Скачать или смотреть Successes and challenges of large model languages | AIJ 2025 (12+) | Arabic

Speaker — Ivan Oseledets, AIRI Institute

During the session, the main points of discussion revolved around the following key aspects:

1. Successes and Problems of Large Language Models (LLMs):
Discussed both the achievements and challenges faced by LLMs, highlighting their ability to compress vast amounts of data effectively while noting issues like limited memory and lack of deep reasoning capabilities.

2. Impact on Industries:
Explored how LLMs are being applied across different sectors, particularly in medicine where they have shown promise in passing medical exams but fall short when it comes to real-world clinical decision-making.

3. Scaling and Data Compression:
Emphasized the systematic approach to scaling LLMs, involving larger datasets, improved hardware, and advanced optimization techniques.

4. New Architectures and Algorithms:
Introduced innovative approaches such as ARM-T (Associative Recursive Memory Transformer) and GigaEvo, an evolutionary algorithm designed to enhance model performance through iterative refinement.

5. Future Prospects and Challenges:
Highlighted the potential for LLMs to evolve into tools for building multi-agent systems capable of solving complex tasks reliably. Also mentioned the need for overcoming current limitations, such as enabling learning during inference and accessing external knowledge sources.

6. Synthetic Data Generation:
Discussed the role of LLMs in generating synthetic data to address data scarcity in specialized domains like medicine and finance.

Overall, the discussion centered on balancing the significant progress made in LLMs with the ongoing efforts needed to overcome existing barriers toward achieving more robust and versatile AI systems.

#aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai