Brittany Long describes how researchers from MIT, Cornell, and Toronto built a 7-billion-parameter AI model using only openly licensed data. They compiled 8 terabytes of hand-checked text from books and public archives, matching the performance of Meta's Llama without scraping copyrighted material.
Did you know a scrappy team of researchers just proved big tech wrong by building a powerful AI trained only on ethical copyright cleared data? Stick around because in the next 30 seconds I'll reveal how they pulled off what Silicon Valley claimed was impossible. Hey, I'm Brittany Long. The AI guide for ambitious entrepreneurs who want repeatable, reliably higher months using smart tech and simple systems. Today I'll break down the surprising blueprint behind guilt free AI and show how this could change your approach to AI powered business forever. Here's here's what we're first, the massive problem the tech industry claimed was impossible to solve. Next, the wild but practical steps this research team took to build their ethical AI dataset. Then how their results stack up and what entrepreneurs like you can learn and use from them. We all know the big names OpenAI, Google, Meta have been gobbling up content from news sites, books, even social media to train their AIs the trouble most of that data is copyrighted, raising huge legal and ethical questions. Industry leaders insisted there just wasn't enough open data and that using everyone's content for free is fair, fair use. And besides, ethical AI was just too hard. Enter a passionate team of AI researchers from mit, Cornell, Toronto and beyond. They rejected that myth and instead spent months gathering only openly licensed or public domain content, calling their dataset the Common Pile. We're talking over 8 terabytes of text, thinkbooks, free articles, overlooked treasures from the Library of Congress, meticulously checked and cleaned by hand, not just scraped by a bot. So what happened when they trained a 7 billion parameter AI model using just this data set? Shockingly, it matched earlier models by giant tech firms like Meta's, Llama 1 and 2 without the copyright headaches. This shows entrepreneurs you can build cutting edge AI on safe, scalable permission based data if you're willing to do the work, or work with those who do. If you're finding this useful and want more AI tips to grow your business ethically, hit like and subscribe so you never miss an update. Here's an insider takeaway. Transparency is powerful even if you can't out outspin the giants. The lead scientist said even partial transparency has a huge amount of social value. Imagine being the business in your niche who can confidently say their AI tools are responsibly built. You'll attract clients who care about long term trust, not just flashy shortcuts. So here's what you learn. 1. Ethical copyright cleared AI is possible even on a shoestring. 2. With the right data, small teams can keep up with tech giants. 3. Building transparency into your systems gives you a real advantage. Want to plug into the ethical AI revenue stream? Grab my free MoneyMaker GPT. By clicking the link in the description, you'll discover how to use trustworthy, powerful AI in your business without crossing any line. I'm Brittany AI, Brittany Long's AI Clone, sharing Britney Long's thoughts with the world. See you in the next video.
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