2.8M
ITThe stages of AI explained. The last one changes everything—for better or worse
@itsemilyhiggins
#Artificial Intelligence Basics
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ITThe easiest way to start learning AI is not to read everything, it’s to read a few good things 💫
If you’re a beginner, start with Superhuman AI.�If you want something simple but a little deeper, read The Neuron.�If you want quick daily updates, use TLDR AI.�If you want the big stuff fast, read The Rundown AI.�If you want to discover tools, check out Future Tools.�And if you want practical business use cases, read Ben’s Bites.
#aitips #aitools #aitipsandtricks #learnai #aiforbeginners
@itsmariahbrunner
91.9K
FUThe most important AI concepts explained in 8 minutes! All visuals are 100% hand-drawn ✍️ #ai #artificialintelligence #aiexplained #technology #techexplained
@futurewithfawzi
951.0K
JEThere are 3 levels of AI. 🤖 Most people don't know Level 2 and 3 exist.
Level 1 → LLMs (ChatGPT, Claude): Single-cycle responses. Text in, text out.
Level 2 → AI Agents (Cursor AI, Windsurf AI, Claude Code): See your project, execute multi-step workflows, ship features.
Level 3 → Agentic AI : Plans entire projects, sets own goals, works for days autonomously. Like a senior engineer who never sleeps.
Comment what AI content you want to see next 👇
#AI #ArtificialIntelligence #AITools #ChatGPT #AIAgents #MachineLearning #TechTok #AIForBusiness #Automation #FutureTech #AINews #TechEducation #ProductivityHacks #AITechnology #DevinAI #ClaudeAI #CodingWithAI #AIWorkflow #TechInnovation #AIRevolution #StartupTech #FounderTips #BuildWithAI #AIExplained #TechTrends #AIAutomation #SmartTech #AIForFounders #TechShorts #Innovation
@jenandtech
1.2M
FUI spent 100 hours on this and I hope this makes AI easier to understand and less scary for you 🫡
What you’ll learn in this video:
1. The types of AI
2. How AI is created
3. How AI becomes biased
4. How AI generates text
5. How AI generates images
6. The energy cost of AI
7. A brief history of AI
If you have more questions or feedback, please share them in the comments. Follow @futurewithfawzi on IG and YouTube for more AI explainers! and yes, these were drawn by me and not AI 😂 #deepseek #ai #artificialintelligence #tech #openai #microsoft #google #nvidia #technology
@futurewithfawzi
10.2K
JEMost people think AI = ChatGPT. Wrong. 🧠
There are 3 AI terms you need to know:
Level 1 → Agentic AI
Doesn't just answer. Completes goals. Orders groceries, schedules tasks, sends invites. Perceive → Reason → Act → Repeat.
Level 2 → Large Reasoning Models (LRMs)
Shows its work before answering. Breaks complex problems into steps. This is how AI solves math proofs and writes complex code without breaking.
Level 3 → Vector Databases
AI's memory system. Stores meaning, not words. Searches by context, not keywords. "King" and "Queen" are close. "King" and "Banana" are not.
🧠 Agentic AI = the worker
🤔 LRMs = the thinker
💾 Vector databases = the memory
This is the intelligence layer behind every AI tool you use.
Comment "PART 2" if you want the infrastructure layer next 👇
#AI #ArtificialIntelligence #AITools #AgenticAI #TechTok
@jenandtech
110.2K
SIThink before you ask AI.
Before involving AI, pause and ask yourself:
- Is something I can reason through on my own first?
- Have I actually thought through my ideas, or am I hoping AI will finish them for me?
The thinking that happens before engaging with AI is a critical part of what determines the quality and usefulness of the output. It’s where the real advantage lies.
Critical thinking, reasoning, judgment, and idea formulation—( the foundational skills!)— are some of the most important skills of the AI era.
@sineadbovell
410.5K
ATAI basics - Part 1 where I cover what is AI ? what is generative AI ? Common use cases. #keepgrowing #levelup
@atul.aicoach
16.0K
AO🚀 Welcome to Day 1 of 100 Days of AI Learning! 👩💻✨
If you’re curious about Artificial Intelligence but feel overwhelmed by jargon—this series is for YOU. 🎯
Today we’re answering: What is AI?
