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Data intelligence company Databricks recently unveiled a novel large language model fine-tuning method – TAO (Test-time Adaptive Optimization). This technology offers new hope for the advancement of open-source models. By leveraging unlabeled data and reinforcement learning, TAO excels in reducing enterprise costs while achieving remarkable results across various benchmark tests. According to tech news outlet NeoWin, TAO...

OpenAI has announced that third-party developers can fine-tune the newly introduced multimodal large model GPT-4o. This feature allows developers to adjust the model's behavior based on specific needs, such as changing the tone, following instructions, or improving the accuracy of technical tasks. Fine-tuning can achieve significant performance improvements with only a small amount of training data and is easy to operate. OpenAI is providing developers with a free allowance of 1 million tokens daily until September 23, as well as a daily free allowance of 2 million tokens for the GPT-4o mini model.