# AI Spectrum

> AI Spectrum is a resource hub for AI news, tools, guides, and analysis.

## Pages
- [About page](https://aispectrum.io/about)
- [Comprehensive exploration of AI agents: autonomous software entities that perform complex human-like tasks. Covers key features, diverse applications, current challenges, and future impact on industries and daily life.](https://aispectrum.io/agents)
- [Guide to deciding between autonomous AI agents and structured AI workflows for app development, focusing on control mechanisms and task adaptability. Features Microsoft AutoGen and LangChain as example tools.](https://aispectrum.io/agents-vs-structured-workflows)
- [A comprehensive guide to modern AI: from transformer architecture and LLMs to training infrastructure, model scaling, and real-world deployment costs. Learn how today's AI systems process thousands of years of human knowledge and a new super intelligence artificial specie rises between humanity.](https://aispectrum.io/ai)
- [Research shows AI tools can accelerate development by 6.5-28%, but impacts vary dramatically by team composition and project type. Explore the data on when AI helps—and when it doesn't.](https://aispectrum.io/ai-impact-software-development-speed)
- [A comprehensive guide of integration strategies including: Fine Tuning, LLM + RAG, AI Agents, and Structured Workflows](https://aispectrum.io/ai-integration-guide)
- [A guide to choosing the right AI methodology by comparing Fine Tuning, Agentic approaches, and Retrieval-Augmented Generation (RAG).](https://aispectrum.io/ai-methodology-selection)
- [Analysis of China's rapid AI advancements in language models, hardware adaptation, and policy responses to US tech sanctions during Q1 2025.](https://aispectrum.io/china-ai-surge)
- [Exploring methods to maintain your data privacy when using AI tools, focusing on local LLMs and data obfuscation techniques](https://aispectrum.io/data-privacy)
- [How a Chinese lab redefined AI economics through pure reinforcement learning - and what it means for the future of AI development](https://aispectrum.io/deepseek-r1)
- [Comprehensive guide to AI tools and resources: development frameworks, enterprise solutions, and industry insights for technical professionals and decision-makers](https://aispectrum.io/dev-tools)
- [Exploring techniques in generative artificial intelligence](https://aispectrum.io/generative-ai)
- [Key terms and concepts in artificial intelligence](https://aispectrum.io/glossary)
- [Analyzing the shift from Human-Computer Interaction to Machine-Computer Interaction with Anthropic Claude's groundbreaking computer use capability and comparing available tools in the market.](https://aispectrum.io/hci-vs-mci)
- [Overview of key standards influencing AI interaction with web content and development practices](https://aispectrum.io/industry-standards)
- [Leading AI research organizations](https://aispectrum.io/labs)
- [Curated collection of AI resources and tools](https://aispectrum.io/links)
- [End-to-end workflow for fine-tuning LLaMA 3 models (8B parameters in model - model size ~5GB) with Unsloth, from dataset preparation to GGUF export and Ollama deployment](https://aispectrum.io/llama-training)
- [Comparing different approaches to implement LLM-based classifiers: analyzing trade-offs between quantized fine-tuned models, RAG systems with frontier/quantized models, and direct prompting.](https://aispectrum.io/llm-implementation-comparison)
- [Analysis of how Large Language Models like ChatGPT are being optimized for cost efficiency, sometimes at the expense of intelligence, through techniques like pruning and quantization.](https://aispectrum.io/llm-optimization-costs)
- [Technical overview of modern LLM system architectures, focusing on inference, fine-tuning, and system integration.](https://aispectrum.io/llm-systems-architecture-2025)
- [Study of LLMs managing a virtual vending machine business. While Claude 3.5 Sonnet turned $500 into $2,217 on average, all models eventually failed through mismanaged inventory, confused scheduling, or complete behavioral breakdowns - highlighting key limitations in AI's long-term reliability.](https://aispectrum.io/llm-vending-machine-benchmark)
- [An Overview on LLMs](https://aispectrum.io/llms)
- [Shallow dive into how multiple AI agents can create realistic social simulations, exploring concurrent architectures and emergent behavior in artificial communities](https://aispectrum.io/many-agent-simulations)
- [Learn about the Model Context Protocol (MCP), how it standardizes AI tool use compared to older methods, and how to integrate it.](https://aispectrum.io/mcp-client-servers)
- [How to Access AI Models from Leading Labs](https://aispectrum.io/models-access)
- [Comprehensive overview of OpenAI's o1 model, exploring its enhanced reasoning capabilities, potential applications, and impact on AI development](https://aispectrum.io/openai-o1)
- [Analysis of how advancing AI technology, particularly AGI and ASI, could lead to a post-scarcity economy where traditional resource limitations and human labor become obsolete.](https://aispectrum.io/post-scarcity)
- [Retrieval-Augmented Generation: Enhancing LLMs with External Knowledge](https://aispectrum.io/rag)
- [Understanding LLM System Prompts and AI Development Strategies](https://aispectrum.io/system-prompts)
- [Comprehensive comparison of frontier AI models (Q4 2025): MMLU-Pro, MMLU, and GPQA benchmark scores for leading models including OpenAI, Claude, Gemini, Grok, and open-source LLMs. Updated performance rankings and capabilities assessment.](https://aispectrum.io/top-models)
- [A comprehensive overview of AI applications across industries, including game development, software engineering, and various business sectors. Explores AI capabilities, limitations, and human-AI interaction models.](https://aispectrum.io/use-cases)
- [Exploring Whisper's capabilities and integration with LangChain](https://aispectrum.io/whisper-openai)