Open AI News: Fine-Tuning and Customized Models

Significant Advances in Fine Tuning: A New Era of AI Customization with OpenAI

In the constantly evolving field of Artificial intelligence, OpenAI continues to distinguish itself by introducing major improvements to its API of Fine tuning, while expanding its program of Custom Models. These developments mark a turning point in how developers can refine the performance of AI models, reduce latency, improve accuracy, and reduce costs, opening up new avenues for AI personalization at scale.

Evolution of Fine Tuning

The Fine tuning Is a key technique for improving the relevance of AI models, allowing them to better understand specific content and increase their knowledge and abilities for defined tasks. With the launch of the API of Fine tuning In self-service for GPT-3.5 in August 2023, OpenAI allowed thousands of organizations to train hundreds of thousands of models, thus significantly improving the quality and efficiency of these models while optimizing costs and latency.

The new features introduced give developers greater control over the process of Fine tuning. Among these innovations, we find the creation of Checkpoints Reducing the need for re-training and limiting the risk of over-adjustment. The introduction of a”Comparative Playground“Now allows side-by-side human evaluation of the outputs of several models or snapshots of Fine tuning, while the integration of third-party platforms like Weights and Biases enriches the data of Fine tuning available for developers.

Expansion of the Program of Custom models

Beyond the Fine tuning, OpenAI is strengthening its program of Custom Models By Introducing the Assisted fine-tuning. This collaborative approach makes it possible to exploit advanced techniques of Fine tuning, offering tailored support for the establishment of effective training data pipelines and assessment systems tailored to the specific needs of organizations. A striking example of this approach is the partnership with SK Telecom, which has resulted in significant improvements in model performance in telecommunication-related customer service tasks.

Toward Deeper AI Personalization

OpenAI doesn't stop at Assisted fine-tuning. For organizations that need a model that is fully adapted to their specific field, OpenAI proposes to train Custom Models Starting from scratch. These custom models are trained using proprietary data and innovative training techniques to teach the model complex and unique knowledge or behaviors, as demonstrated by partnering with Harvey to create a specialized business law model.

Future perspective

OpenAI envisions a future where the majority of organizations will develop Custom Models, adapted to their industry, their business or their use case. Thanks to the variety of techniques available, custom models can have a significant and specific impact on organizations' AI implementations. OpenAI encourages organizations to explore these new features and consider the Fine tuning and the customization of models as ways to achieve optimal performance and achieve significant results quickly.

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