Music can make your videos sound amazing and help set the right mood. But you must be careful when using songs that belong to someone else. YouTube watches this very closely, and using copyrighted music can cause problems for your channel. Here is what can happen: 💥 Copyright Claim The owner of the song lets your video stay up, but they get the ad money instead of you. 💥 Copyright Strike This is more serious. The owner tells YouTube to remove your video. If you get three strikes within 90 days, your whole channel can be deleted. So take strikes seriously and try to fix them right away. 💥 Muted or Blocked Video YouTube can mute your video or block it in some countries if the music is not allowed. How to stay safe with music: 💥 Use free songs and sound effects from YouTube’s Audio Library. The music there is not the greatest. In my opinion, a lot of it sounds a little corny. But it is safe and will not cause copyright issues. 💥 Pay for music from trusted royalty free sites like Epidemic Sound, Artlist, and Envato Elements. They have better quality music and give you peace of mind. 💥 Use CreatorMix.com — a site I have used myself. It is 100% free and safe to use with no copyright problems. 💥 Make your own background music or use AI tools to create simple tracks. 💥 Always check the license before you use a song. Summary: If you did not make the music or get permission to use it, do not use it. Stick to safe or royalty free music. That keeps your channel protected and stress free. Keep creating, stay smart, and remember — you got this! 🙌

Nice session. I learned, met, have been inspired and encouraged. Thank you! Nicole

Welcome to the group! I'm thrilled to help you on your journey to build a $7-figure AI-Powered Business! Tell us what you do, what you would like to help others with and what you want to learn from this community.

I’ve been wondering what might happen if everything below collapsed into one unified AI model with self-awareness, meaning we (or at least the builders) can observe and understand what’s going on inside: - Latent spaces (compressed, low-dimensional representations that capture underlying data features) - Liquid Neural Networks (LNNs). which I started creating myself two years ago, based on MIT’s innovations - Tokenformers (which may have the potential to replace transformers) - Hybrid models (combining multiple AI techniques for greater robustness and versatility) - New lenses on paradigms - Some form of self-emergent empathy I suspect such a model could be surprisingly compact, potentially only a few million parameters and sized somewhere between 30 to 50 MB, maybe up to 100 MB. Of course, this is a rough estimate, but it’s exciting to imagine. Such models could easily run on phones without problems, and I believe they might even outperform current models like OpenAI’s and Claude’s. Let’s see how far off I am, and when this actually happens. This isn’t about reaching the end of prompting, context engineering, red teaming, or agentic AI workers—those will continue evolving. But I believe the next paradigm shifts are just around the corner. What are your thoughts on this? P.S. If you’re wondering where the research papers or articles on this are...I don’t have any to share yet. These are my own thoughts, exploring the future possibilities of AI.

I generated these videos- short rap battles between Siri & PAC & Biggie. Now on to some marketing videos.