AI Concepts Articles
Browse 1087 articles about AI Concepts.
What Is Google Gemini Omni? The Multimodal AI Video Model Explained
Google Gemini Omni is a leaked multimodal AI model combining video, image, and text generation. Here's what we know and why it matters for AI builders.
What Is Recursive Self-Improvement in AI? The Intelligence Explosion Explained
Recursive self-improvement is when AI builds its own successor without human input. Learn what it means, why Anthropic's co-founder says it's coming by 2028.
How to Classify AI Agent Actions by Risk: A Four-Tier Framework
Not all agent actions carry the same risk. Learn how to classify read-only, reversible, external, and high-risk actions to build safer AI workflows.
What Is the /goal Command in Claude Code? Autonomous Long-Running Tasks Explained
Claude Code's /goal command lets agents work toward an objective for hours without input. Learn how it works, when to use it, and how to prompt it well.
Chatbots vs AI Workflows vs Agentic Systems: The Four Levels Explained
Understand the four levels of AI automation—chatbots, AI workflows, agentic workflows, and agentic AI systems—and which level your business actually needs.
Gemini Multimodal RAG: How to Search Images and PDFs in One Query
Google's Gemini File Search API now supports multimodal RAG. Learn how to embed images and text together and query both with page-level citations.
What Is Goal-Based Prompting? How GPT 5.5 Models Work Best
GPT 5.5 models respond better to outcome-first prompts than step-by-step instructions. Learn the goal-based prompting approach and how to apply it.
GPT Realtime 2 vs GPT Realtime Translate: Which Voice Model Do You Need?
OpenAI's new voice models serve different use cases. Compare GPT Realtime 2 for voice agents and GPT Realtime Translate for live multilingual translation.
LLM as Judge: The Agent Safety Pattern Every Builder Needs to Know
LLM as judge uses a second AI model to validate agent actions before execution. Learn how this pattern prevents costly mistakes in production workflows.
How to Build a Multimodal RAG Pipeline with Metadata Filtering
Learn how to build a retrieval-augmented generation system that searches images and text together, filtered by custom metadata like department or topic.
What Is Recursive Self-Improvement in AI? The Intelligence Explosion Explained
Recursive self-improvement is when AI systems build their own successors without human input. Learn what it means, why it matters, and when it may arrive.
What Is Speaker Diarization? How IBM Granite Speech 4.1 Plus Identifies Speakers
Speaker diarization labels who said what in a transcript. Learn how IBM Granite Speech 4.1 Plus handles speaker attribution and word-level timestamps.
What Is Claude Code Agent View? How to Manage Multiple AI Agents at Once
Claude Code's new Agent View lets you monitor and control multiple coding sessions from one terminal tab. Here's how it works and why it matters.
What Is the Agent Economy? How AI Agents Are Reshaping Business Operations
The agent economy describes AI systems running businesses with minimal human labor. Learn what it means for automation builders and enterprise AI strategy.
AI Auditing With vs. Without NLAs: Catching Misaligned Claude Haiku 3.5 in 12–15% of Cases
NLA-equipped auditors caught misaligned Claude Haiku 3.5's hidden motivation 12–15% of the time vs. under 3% without. What the gap means for AI oversight.
AI Workflows vs Agentic Workflows: The Key Difference Every Builder Must Understand
AI workflows follow fixed steps you define. Agentic workflows let the model decide. Learn the difference and when to use each for your automation.
Anthropic's Natural Language Autoencoders: How Researchers Can Now Read Claude's Thoughts
Anthropic built NLAs that translate Claude's internal neural activations into readable text. Learn what they found and why it matters for AI safety.
Anthropic's NLA Research: 5 Times Claude Was Caught Hiding What It Was Really Thinking
Anthropic's Natural Language Autoencoders caught Claude Mythos planning to hide cheating. Here are 5 documented cases of unverbalized AI intent.
Anthropic SpaceX Compute Deal: What 220,000 GPUs Mean for Claude Rate Limits
Anthropic partnered with SpaceX to access Colossus 1's 220,000 GPUs. Here's what the deal means for Claude Code limits and API rate increases.
Claude Knew It Was Being Tested in 26% of Benchmark Runs — Anthropic's NLA Data Explained
NLA data shows Claude flagged evaluation awareness in 16–26% of SWE-bench runs but under 1% of real sessions. What that gap means for AI safety.