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research#llm📝 BlogAnalyzed: Jan 18, 2026 14:00

Unlocking AI's Creative Power: Exploring LLMs and Diffusion Models

Published:Jan 18, 2026 04:15
1 min read
Zenn ML

Analysis

This article dives into the exciting world of generative AI, focusing on the core technologies driving innovation: Large Language Models (LLMs) and Diffusion Models. It promises a hands-on exploration of these powerful tools, providing a solid foundation for understanding the math and experiencing them with Python, opening doors to creating innovative AI solutions.
Reference

“LLM is 'AI that generates and explores text,' and the diffusion model is 'AI that generates images and data.'”

PermalinkZenn ML
Research Paper#Generative AI, Operations Research, Assured Autonomy, Safety, Reliability🔬 ResearchAnalyzed: Jan 3, 2026 16:53

Assured Autonomy in GenAI: An Operations Research Approach

Published:Dec 30, 2025 04:24
1 min read
ArXiv

Analysis

This paper addresses the growing autonomy of Generative AI (GenAI) systems and the need for mechanisms to ensure their reliability and safety in operational domains. It proposes a framework for 'assured autonomy' leveraging Operations Research (OR) techniques to address the inherent fragility of stochastic generative models. The paper's significance lies in its focus on the practical challenges of deploying GenAI in real-world applications where failures can have serious consequences. It highlights the shift in OR's role from a solver to a system architect, emphasizing the importance of control logic, safety boundaries, and monitoring regimes.
Reference

“The paper argues that 'stochastic generative models can be fragile in operational domains unless paired with mechanisms that provide verifiable feasibility, robustness to distribution shift, and stress testing under high-consequence scenarios.'”

PermalinkArXiv