title":{"rendered":"Apple afsl\u00f8rer MM1, sin f\u00f8rste familie af multimodale LLM'er"},"content":{"rendered":"

Apple har endnu ikke officielt frigivet en AI-model, men en ny forskningsartikel giver et indblik i virksomhedens fremskridt med at udvikle modeller med avancerede multimodale funktioner.<\/strong><\/p>\n

Avisen<\/a>med titlen \"MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training\", introducerer Apples familie af MLLM'er kaldet MM1.<\/p>\n

MM1 viser imponerende evner inden for billedtekstning, visuel sp\u00f8rgsm\u00e5lssvar (VQA) og udledning af naturligt sprog. Forskerne forklarer, at omhyggelige valg af billedtekstpar gjorde det muligt for dem at opn\u00e5 overlegne resultater, is\u00e6r i l\u00e6ringsscenarier med f\u00e5 billeder.<\/p>\n

Det, der adskiller MM1 fra andre MLLM'er, er dens overlegne evne til at f\u00f8lge instruktioner p\u00e5 tv\u00e6rs af flere billeder og til at r\u00e6sonnere over de komplekse scener, den bliver pr\u00e6senteret for.<\/p>\n

MM1-modellerne indeholder op til 30B parametre, hvilket er tre gange s\u00e5 meget som GPT-4V, den komponent, der giver OpenAI's GPT-4 sine synsfunktioner.<\/p>\n

Her er nogle eksempler p\u00e5 MM1's VQA-evner.<\/p>\n

\"\"
Test af MM1's evne til at r\u00e6sonnere p\u00e5 tv\u00e6rs af billeder og tekster. Kilde: arXiv<\/figcaption><\/figure>\n

MM1 gennemgik en storstilet multimodal pretr\u00e6ning p\u00e5 \"et datas\u00e6t med 500M sammenflettede billed-tekstdokumenter, der indeholder 1B billeder og 500B teksttokens.\"<\/p>\n

Omfanget og mangfoldigheden af fortr\u00e6ningen g\u00f8r det muligt for MM1 at udf\u00f8re imponerende forudsigelser i kontekst og f\u00f8lge brugerdefineret formatering med et lille antal eksempler p\u00e5 f\u00e5 billeder. Her er eksempler p\u00e5, hvordan MM1 l\u00e6rer det \u00f8nskede output og format ud fra kun 3 eksempler.<\/p>\n

\"\"
MM1 kan t\u00e6lle objekter, udf\u00f8re OCR p\u00e5 specifikke omr\u00e5der af et billede, anvende sund fornuft p\u00e5 objekter og udf\u00f8re grundl\u00e6ggende matematiske funktioner. Kilde: arXiv<\/figcaption><\/figure>\n

At lave AI-modeller, der kan \"se\" og r\u00e6sonnere, kr\u00e6ver en vision-sprog-forbindelse, der overs\u00e6tter billeder og sprog til en samlet repr\u00e6sentation, som modellen kan bruge til videre behandling.<\/p>\n

Forskerne fandt ud af, at designet af syns-sprogforbindelsen var en mindre faktor i forhold til MM1's pr\u00e6station. Interessant nok var det billedopl\u00f8sningen og antallet af billedtokens, der havde den st\u00f8rste indvirkning.<\/p>\n

Det er interessant at se, hvor \u00e5ben Apple har v\u00e6ret med hensyn til at dele sin forskning med det bredere AI-samfund. Forskerne siger, at \"i denne artikel dokumenterer vi MLLM-byggeprocessen og fors\u00f8ger at formulere designlektioner, som vi h\u00e5ber kan v\u00e6re til nytte for samfundet.\"<\/p>\n

De offentliggjorte resultater vil sandsynligvis p\u00e5virke den retning, som andre MMLM-udviklere tager med hensyn til arkitektur og valg af data til pr\u00e6tr\u00e6ning.<\/p>\n

Pr\u00e6cis hvordan MM1-modellerne vil blive implementeret i Apples produkter, er endnu uvist. De offentliggjorte eksempler p\u00e5 MM1's evner antyder, at Siri bliver meget smartere, n\u00e5r hun til sidst l\u00e6rer at se.<\/p>","protected":false},"excerpt":{"rendered":"

Apple har endnu ikke officielt frigivet en AI-model, men en ny forskningsartikel giver et indblik i virksomhedens fremskridt med at udvikle modeller med avancerede multimodale funktioner. Artiklen har titlen \"MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training\", introducerer Apples familie af MLLM'er kaldet MM1. MM1 viser imponerende evner inden for billedtekstning, besvarelse af visuelle sp\u00f8rgsm\u00e5l (VQA) og udledning af naturligt sprog. Forskerne forklarer, at omhyggelige valg af billedtekstpar gjorde det muligt for dem at opn\u00e5 overlegne resultater, is\u00e6r i l\u00e6ringsscenarier med f\u00e5 billeder. Det, der adskiller MM1 fra andre MLLM'er, er dens overlegne evne til at f\u00f8lge instruktioner p\u00e5 tv\u00e6rs af flere billeder og<\/p>","protected":false},"author":6,"featured_media":10790,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[126,166],"class_list":["post-10786","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-apple","tag-computer-vision"],"yoast_head":"\nApple reveals MM1, its first family of multimodal LLMs | 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\/da\/2024\/03\/apple-reveals-mm1-its-first-family-of-multimodal-llms\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apple reveals MM1, its first family of multimodal LLMs | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Apple is yet to officially release an AI model, but a new research paper gives an insight into the company\u2019s progress in developing models with state-of-the-art multimodal capabilities. The paper, titled \u201cMM1: Methods, Analysis & Insights from Multimodal LLM Pre-training\u201d, introduces Apple\u2019s family of MLLMs called MM1. MM1 displays impressive abilities in image captioning, visual question answering (VQA), and natural language inference. The researchers explain that careful choices of image-caption pairs enabled them to achieve superior results, especially in few-shot learning scenarios. 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