What Are LLMs And How Do They Work?

AI is actively changing various industries, and one of the most significant developments in this area has become LLM (Large Language Models). These algorithms are able to analyze, generate, and interpret text, which makes them useful for many tasks, including natural language processing, process automation, and service personalization. LLMs are especially actively used in fintech projects, where they help improve customer service, automate support, and analyze financial data. In this article, we will analyze how LLMs work and why they are becoming a key tool for digital transformation. If you are interested in advanced solutions in fintech, including a white-label solution for banks, in particular using AI, visit kindgeek.com/core_payment_platform.

What Is LLM?

LLM (Large Language Model) is a large language model trained on huge text data, capable of generating and analyzing texts, images, and computer code at a level that imitates human capabilities. Simply put, LLM is a program that does not select ready-made answers, like a search engine, but understands the meaning of the question and generates an answer on its own.

What Tasks Are LLMs Used For Today?

Large language models are used to automate and improve processes in various areas of life: industry, finance, business, art, and medicine. Let’s consider how they can help people and what they can do:

1. Generate texts and content. Programs based on large language models analyze style, meaning, and content and create content that would take a lot of time and effort for a person.
2. Make interaction with customers easier. Chatbots are created based on LLMs that answer customers’ questions about a product or service, calculating the user’s intentions. Such programs tell about the characteristics and benefits of a product in real time. With their help, you can get in contact with a potential buyer and even make sales. Using chatbots allows you to reduce customer service costs by 80%.
3. Perform the functions of virtual assistants. Virtual assistants based on LLMs process user requests and help solve various everyday tasks, such as organizing affairs. Their main strength is the ability to work with vague and unclear requests. Such assistants are especially relevant for payment platforms and neobanks.
4. Reduce long texts to summaries. LLM-based chatbots can extract the main points from the text and make understandable summaries. People for whom this is important (scientists, managers) do not need to reread 100 pages of text to understand the gist. They can simply place the script in the chatbot and receive high-quality material in the form of text or a table.
5. Create interactive training programs. The potential of LLM in education deserves special attention: AI generates educational materials and systems that help students better understand the subject in real-time.
6. Help with health. In the healthcare sector, advanced Large Language Model algorithms are used to create virtual diagnosticians who help patients find coherent answers to questions and monitor their health. Doctors can analyze data from people’s medical histories and make preliminary diagnoses.
7. Translate texts from many languages. When translating, LLM programs take into account the specifics of the text, terminology, style, intonation, and punctuation. The resulting texts sometimes surpass those worked on by a professional translator. And one model often knows more languages ​​than one person.
8. LLMs can automatically correct errors and offer options for improving the text. This is especially useful for authors, editors, and translators working with large volumes of text.
9. Conduct an advanced intelligent search. LLM effectively processes information from the Internet using semantic queries instead of just keywords.

The Most Popular LLMs for Business

There is no perfect LLM that would be better in everything. It would be better to consider all the strong models and combine them for specific tasks.

1. ChatGPT o1 is a universal language model from the American company OpenAI. It can reason, perform complex tasks, analyze, and use a consistent approach. For example, in the selection exam of the International Mathematical Olympiad, ChatGPT o1 solved 83% of the problems.
2. DeepSeek r1 is a language model from the Chinese company DeepSeek. This is an open-source LLM. It uses the Mixture-of-Experts (MoE) architecture, which divides the model into 256 independent “expert” modules. When processing a request, the system activates only the 8 most suitable experts out of 256, which speeds up the process and makes it more efficient.
3. Grok 3 is a language model from xAI. It uses the Mixture-of-Experts (MoE) architecture, and is equipped with the DeepSearch function for analyzing information from the Internet and the X social network. It can generate images, there is a voice mode.
4. Claude 3.5 Sonnet is a language model from the American company Anthropic. It is based on a transformer architecture: it processes a sequence of arbitrary length and takes into account the context and the relationship between words in different positions.
5. Gemini 2 flash is an LLM from Google. It supports multimodal output: images, video, and audio. This model works much faster than most analogs.
6. Llama 3.3 70B is a large open-source language model from Meta. It supports eight languages and understands context. There are local deployment options, which allow you to integrate the model – download, deploy to a private cloud, modify, and use for your own purposes.
7. Amazon Nova Pro is a multimodal model from the American company Amazon. It supports more than 200 languages ​​and understands text, images, and video.
8. Qwen 2.5 is an open-source language model from the Chinese corporation Alibaba. Like DeepSeek, it uses the MoE architecture — it analyzes input data and sends it to the most relevant expert for processing. It supports 29 languages.

Conclusion

LLM usage opens up new opportunities for business automation and process optimization. These models can analyze huge amounts of data, help in processing customer requests and increase the level of personalization of financial services. By integrating LLM with white-label solutions for banks, companies can offer innovative services, improving user experience and reducing operational costs. Artificial intelligence is becoming an important element of digital transformation, allowing companies to remain competitive in a dynamic market. If you want to learn more about modern fintech solutions and LLM implementation, contact Kindgeek, in particular, you can visit kindgeek.com/core_payment_platform.