Research
Latest research on artificial intelligence and large language models.
AI Safety & Alignment
RAG Hallucination in Production
Robotics
Robot Learning from Human Demonstration: Current State and Benchmarks
A survey of robot learning from human demonstration covering imitation learning algorithms, the distribution shift problem, and leading benchmarks like CALVIN, RLBench, and OpenVLA.
Computer Vision
Vision Transformers in 2026: How ViT, DINOv2, and SAM Are Redefining Computer Vision Pipelines
Vision Transformers, DINOv2, and SAM are reshaping computer vision pipelines in 2026. Learn how these models work together and when to use each.
AI Safety & Alignment
Constitutional AI and the Quest for Safe, Aligned Large Language Models
Constitutional AI replaces costly human feedback with AI-generated guidance based on explicit principles. Learn how CAI works, its 2026 evolution, and what it means for enterprise AI deployments.
AI Research
Sparse Mixture of Experts: How MoE Cuts LLM Inference Costs by 80% Without Sacrificing Quality
Comprehensive guide to sparse mixture of experts and how MoE architecture cuts LLM inference costs by 80% for enterprise deployments.
NLP & LLMs
Beyond Transformers: The Rise of State Space Models in Production NLP
Practical guide to state space models in production NLP: how Mamba, S4, and hybrid architectures compare to transformers.
AI Safety & Alignment
AI Safety Benchmarks in 2026: From RLHF to Constitutional AI and Beyond
The problem is stark: MMLU-Pro — once the gold standard for measuring general knowledge — now sits near saturation at the frontier. Top models routinely score above 88%, making it near-impossible...
Reinforcement Learning
Reinforcement Learning in Industrial Robotics: From Simulation to Real-World Deployment
Comprehensive guide to RL in industrial robotics, from simulation to real-world deployment.