If you are curious what my late nights look like, its staying up till 2 Am to post videos like this. Twelve minutes on thinking machines. Descartes, Lovelace, Turing, Searle's Chinese Room, and why the AI consciousness argument we're having right now is already four hundred years old. Animations built with my automation structure. Script and content is all me though. Going to decide where this fits in the courses and maybe make a text companion. A new style I may keep for a genre of future videos if people like it. Let me know what lands.

Second Monday. Second winner. Let's keep it going. @Alex Nartey topped the 7-day leaderboard with +191 points and earned himself free lifetime Premium access. 71 total contributions to this community. Not lurking. Not watching from the sideline. Showing up in the comments on Jake's posts, Matt's posts, other members' posts. Adding to the conversation. Engaging with the work. That's what the leaderboard actually measures. Participation that helps other people learn. Alex wasn't farming points. He was in the threads doing the thing that makes this community worth being in. 🎉 @Alex Nartey congratulations. You earned it. The leaderboard resets now. New week. New race. Whoever is on top next Monday morning gets the same deal. Free lifetime Premium. Already a paying VIP member? We'll upgrade you to free lifetime VIP. See you next Monday!!

Before joining this community, I thought I needed better prompts. Turns out I was asking AI to work with nothing, no context, no structure... just random chats. Everything changed when I did one simple thing. I defined; what I’m building, what “good” looks like and what to avoid. That’s it. The outputs improved not because the AI got smarter, but because it stopped guessing. Most people here are still trying to “talk better” to AI, but remember better wording doesn’t fix missing structure. Are you still refining prompts… or actually building systems around them?

Over the past couple of days, there have been numerous discussions about the heavy use of acronyms in the AI space and the overwhelming frustration that those new to AI often feel when trying to understand conversations in the community. I created this resource to help.Below is a comprehensive, well-organized list of the most commonly used acronyms in AI — covering LLMs, prompting techniques, model architectures, training methods, tools, and more. Whether you're just starting out or looking to fill in the gaps, this should serve as a quick and handy reference.Commonly Used Acronyms in the AI Space Core AI & ML Foundations - AI — Artificial Intelligence - AGI — Artificial General Intelligence - ASI — Artificial Superintelligence - ML — Machine Learning - DL — Deep Learning - RL — Reinforcement Learning Models & Architectures - LLM — Large Language Model - SLM — Small Language Model - LMM — Large Multimodal Model - VLM — Vision-Language Model - GPT — Generative Pre-trained Transformer - BERT — Bidirectional Encoder Representations from Transformers - MoE — Mixture of Experts - CNN — Convolutional Neural Network - RNN — Recurrent Neural Network - LSTM — Long Short-Term Memory - GAN — Generative Adversarial Network Techniques, Prompting & Alignment - CoT — Chain of Thought - ToT — Tree of Thoughts - RAG — Retrieval-Augmented Generation - RLHF — Reinforcement Learning from Human Feedback - DPO — Direct Preference Optimization - LoRA — Low-Rank Adaptation - QLoRA — Quantized Low-Rank Adaptation - PEFT — Parameter-Efficient Fine-Tuning - ReAct — Reason + Act Other Practical & Business Terms - POC — Proof of Concept - MVP — Minimum Viable Product - GenAI — Generative AI - MLOps — Machine Learning Operations - AEO — Answer Engine Optimization This list focuses on the acronyms you’ll encounter most frequently in papers, forums, product documentation, and day-to-day AI discussions. Feel free to bookmark this post — I’ll keep it updated as new terms become common. If you come across an acronym that’s missing or want a deeper explanation on any of them, just drop a comment and I’ll add it.

I saw this on LinkedIn and I can’t help but wonder what went wrong? Text reads thus: “We just did an "Al layoff" due to rising costs ••• Turns out Al is getting way too expensive. We just canceled 5 of our Al subscriptions and hired 2 mid-level devs instead.” What are your thoughts?