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Startup Building: Challenges & Opportunities
The Ben & Marc Show
Self-improvement through iterative model training
Training models with synthetic data to solve problems across multiple steps, then retraining based on the results enables them to solve complex problems in a single step. This approach reflects a self-improvement loop where models learn and generalize through iterative training. By guiding the model through the initial multi-step process and then retraining it, the model can learn to perform tasks without the need for handholding in subsequent iterations. This mimics human learning processes, where individuals are taught step-by-step until they can perform tasks independently.
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