{"id":1306,"date":"2025-10-22T13:12:43","date_gmt":"2025-10-22T13:12:43","guid":{"rendered":"https:\/\/www.rasyona.com\/?p=1306"},"modified":"2025-10-22T13:12:43","modified_gmt":"2025-10-22T13:12:43","slug":"llm-nedir-yapay-zeka-modelleri-nasil-calisir","status":"publish","type":"post","link":"https:\/\/www.rasyona.com\/en\/llm-nedir-yapay-zeka-modelleri-nasil-calisir\/","title":{"rendered":"What is LLM? How Do Artificial Intelligence Models Work?"},"content":{"rendered":"

Having entered our lives with the development of artificial intelligence technologies <\/span>Large Language Models (LLM)<\/b>, are no longer limited to just text generation; they are used in a very wide range of areas, from decision support systems to data analytics, coding assistance to customer service.<\/span><\/p>\n

LLMs are transforming both individual and corporate processes thanks to their human-like language understanding and generation capability. Businesses, in particular, when they integrate these models correctly <\/span>automation, efficiency, and information management<\/b> achieve striking gains in these areas.<\/span><\/p>\n

One of the companies accelerating this transformation in Turkey is <\/span>Rasyona<\/b>, by securely and sustainably integrating LLM's into corporate workflows, <\/span>ROOTIS platform<\/b> makes artificial intelligence processes traceable with the ROOTIS platform.<\/span><\/p>\n

What is a Large Language Model (LLM)?<\/b><\/h2>\n

LLM (Large Language Model)<\/b>, is an artificial intelligence model trained on a massive amount of text data. The goal is to learn the structure, relationships, and context of the language and <\/span>generate human-like text<\/b> and comprehend it.<\/span>
\n<\/span> These models can generate consistent answers even in complex language structures because they have billions of parameters. For instance, OpenAI's GPT series or Google's Gemini models are prominent examples of this category.<\/span>
\n<\/span> Bir LLM\u2019in ba\u015far\u0131s\u0131, <\/span>e\u011fitim verisinin \u00e7e\u015fitlili\u011fi<\/b> and <\/span>model parametrelerinin optimizasyonuna<\/b> ba\u011fl\u0131d\u0131r. Bu sayede hem teknik metinleri hem do\u011fal diyaloglar\u0131 anlayabilir hale gelirler.<\/span><\/p>\n

LLM Operating Principle<\/b><\/h2>\n

LLM\u2019ler temel olarak <\/span>derin \u00f6\u011frenme (deep learning)<\/b> and <\/span>do\u011fal dil i\u015fleme (NLP)<\/b> y\u00f6ntemlerini birle\u015ftirerek \u00e7al\u0131\u015f\u0131r.<\/span>
\n<\/span> Bir c\u00fcmledeki her kelimenin ba\u011flam i\u00e7indeki anlam\u0131n\u0131 tahmin etmek i\u00e7in <\/span>transformer mimarisi<\/b> kullan\u0131l\u0131r. Bu yap\u0131, modelin ayn\u0131 anda \u00e7ok say\u0131da kelime ili\u015fkisini analiz etmesini sa\u011flar.<\/span>
\n<\/span> Model, \u201c\u00f6nceki kelimelere bakarak bir sonraki kelimeyi tahmin etme\u201d prensibine dayal\u0131d\u0131r. Ancak milyonlarca \u00f6rnek \u00fczerinden e\u011fitildi\u011fi i\u00e7in bu tahmin s\u00fcreci, basit bir istatistikten \u00e7ok daha fazlas\u0131d\u0131r; ba\u011flam, ton ve anlam b\u00fct\u00fcnl\u00fc\u011f\u00fcn\u00fc kavrar.<\/span>
\n<\/span> At the corporate level, LLMs' <\/span>integration with systems like ROOTIS<\/b>, facilitates the management of artificial intelligence processes in terms of performance, security, and traceability.<\/span><\/p>\n

What are the Types of LLM?<\/b><\/h2>\n

LLMs are generally divided into three main categories:<\/span><\/p>\n

    \n
  1. General-Purpose Models:<\/b> These are models with a wide range of use, such as GPT, Claude, and Gemini.<\/span>\n

    <\/span><\/li>\n

  2. Domain-Specific Models:<\/b> These are models trained with specific datasets, such as those for health, law, finance, or technical document generation.<\/span>\n

    <\/span><\/li>\n

  3. Enterprise Customized Models:<\/b> These are models trained with in-house company data and customized to suit corporate terminology and processes.<\/span>
    \n<\/span> Rasyona's corporate consultancy approach enables businesses to create custom LLM models with their own data, ensuring that artificial intelligence <\/span>increases the job-specific accuracy rate.<\/b>.<\/span><\/p>\n

    <\/span><\/li>\n<\/ol>\n

    The Relationship Between NLP and LLM: What are the Similarities and Differences?<\/b><\/h2>\n

    NLP (Natural Language Processing)<\/b>, is the field of science that enables the structural analysis of language and its understanding by computers.<\/span>
    \n<\/span> LLM, on the other hand, is an advanced application of this concept. While NLP performs tasks like language analysis, sentiment analysis, and translation, LLM <\/span>does these in a more flexible and creative way by understanding the context.<\/b> performs them.<\/span>
    \n<\/span> In short, NLP is the language of \"rules,\" while LLM is the language of \"context.\"<\/span>
    \n<\/span> Today, many NLP applications are becoming LLM-based, <\/span>increasing their accuracy rate and adaptation capability.<\/b> have significantly increased.<\/span><\/p>\n