🧠 AI (Artificial Intelligence) is the simulation of human intelligence by machines. From voice assistants like Siri, to Netflix’s movie recommendations, to facial recognition in your phone—AI is everywhere. It’s all about training machines on massive datasets so they can spot patterns, learn, predict, and make decisions like a pro.
👋 If we haven’t met before, I’m Dr. Meghna Asthana—with nearly a decade of hands-on experience in AI & Machine Learning at top academic institutions in London and Cambridge, and AI startups across Europe and Asia. Now I’m breaking it ALL down into digestible, daily pieces—just for you. 🎓💡
📚 Whether you’re an AI beginner, tech professional, product manager, or startup founder, this 100-day journey will give you the confidence to speak about AI intelligently in meetings, pitches, or everyday conversations.
✨ FOLLOW me @aotc_ai for your daily dose of AI knowledge
👍 Like this video if you learned something new
🔁 Save & share if you’re building your AI fluency
💬 Drop a “Day 1” in the comments if you’re joining the 100-day challenge!
📌 Tag a friend who should start learning AI with you!
#AIExplained #ArtificialIntelligence #WhatIsAI #AIForBeginners #100DaysOfAI #AIlearning #TechExplained #LearnAI #AIEducation #WomenInAI #MachineLearningBasics #DailyAI #FutureOfTech #AIinPlainEnglish #aotc_ai
@aotc_ai
210.9K
JEcomment “data” for full YouTube tutorial on how I built a LinkedIn Data Analyst AI Agent in 6 MIN!
84% of people have NEVER used AI. What level are you on??
Level 1 LLMs (You prompt, it responds): Claude, Gemini, and ChatGPT are fluent in language tasks, but they only predict based on your input. They don’t have awareness once you close down the chat window.
Level 2 Agents (It works alongside you): Cursor, Zapier AI Agents, n8n, GitHub Copilot, and Claude Code. These combine a language model with real tools like browsers (Notion, Google Sheets, Slack, and more). You’re no longer in every loop.
Level 3 Agentic AI (It works without you): ManusAI, Gemini Deep Research, Claude Research. These run in a continuous loop. One prompt, full output with no hand-holding required.
Agents are reactive to your process, while agentic systems are autonomous.
That distinction changes what’s actually possible!
@jessramosdata
612.7K
TIHave you heard of autonomous artificial intelligence? This tool allows you to play with it without having to integrate it into your code (up until this tool you would typically have to have some coding knowledge)! There are so many interesting repositories using this technology to build agent Ais that “work for them”. This is a good way to experience what is possible too. And use it to help you with so many tasks.
#stem #tech #artificialintelligence #ai #coding
@tiffintech
2.3K
TILet me explain what AI inference is, how it works, and why AI companies are racing to reduce the cost of it.
You already know from my other videos what AI training is. Training is the learning phase. Inference is everything that happens after that.
Every single time you type something into ChatGPT and it gives you a response, that’s inference. The model is not learning anything new from your message. It’s using what it already learned during training to generate a response in real time.
Think of it like school. Training is when you study for the exam. Inference is when you actually take it.
So here’s what actually happens when you send a message. First, your text gets broken up into tokens. These are small chunks of words or parts of words. Then each token gets converted into a vector, which is basically a long list of numbers that represents the meaning of that token.
Those vectors get fed through the transformer, which is the neural network architecture behind all of this. It processes them through dozens of layers, figuring out how every word relates to every other word. And at the end, it predicts the most likely next token. Then it does that again and again until you get a full response.
All of this happens in seconds.
Inference is much cheaper and less compute intensive than training. But when you’re doing that for millions of users at the same time, the cost adds up fast. That’s why AI companies are racing to make inference faster and cheaper, and building specialized chips to do it.
So when someone says a model was “trained,” that’s the learning phase. When you actually use it, that is the inference phase.
This video is part of a new series where I explain common tech terms. If you like content like this, definitely follow along for more.
@timothybramlett
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