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From terabytes to insights: Real-world AI obervability architecture

GUEST: Consider maintaining and developing an e-commerce platform that processes millions of transactions every minute...

From Surveys to Narratives: Rethinking Cultural Value Adaptation in LLMs

arXiv:2505.16408v2 Announce Type: replace Abstract: Adapting cultural values in Large Language Models (LLMs) presents significant...

From Roots to Rewards: Dynamic Tree Reasoning with Reinforcement Learning

arXiv:2507.13142v3 Announce Type: replace-cross Abstract: Modern language models address complex questions through chain-of-thought (CoT) reasoning...

From RLHF to Direct Alignment: A Theoretical Unification of Preference Learning for Large Language Models

arXiv:2601.06108v1 Announce Type: cross Abstract: Aligning large language models (LLMs) with human preferences has become...

From prompt chaos to clarity: How to build a robust AI orchestration layer

Choosing orchestration frameworks can be overwhelming, but some experts believe there are best practices to...

From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem

Large language models (LLMs) very often generate “hallucinations”—confident yet incorrect outputs that appear plausible. Despite...

From Perception to Action: The Role of World Models in Embodied AI Systems

Introduction to Embodied AI Agents Embodied AI agents are systems that exist in physical or...

From Interpretability to Performance: Optimizing Retrieval Heads for Long-Context Language Models

arXiv:2601.11020v1 Announce Type: new Abstract: Advances in mechanistic interpretability have identified special attention heads, known...

From integration chaos to digital clarity: Nutrien Ag Solutions’ post-acquisition reset

Thank you for joining us on the “Enterprise AI hub.” In this episode of the...

From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship

arXiv:2506.23101v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown impressive capabilities across...

From Implicit to Explicit: Token-Efficient Logical Supervision for Mathematical Reasoning in LLMs

arXiv:2601.03682v1 Announce Type: new Abstract: Recent studies reveal that large language models (LLMs) exhibit limited...

From hallucinations to hardware: Lessons from a real-world computer vision project gone sideways

What we tried, what didn’t work and how a combination of approaches eventually helped us...

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