Category: Emerging Technologies

Introduction: Multimodal AI processes and generates content across multiple modalities—text, images, audio, and video. This capability enables applications that were previously impossible: describing images, generating images from text, transcribing and understanding audio, and creating unified experiences that combine all these modalities. This guide covers the practical aspects of building multimodal applications: vision-language models for image… Continue reading

Introduction: Fine-tuning transforms general-purpose LLMs into specialized models that excel at your specific tasks. While prompting can get you far, fine-tuning unlocks capabilities that prompting alone cannot achieve: consistent output formats, domain-specific knowledge, reduced latency from shorter prompts, and behavior that would require extensive few-shot examples. This guide covers the practical aspects of LLM fine-tuning:… Continue reading

Introduction: AI agents represent the next evolution of LLM applications—systems that can reason, plan, and take actions to accomplish complex tasks autonomously. Unlike simple chatbots that respond to single queries, agents maintain state, use tools, and iterate toward goals. This guide covers the architectural patterns that make agents effective: the ReAct framework for reasoning and… Continue reading