Level: Foundational Category: AI System Categories This term introduces the major categories of AI systems and what they are designed to do in practical use. 🪄 Simple Definition: A Large Language Model (LLM) is an AI system trained to understand, interpret, and generate human language. 🌟 Expanded Definition: LLMs are built using deep learning and trained on massive collections of text. This enables them to recognize patterns, understand context, and produce writing that feels natural and human-like. Examples include ChatGPT, Claude, Gemini, and Grok.LLMs can summarize documents, answer questions, write content, support research, and assist in decision-making.They don’t “think” like people—they generate responses based on statistical patterns learned during training. ⚡ In Action: You type: “Draft a follow-up message for customers who missed their service appointment.” The LLM produces a polished, professional message in seconds. 💡 Pro Tip: Clear instructions produce stronger results. Define the role, purpose, tone, and audience to guide the model effectively. This term is part of the Classroom Course - AI Fundamentals

✨ The Quirk: If you ask ChatGPT what time it is, it can’t actually tell you — even though it feels like it should. There’s no built-in awareness of the current clock or moment. What’s Going On: - ChatGPT doesn’t have a live clock or real-time awareness by default. - It generates responses based on patterns, not the current moment. - Time only exists for the model if you explicitly provide it. - So asking “What time is it?” is a bit like asking a calculator what day it is. 🔧 What To Do If You See It: - Don’t assume AI knows “now” — give it the time when it matters. - Include the date, time, or timeframe directly in your prompt. - Try this prompt: “It’s currently 3:15 PM on Tuesday. Based on that, what should I do next?” Why This Matters: This quirk is a reminder that AI is context-driven, not situationally aware. The clearer the context you provide, the smarter it feels. This one genuinely surprised me. For some reason, I assumed “knowing the time” was basic. Turns out, it’s not. Does this surprise you too? Or is this something you already knew? Try asking ChatGPT the time, and see what response you get.

If you’re new to the community — or you’re just starting to use (or trying to understand) ChatGPT and tools like it — this is the course for you. We’ve just added a new Classroom course: How LLMs Like ChatGPT Work This course is designed to help you understand what’s actually happening when you use ChatGPT, so you can stop guessing and start getting better results. The big idea is simple:👉 The more you understand how ChatGPT works, the better you can guide it with your prompts. What you’ll learn: - The building blocks behind ChatGPT and large language models (LLMs) - How prompts, responses, and conversation work together - Why ChatGPT answers the way it does — and why it sometimes sounds confident but gets things wrong - How this understanding helps you write clearer prompts and use AI more intentionally 📌 Quick Note: There are many LLMs similar to ChatGPT available today, like Gemini and Claude, which are covered in a separate course. In this course, we use ChatGPT illustratively to explain how LLMs work in practice. This course is: - Beginner-friendly - Plain English - Built for real-world use (not engineers) If you’ve ever wondered why ChatGPT responded the way it did — or how to steer it more effectively — this course will help.

Real quick question — what email platform do you mostly use? I’m shaping upcoming classroom content and want the examples to line up with how you really work, not just theory. Thanks for taking a second to vote 👍

I was very excited to try the new Oakley Meta HSTN Transitions® AI Glasses. Short Review: A Strong Concept, Still Early Full Review: I recently spent time testing the Oakley Meta HSTN Transitions® AI glasses, and while I genuinely like the direction Meta and Oakley are heading, my overall takeaway is that this product still feels more like an early glimpse of the future than a finished, everyday device. This specific model combines Oakley’s sport-forward HSTN frame design with Transitions® lenses that automatically shift from clear to tinted based on lighting conditions. On paper, it sounds like an ideal blend of performance eyewear and AI-powered convenience. In real-world use, though, the experience is more nuanced. What These Glasses Are — and Aren’t: An important expectation to set up front: there is no visual display. Nothing appears in your field of view. All interaction happens through audio and voice commands. That design choice keeps the glasses lightweight and familiar, but it also defines the experience. These are not augmented reality glasses. They function more like hands-free AI-enabled audio glasses with cameras. Key Features: This model brings together several notable features: - Transitions® lenses that adapt automatically between indoor and outdoor lighting - Open-ear audio built into the frame for music, calls, and spoken responses - Hands-free voice control for asking questions, capturing photos or video, and triggering actions - Dual built-in cameras integrated into the frame - Sport-oriented Oakley design, clearly intended for outdoor and active use From a hardware perspective, this is a meaningful step forward compared to earlier Meta frames. The Oakley design finally makes the concept feel purposeful rather than experimental. What Works Well: The audio quality is better than expected, particularly outdoors. Music, calls, and spoken responses come through clearly without fully blocking ambient sound — an important detail for safety and awareness during activity.