Tag
15 articles
This explainer explores agentic AI—intelligent systems that perceive, reason, and act autonomously in enterprise environments. Learn how these platforms are transforming business operations through automation and cross-system orchestration.
Learn to compress instruction-tuned language models using FP8, GPTQ, and SmoothQuant quantization techniques with llmcompressor, and benchmark their performance.
Learn how to build and extend AI agents using the new Cline SDK, including creating basic agents, plugins, and subagents.
Learn how to implement basic LLM distillation techniques to train smaller, more efficient models that mimic larger pre-trained models.
Learn to build an autonomous coding system using LLMs, similar to Xiaomi's MiMo-V2.5-Pro, that can execute long-running tasks with minimal token consumption.
This explainer article explains what Large Language Models (LLMs) are and why it's important for AI development to focus on what regular people actually want, not just technical breakthroughs.
An open-source project called OpenMythos attempts to reconstruct Anthropic's Claude Mythos architecture from first principles, achieving 1.3B-level performance with only 770M parameters through advanced modeling techniques.
Learn to build an agentic AI platform for manufacturing execution systems, similar to Athena's FabOrchestrator, that automates reporting, support tickets, and system modeling.
Learn how to interact with large language models like ChatGPT using Python, and understand how these systems can be misused in stalking cases.
Learn how to build a five-layer security framework for autonomous LLM agents to protect against vulnerabilities in systems like OpenClaw.
Learn how to use Unsloth Studio, a no-code interface for fine-tuning Large Language Models locally with 70% less VRAM usage.
This explainer compares Model Context Protocol (MCP) and AI Agent Skills, two approaches for enabling LLMs to interact with external tools. It covers their architectural differences, operational mechanisms, and practical implications for AI system development.
