The data "supply chain" has already surged ahead of production elsewhere. Companies aren't just passively taking what's out there, they actively harvest highly

The data "supply chain" has already surged ahead of production elsewhere. Companies aren't just passively taking what's out there, they actively harvest highly curated content, benefiting even further when we voluntarily correct and refine their models. Heck, some of us are even paying them for the privilege of training AI. The best time to have made this argument would've been when GPT originally released, but I think most people were too enamored with it to care and the idea it would be "open-source" meant we'd get it back at the end of the day. Unrelated, but this is exactly why I've been spending time building my AI framework (TSCE). The idea is to leverage these open-weight LLMs, typically smaller and accessible, to achieve accuracy and reliability comparable to larger models. It doesn't necessarily make the models "smarter" (like retraining or fine-tuning might), but it empowers everyday users to build reliable agentic workflows or AI tools from multiple smaller LLM instances. Check it out: https://github.com/AutomationOptimization/tsce_demo https://github.com/AutomationOptimization/tsce_demo