AI 101 in plain English

Learn AI in plain English: Rule Based AI, Machine Learning, Generative AI, and ChatGPT Hi, I’m Aish. I lead Developer Relations at Fireworks AI, a high-growth Bay Area startup powering large-scale AI inference. My career spans Big Tech and startups, including roles as a Senior AI Advocate at Microsoft, Data Scientist at Google Cloud, and AI & ML Innovation Leader at IBM. In this video, I will walk you from the basics of AI and machine learning to advanced prompt engineering techniques for ChatGPT. Whether you’re a beginner or looking to refine your skills, this episode covers everything you need to know to use ChatGPT effectively, avoid common pitfalls, and get the most out of your AI assistant. Timestamps / Video Chapters 00:00 – Introduction & What is ChatGPT? 00:22 – From Calculators to Rule-Based Systems 00:39 – The Limits of Rule-Based Systems 00:59 – Supervised Machine Learning Explained 01:23 – Unsupervised Machine Learning & Its Role 01:43 – The Quest for General Intelligence (AGI) 02:01 – How Large Language Models Learn 02:42 – How LLMs Process Language 03:23 – Multimodal Models: Beyond Text 03:54 – Generative vs. Traditional LLMs 04:26 – Generative AI in Action 04:47 – ChatGPT’s Unique Capabilities 05:10 – How ChatGPT Breaks Down Instructions 05:33 – Action Assessment & Gap Prediction 05:51 – Traditional Chatbots vs. ChatGPT 06:11 – ChatGPT as Your AI Assistant 06:33 – Understanding Hallucinations in AI 07:14 – Using ChatGPT for Everyday Tasks 07:56 – Principles of Prompt Engineering 08:15 – Basic Prompting Techniques 08:36 – Intermediate Prompting Techniques 08:57 – Advanced Prompting Techniques 09:19 – Ultra-Advanced Prompting Structure 09:59 – Best Practices for Using ChatGPT 10:19 – Using Images, Documents, and Data 10:37 – Iteration and Feedback with ChatGPT 10:56 – Fact-Checking and Confidence Levels 11:15 – Common Prompting Elements 11:39 – Ensuring Quality and Self-Review 12:03 – Critical Thinking and Bias Awareness 12:22 – Mastering ChatGPT Through Practice 12:57 – Conclusion & Further Resources If you found this episode helpful, don’t forget to like, subscribe, and check out the resources below for more on mastering ChatGPT! 〰️〰️〰️〰️ Beginner ✦ AI for Everyone https://www.coursera.org/learn/ai-for-everyone ✦ Generative AI for Everyone https://www.coursera.org/learn/generative-ai-for-everyone ✦ Introduction to Generative AI (Google) https://www.cloudskillsboost.google/paths/118 ✦ Machine Learning Crash Course (Google) https://developers.google.com/machine-learning/crash-course ✦ Executive Guide: Generative AI (PDF, Google) https://services.google.com/fh/files/misc/exec_guide_gen_ai.pdf ✦ Foundational LLMs and Text Generation (PDF, Google/Kaggle) https://www.kaggle.com/whitepaper-foundational-llm-and-text-generation 〰️〰️〰️〰️ Intermediate ✦ Machine Learning Specialization https://www.coursera.org/specializations/machine-learning-introduction ✦ Neural Networks and Deep Learning https://www.coursera.org/learn/neural-networks-deep-learning ✦ Generative AI with Large Language Models https://www.coursera.org/learn/generative-ai-with-llms ✦ Prompt Engineering for Developers https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/ ✦ Prompt Engineering (PDF, Google/Kaggle) https://www.kaggle.com/whitepaper-prompt-engineering ✦ Prompting Guide 101: Gemini for Google Workspace (PDF, Google) https://services.google.com/fh/files/misc/gemini-for-google-workspace-prompting-guide-101.pdf ✦ Embeddings and Vector Stores (PDF, Google/Kaggle) https://www.kaggle.com/whitepaper-embeddings-and-vector-stores ✦ Microsoft Learn: Generative AI Fundamentals https://learn.microsoft.com/en-us/training/paths/introduction-generative-ai/ 〰️〰️〰️〰️ Advanced ✦ CS324: Large Language Models https://stanford-cs324.github.io ✦ CS25: Transformers United https://web.stanford.edu/class/cs25/ ✦ Fast.ai: Practical Deep Learning for Coders https://course.fast.ai ✦ Agents (PDF, Google/Kaggle) https://www.kaggle.com/whitepaper-introduction-to-agents ✦ Agents Companion (PDF) https://elhacker.info/manuales/Agents_Companion_v2%20%283%29.pdf ✦ Solving Domain-Specific Problems with LLMs (PDF, Google/Kaggle) https://www.kaggle.com/whitepaper-domain-specific-llms ✦ OpenAI Cookbook https://cookbook.openai.com ✦ Anthropic Prompt Engineering Guide https://docs.anthropic.com/claude/docs/prompt-engineering ✦ Responsible AI Practices (Google) https://developers.google.com/machine-learning/responsible-ai ✦ End-to-End Responsibility: A Lifecycle Approach to AI (PDF, Google) https://ai.google/static/documents/ai-responsibility-2024-update.pdf