Bright Data: https://brdta.com/codingwithlewis I tried training an AI model on 10,000+ memes to see if AI can be funny. In this video, we go through the process of creating a meme with AI and learn why we find things like memes and humor funny to begin with. This video took a very long time to make. Over 10 different models were used. Throughout this video you will see all of the things that I did to get this to work. Let me know what you think in the comments :) 👉WE ARE PLANNING A HACKATHON!!! 👈 Join the discord to learn more: https://dsc.gg/lewismenelaws 🧑💻DEMO & SOURCE CODE🧑💻 Demo: https://memegenerator-ergog3zn3pc7txnm6mgggf.streamlit.app/ GitHub: https://github.com/CodingWithLewis/MemeGenerator (messy lol) Fine-Tuned Model: https://huggingface.co/codingwithlewis/mistralmemes OwlV2 Demo: https://huggingface.co/spaces/codingwithlewis/owlv2 If you like this video, check out some of my other videos where I build awesome projects and provide awesome developer resources that you can use in order to be a better developer :) LINKS --- MY NEWSLETTER 💌 https://thebetter.dev ------ CONNECT WITH ME ON SOCIAL 📸 Instagram: https://instagram.com/lewismenelaws 🎚TikTok: https://tiktok.com/@lewismenelaws 🐣 Twitter: https://twitter.com/LewisMenelaws — My gear 💻 https://liinks.co/lewismenelaws ----- TIMESTAMPS 0:00 Intro 0:22 Why is AI not funny? 0:40 What is a meme... really? 1:51 Getting a LARGE amount of memes 2:32 The Data Collection 3:29 Using Bright Data 4:12 Initial Results 4:45 Prepping for Training 5:11 Getting image descriptions 6:03 Returned image descriptions 6:35 Training the AI Model 7:57 Results... and de-motivation... 8:49 Realizing... I should teach AI how to be funny 9:35 Getting Relevant Context 10:20 Initial Observations 10:37 Labelling Feature 11:27 The right AI model for the job... 12:14 Building out the UI 12:51 Reactions 14:08 Why I made this video... 14:40 SUBSCRIBE