· ai
How Google’s 'internal RL' could unlock long-horizon AI agents
Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or f...
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Tool Boundaries for Agents: When to Call Tools + How to Design Tool I/O (So Your System Stops Guessing)
Tool‑Calling — Make Your Agents Stop Guessing !Anindya Obihttps://media2.dev.to/dynamic/image/width=50,height=50,fit=cover,gravity=auto,format=auto/https%3A%2F...
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How RAG Works...
What is Retrieval‑Augmented Generation RAG? If you’ve been following the AI space, you’ve definitely heard the buzzword RAG Retrieval‑Augmented Generation. It...
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Part 4 — Retrieval Is the System
Why Most Practical GenAI Systems Are Retrieval‑Centric - Large language models LLMs are trained on static data, which leads to: - Stale knowledge - Missing dom...
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How to Use Synthetic Data to Evaluate LLM Prompts: A Step-by-Step Guide
Overview The deployment of Large Language Models LLMs in production has shifted the bottleneck of software engineering from code syntax to data quality. - In t...
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How RAG Is Transforming the Power of LLMs for Real-World Healthcare
Large Language Models LLMs changed the world — but Retrieval‑Augmented Generation RAG is what makes them truly useful in real‑world applications. Why RAG Is Bec...
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The 'truth serum' for AI: OpenAI’s new method for training models to confess their mistakes
OpenAI researchers have introduced a novel method that acts as a 'truth serum' for large language models LLMs, compelling them to self-report their own misbehav...