{"id":6362,"date":"2024-02-02T12:15:10","date_gmt":"2024-02-02T11:15:10","guid":{"rendered":"https:\/\/edihadria.eu\/?p=6362"},"modified":"2024-02-02T12:15:10","modified_gmt":"2024-02-02T11:15:10","slug":"razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija","status":"publish","type":"post","link":"https:\/\/edihadria.eu\/en\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\/","title":{"rendered":"Development of generative artificial intelligence in 2024: Applications, challenges and education"},"content":{"rendered":"<p>2023 saw the incredibly rapid development of generative artificial intelligence (AI) technologies, based on large language models (LLM). The development of large language models, especially multimodal (text, image, sound, programming code) has accelerated the possibilities of application in various business segments such as marketing - managing sales channels and general communication with customers and customers, writing minutes and summaries of large business studies; in medicine for faster writing of medical reports and diagnoses, in education to help with knowledge verification; in law for faster analysis of legal files and writing legal documents, in scientific research for anticipation of new antibiotics and others. <strong>Studies show that generative AI has already brought changes to the labour market and that changes will continue at a rapid pace.<\/strong><\/p>\n<p>However, the economic benefits of applying this technology come with a number of <strong>Potential safety issues<\/strong> such as the generation of inaccurate content, referred to as hallucinations, bias and toxicity, the reliability of the generated text, copyright and privacy. These risks can significantly damage the company's reputation and affect society.<\/p>\n<p>EDIH Adria project has prepared a series<a href=\"https:\/\/edihadria.eu\/en\/edukacije\/\"> one-day workshops<\/a> where you can find the best way to increase your own productivity and grow your business through generative AI.<\/p>\n<p><a href=\"https:\/\/edihadria.eu\/en\/prompt-inzinjering\/\">Prompt engineering<\/a> so covers topics like: Introduction to generative AI and impact on business and labour market. An overview of the tasks that generative AI can solve and which challenges it is not up to with an overview of risks and limitations. It will answer the question of what is the difference of using pre-trained and fine-tuned models, and will give an overview of models for generating text, images, speech, music and video with examples of applications in marketing, medicine, business, etc. Further sitematizing will be prompt engineering approaches and recommendations with Zero-shot Prompting, Few-shot Prompting, Chain-of-Thought Prompting, Tree of Thoughts prompting, ReAct prompting, Active-Prompting, Multimodal CoT prompting, etc.<\/p>\n<p><a href=\"https:\/\/edihadria.eu\/en\/razvoj-aplikacija-s-llm-om\/\">Introduction to the development of LLM-based applications<\/a> (large language model) is an education based on the application of the Deep Grid Transformer architecture, i.e. its decoder part. In the introductory part, the principles of learning large language models for text generation, their fine-tuning and the principles of evaluation on benchmark data will be presented. Also, techniques for the application of large language models in applications such as fine tuning, the problem of castastrophic forgetting and learning within the context will be presented. Parameter Efficient Fine-Tuning-PEFT, adapter and Low-Rank Adaptation of Large Language Models-LoRA techniques will be presented. Particular attention will be paid to generating factually accurate texts with Retrieval Augmented Generation (RAG) techniques using vector bases, knowledge graphs or external knowledge. LLM agents and the most important software packages for building applications such as LangChain and LlamaIndex will be explained. After this course, users will distinguish between pre-trained and fine-tuned models, and be able to start developing applications that use generative AI responsibly and safely.<\/p>\n<p>If users want to try their hand at <a href=\"https:\/\/edihadria.eu\/en\/naucite-vlastiti-llm-bert\/\">building your own LLM on BERT architecture<\/a>, Advanced education covers basic architectures and deep learning principles with activation and loss functions. The differences between the recurrent network and the transformer network, as well as its encoder, decoder and encoder-decoder variants will be explained. At the core of the architecture are the mechanisms of attention Self attention and Multihead attention. The principles of autoregressive and masked learning will be explained, as well as the difference between static and dynamic (contextualized) vectors for the representation of languages - embeddings. The BERT model comes with variations: RoBERT, AlBERT, SpanBERT. For model learning to be successful, it is important to understand the principles of transfer learning by fine-tuning the model to the user's task from the domain of sequence prediction, classification or sentence generation.<\/p>","protected":false},"excerpt":{"rendered":"<p>In 2023, we witnessed the incredibly rapid development of generative artificial intelligence (AI) technologies, based on large language models (LLMs). The development of large language models, especially multimodal ones (text, image, sound, programming code) has accelerated the possibilities of application in various business segments such as marketing \u2013 management of sales channels and general communication with customers and users, [...]<\/p>","protected":false},"author":6,"featured_media":6256,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[50],"tags":[],"class_list":["post-6362","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-novosti"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Razvoj generativne umjetne inteligencije u 2024: Primjene, izazovi i edukacija - Digitalizacija Jadranske Hrvatske<\/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:\/\/edihadria.eu\/en\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Razvoj generativne umjetne inteligencije u 2024: Primjene, izazovi i edukacija - Digitalizacija Jadranske Hrvatske\" \/>\n<meta property=\"og:description\" content=\"U 2023. godini svjedo\u010dili smo nevjerojatno brzom razvoju tehnologija generativne umjetne inteligencije (UI), koje se temelji na velikim jezi\u010dnim modelima (LLM). Razvoj velikih jezi\u010dnih modela, posebice multimodalnih (tekst, slika, zvuk, programski kod) ubrzao je mogu\u0107nosti primjene u razli\u010ditim poslovnim segmentima poput marketinga &#8211; upravljanje prodajnim kanalima te op\u0107enitoj komunikaciji s kupcima i korisnicima, pisanju zapisnika [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/edihadria.eu\/en\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\/\" \/>\n<meta property=\"og:site_name\" content=\"Digitalizacija Jadranske Hrvatske\" \/>\n<meta property=\"article:published_time\" content=\"2024-02-02T11:15:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/edihadria.eu\/wp-content\/uploads\/2024\/01\/google-deepmind-LuzT78A1g7M-unsplash-scaled-e1705404090383.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1300\" \/>\n\t<meta property=\"og:image:height\" content=\"563\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Emira Brki\u0107 Karnin\u010di\u0107\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Emira Brki\u0107 Karnin\u010di\u0107\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/\"},\"author\":{\"name\":\"Emira Brki\u0107 Karnin\u010di\u0107\",\"@id\":\"https:\\\/\\\/edihadria.eu\\\/#\\\/schema\\\/person\\\/94df10824533eca3d05833421d2ba13e\"},\"headline\":\"Razvoj generativne umjetne inteligencije u 2024: Primjene, izazovi i edukacija\",\"datePublished\":\"2024-02-02T11:15:10+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/\"},\"wordCount\":631,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/edihadria.eu\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/edihadria.eu\\\/wp-content\\\/uploads\\\/2024\\\/01\\\/google-deepmind-LuzT78A1g7M-unsplash-scaled-e1705404090383.jpg\",\"articleSection\":[\"Novosti\"],\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/\",\"url\":\"https:\\\/\\\/edihadria.eu\\\/razvoj-generativne-umjetne-inteligencije-u-2024-primjene-izazovi-i-edukacija\\\/\",\"name\":\"Razvoj generativne umjetne inteligencije u 2024: Primjene, izazovi i edukacija - 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