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A Systematic Review of LLM Advancements from GPT-3 to Reasoning Agents
Full text (PDF)
UDC: 004.8
Publication Language: Ukrainian
Stuc. intelekt. 2025; 30(3):32-43
Abstract: The article offers a comprehensive analysis of the stages of evolution of large language models between 2020 and 2025. We analyzed the strategic focus, approaches, architecture, and key stages of development of the AI industry, focusing on the contributions of ten leading companies: OpenAI, Anthropic, Google, Meta, Mistral AI, DeepSeek AI, AI21 Labs, Qwen, Cohere, and xAI. We analyzed the main paradigms of LLM development: scaling, proposed with the release of the GPT-3 model; aligning model responses with user prompts, characterised by the emergence of techniques such as RLHF; spreading models with open weights; reducing model costs through optimisation; and the current stage, focused on architectural efficiency, multimodality, and agent behaviour. Key trends that have shaped the current landscape of generative AI are identified, including competition between proprietary and open models, the rise of specialised agents over universal models, and the growing importance of economic efficiency. The paper summarises the current state of the industry on a proposed hierarchical model of technology development levels and outlines prospects for further development of the industry, emphasising the role of agent ecosystems and high-quality data.
Keywords: large language models, generative AI, artificial intelligence, AI evolution, model architecture, agentic reasoning, review
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