The State Of LLMs 2025: Progress, Problems, and Predictions
Read OriginalThis article provides a comprehensive year-end review of the state of large language models (LLMs) in 2025. It analyzes major trends like reasoning models (e.g., DeepSeek R1), architectural shifts, inference scaling, and the focus on cost efficiency (GRPO). It also covers LLM applications in coding and research, discusses persistent challenges, and offers predictions for 2026, including a curated list of recent research papers.
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