Huawei Researchers Propose Self-Improving AI Agents That Learn From Experience
New framework treats skills as living assets that evolve across tasks, potentially transforming how language model agents solve problems.
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How Large Language Models Work: A Technical Explainer
Understand tokens, attention, and next-token prediction without the PhD-level math.
GPT-5 vs Claude 4.5 vs Gemini Ultra: Choose the Right LLM
A technical comparison for production teams selecting a frontier model in 2026
What Are AI Agents? A Practical Guide for Builders in 2026
How autonomous agents differ from chatbots, what frameworks actually work, and where they reliably fail.
Fine-tuning vs RAG vs Prompt Engineering: A Decision Framework
When to customize an LLM: cost, latency, and accuracy tradeoffs explained for engineering leaders.
What is Retrieval-Augmented Generation (RAG)? A 2026 Guide
How RAG fixes LLM hallucinations by letting models fetch real data before generating answers.
Turning Chores Into AI Training Data: The Hidden Cost
As companies recruit everyday people to record household tasks for robot training, participants face unforeseen consequences of monetizing their daily routines.
Deep Dives
Critical Flaw in Popular Python Framework Exposes AI Agents Globally
A severe vulnerability in Starlette threatens millions of AI deployments and the credentials they manage for external services.
Manufacturing's Digital Divide: When to Deploy Simulation vs. Digital Twins
As factories embrace virtual tools, understanding the strategic differences between simulations and digital twins becomes critical for smart technology investment.
