The Truth About AI: Job Market Shifts, RAG, and Advanced Prompting скачать в хорошем качестве

The Truth About AI: Job Market Shifts, RAG, and Advanced Prompting

In this session, we dive past the hype to understand what Artificial Intelligence and Large Language Models (LLMs) actually are—and how they are reshaping the workforce. We explore the fundamental misconception that AI is a "repository of facts" and explain why it is actually a "text prediction machine" relying on transformers and tokens. We also discuss the urgent shift in the job market. With major tech companies like Amazon redirecting budget from salaries to AI infrastructure, junior knowledge work (the "bricklayers") is decreasing in demand, while the need for "architects"—those with design skills, empathy, and judgment—is rising. Finally, we cover essential technical concepts like Retrieval Augmented Generation (RAG) to prevent hallucinations, the difference between fine-tuning and deep research, and practical principles for better prompting. In this video, you will learn: The Core Misconception: Why GPTs are next-token prediction engines, not knowledge bases. Career Survival Guide: Why "architect" roles are safe while "junior analyst" roles are at risk. Technical Deep Dive: Understanding tokens, context windows, and memory. *RAG Explained: How Retrieval Augmented Generation grounds AI to stop it from making things up. Fine-Tuning vs. Deep Research: When to train a model on specific data (like legal statutes) versus letting it research the web. Prompt Engineering: Moving from "Chain of Thought" to "Chain of Draft" and how to get the best outputs. Timestamps: 0:00 - Introduction: AI is not a fact repository 0:45 - The Job Market: Why companies are freezing hiring 2:30 - The urgency to build AI skills now 4:15 - Architects vs. Bricklayers: The shift in valued skills 6:00 - How LLMs work: Tokens and Context Windows 8:30 - RAG (Retrieval Augmented Generation) & Hallucinations 11:00 - Fine-tuning models for specific industries (Legal, Coaching) 14:00 - Prompt Engineering Principles: One-shot, Chain of Thought, & Chain of Draft 17:30 - Practical Tip: Asking AI how to improve your prompts 19:00 - Reducing "Administrative Drag" with AI 21:00 - Live Demo: Gemini and Deep Research #ArtificialIntelligence #LLM #FutureOfWork #PromptEngineering #RAG #GenerativeAI #TechCareers #MachineLearning