A project manager at your company is skeptical about using synthetically generated data to fine-tune a new Large Language Model. They argue that only human-created data is reliable and that 'fake' data will degrade performance. Citing the precedent set by several prominent, well-tuned LLMs, how would you justify the strategic value and proven utility of incorporating synthetic data into the fine-tuning process?