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OpenAI announced that it is partnering with San Francisco based data labeling startup Scale to help more companies benefit from fine-tuning its text generating model GPT-3.5.
The company in their blog post stated that it is working with Scale as a preferred partner to extend the benefits of our fine-tuning capability given its experience helping enterprises securely and effectively leverage data for AI.
OpenAI further said they have extended the opportunity to Scale customers to fine-tune OpenAI models, mirroring the process they would follow with OpenAI. Moreover, these customers stand to gain from Scale’s proficiency in enterprise AI and the utilization of their Data Engine.
“Scale extends our ability to bring the power of fine-tuning to more companies, building on their enterprise AI experience to help businesses better apply OpenAI models for their unique needs.”said Brad Lightcap, COO, OpenAI.
OpenAI a day earlier had announced that fine-tuning for GPT-3.5 Turbo is now available and fine-tuning for GPT-4 is coming this fall. OpenAI has stated that the fine-tuning of GPT 3.5 Turbo is suitable specifically for businesses and developers to customize the model depending upon their use case as it lets them train the model on company’s data and run it at scale.
Founded in 2016, Scale’s Generative AI Platform leverages enterprise data to customize powerful base generative models to safely unlock the value of AI.
“We are excited to partner with OpenAI to supercharge model performance – helping every enterprise utilize AI most effectively for their unique needs. Prompting alone—atop even the best LLMs like GPT-3.5 — is not enough model customization to produce the most accurate, efficient results. As with software, an incredible amount of value comes from fine-grained optimizations, and fine tuning is critical for that.” said Alexandr Wang, Founder and CEO, Scale AI
Scale has earlier worked with American financial service and technology company Brex. Scale in their blog post claimed that by using the GPT-3.5 fine-tuning API on Brex data annotated with Scale’s Data Engine, they saw that the fine-tuned GPT-3.5 model outperformed the stock GPT-3.5 turbo model 66% of the time.