Self-improvement through iterative model training

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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.

"It turns out the spreadsheet is not actually the business, despite what you may have learned in business school." - Ben Horowitz

Welcome back to "The Ben & Marc Show" featuring a16z co-founders Marc Andreessen and Ben Horowitz. In this second episode of a two-part series, Marc and Ben answer MORE questions about startup building in the post-COVID world.

In this one-on-one conversation, Ben and Marc discuss how startups can think differently about organizational design and talent deployment, unpack the lore around layoffs, and even tackle the future of customer service. They also reveal some unexpected benefits of nicotine and Ozempic. That and much more. Enjoy!

*Watch the FULL EPISODE on YouTube: https://youtu.be/Fw4p85jSfQc

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