Open source vs open weight in AI: two terms everyone uses and almost nobody defines the same way.
These two labels stopped meaning what they did back in the Apache and MIT days, and the gap matters more than it looks. Truly open source means something specific, almost no model clears that bar, and there's exactly one that does. The expensive detail sits inside the Llama license: a clause that can drag a growing startup into a lawsuit with Meta.
? What you'll learn:
1️⃣ Why open source in AI needs both the weights and the training data, not just one
2️⃣ The real reason companies share weights but never the training data
3️⃣ How open weight differs from open source, using Llama and DeepSeek as examples
4️⃣ The 700 million user clause in the Llama license almost nobody reads
5️⃣ What's actually at risk when you send data to closed models like OpenAI and Anthropic
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⏰ Timestamps:
00:00 - Why Open Source and Open Weight got confusing
00:38 - Open Source Model Explained
02:11 - Difference between Open Source and Open Weight
05:07 - The Llama license clause that can sue you
06:30 - Conclusion
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