    Best LLM Models, Their Prominent Features, and Usage Areas<\/b><\/h2>\n

    Some prominent large language models today include:<\/span><\/p>\n\n\n\n\n\n\n\n
    Model<\/b><\/td>\nDeveloper<\/b><\/td>\nProminent Feature<\/b><\/td>\n<\/tr>\n
    GPT-4 \/ GPT-5<\/b><\/td>\nOpenAI<\/span><\/td>\nNatural language generation, coding, multi-language support<\/span><\/td>\n<\/tr>\n
    Claude 3<\/b><\/td>\nAnthropic<\/span><\/td>\nLong content analysis and ethical response generation<\/span><\/td>\n<\/tr>\n
    Gemini<\/b><\/td>\nGoogle DeepMind<\/span><\/td>\nMultimodal (visual + text) understanding capability<\/span><\/td>\n<\/tr>\n
    LLaMA 3<\/b><\/td>\nMeta<\/span><\/td>\nOpen-source structure, suitable for enterprise adaptation<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Usage areas include customer service, content generation, technical support, data analysis, and educational systems.<\/span><\/p>\n

    <\/span><\/p>\n

    Things to Consider When Choosing an LLM<\/b><\/h2>\n

    The following factors should be considered when choosing an LLM:<\/span><\/p>\n

      \n
    • Data Privacy:<\/b> How the model processes and stores data is critically important.<\/span>\n

      <\/span><\/li>\n

    • Performance & Scalability:<\/b> The model's response time and processing power must be able to handle the organization's load.<\/span>\n

      <\/span><\/li>\n

    • Cost & Licensing:<\/b> Open-source or commercial; how is the usage license determined?<\/span>\n

      <\/span><\/li>\n

    • Integration Compatibility:<\/b> It must be able to work harmoniously with existing systems (such as SAP or CRM infrastructures).<\/span>
      \n<\/span> Rasyona provides organizations in this process <\/span>technical evaluation and strategic model selection<\/b> consultancy on.<\/span><\/p>\n

      <\/span><\/li>\n<\/ul>\n

      Conclusion<\/b><\/h2>\n

      LLMs are not only a technological innovation but also <\/span>redefining the way we interact with information in the business world.<\/b> a revolution.<\/span>
      \n<\/span> In the corporate world, the way to effectively use artificial intelligence is <\/span>through the correct model selection<\/b>, <\/span>secure infrastructure integration<\/b> and <\/span>continuous monitoring<\/b>and governance.<\/span>
      \n<\/span> At this point, <\/span>Rasyona's expertise<\/b> and <\/span>ROOTIS's monitoring capability<\/b>, provides organizations not only with efficiency but also with sustainable digital maturity.<\/span><\/p>\n

      FAQ<\/b><\/h2>\n

      What data are LLMs trained with?<\/b>
      \n<\/b> They are generally trained with texts on the internet, academic articles, books, and open datasets. It is recommended that they be retrained with specialized datasets for corporate use.<\/span><\/p>\n

      Does an LLM continue to learn on its own?<\/b>
      \n<\/b> No. The model is fixed after the training is complete. However, it can be updated for corporate use through the \u201cfine-tuning\u201d method.<\/span><\/p>\n

      Are LLMs safe in terms of data privacy?<\/b>
      \n<\/b> Bulut tabanl\u0131 kullan\u0131mlarda dikkatli olunmal\u0131d\u0131r. Rasyona gibi dan\u0131\u015fmanl\u0131k firmalar\u0131, LLM entegrasyonlar\u0131nda <\/span>data security policies<\/b> develop<\/span><\/p>\n

      How does ROOTIS support LLM processes?<\/b>
      \n<\/b> ROOTIS, in systems where LLMs are integrated, <\/span>performance, log management, and infrastructure monitoring<\/b> undertakes these functions, ensuring uninterrupted operation.<\/span><\/p>\n

      Which LLM model is suitable for my business?<\/b>
      \n<\/b> This varies according to industry, data type, and workflow. Rasyona's expert team provides customized solutions for organizations <\/span>model evaluation and selection support<\/b> provides<\/span><\/p>\n

       <\/p>","protected":false},"excerpt":{"rendered":"

      Yapay zek\u00e2 teknolojilerinin geli\u015fimiyle birlikte hayat\u0131m\u0131za giren B\u00fcy\u00fck Dil Modelleri (LLM \u2013 Large Language Model), art\u0131k sadece metin \u00fcretimiyle s\u0131n\u0131rl\u0131<\/p>","protected":false},"author":1,"featured_media":1307,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1306","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bilgi-kutusu"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/posts\/1306","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/comments?post=1306"}],"version-history":[{"count":1,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/posts\/1306\/revisions"}],"predecessor-version":[{"id":1308,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/posts\/1306\/revisions\/1308"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/media\/1307"}],"wp:attachment":[{"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/media?parent=1306"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/categories?post=1306"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rasyona.com\/en\/wp-json\/wp\/v2\/tags?post=1306"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}