We used novel synthetic data generation techniques, such as distilling outputs from OpenAI's o1-preview, to fine-tune the GPT-4o to open canvas, make targeted edits, and leave high-quality comments inline. This approach allowed us to rapidly improve the model and enable new user interactions, all without relying on human-generated data.
AI will someday produce synthetic data good enough to train itself, effectively. That would be advantageous for firms like OpenAI, which spends a fortune on human annotators and data licenses.
Although synthetic data presents opportunities for efficiencies and enhancements in model training, some researchers caution that dependence on such data could lead to inaccuracies and an unforeseen set of challenges in AI reliability.
Meta partially relied on synthetic captions generated by an offshoot of its Llama 3 models for developing Movie Gen. The groundwork was largely automated, although a team of human annotators were also recruited.
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