To assist business customers in creating customized generative artificial intelligence models utilizing its software for specific scenarios, fields, and programs, OpenAI is growing its Custom Model program.
Presented at OpenAI’s first-ever developer’s conference, DevDay, the previous year, Custom Model allows businesses to collaborate with a team of committed OpenAI academics to develop and enhance systems for particular fields. Since then, “dozens” of clients have signed up for Custom Model. However, OpenAI claims that after interacting with this first group of users, it has realized that the program must expand to optimize efficiency.
Custom-trained algorithms and supported fine-tuning follow.
A new feature of the Custom Model system supported fine-tuning, allowing companies to establish data training lines, systems for assessment, and other supporting systems to enhance model performance on specific tasks. According to OpenAI, these techniques include further hyperparameter settings and effective fine-tuning techniques at higher levels.
Regarding custom-trained models, OpenAI describes them as unique models created for clients who require “more profoundly fine-tuning their models” or “integrating additional, domain-specific information” by utilizing OpenAI’s foundation algorithms and instruments (e.g., GPT-4).
OpenAI uses the Korean telecom powerhouse SK Telecom to demonstrate how it collaborated with OpenAI to optimize GPT-4 to perform better in “telecom-related talks” in Korean. Another client, Harvey, collaborated with OpenAI to develop an individual algorithm for case law that included input from licensed expert legal professionals and tens of billions of characters of regulatory text. Harvey is developing AI-powered juridical instruments with assistance from OpenAI Startup Fund, the company’s AI-focused venture arm.
According to a blog post by OpenAI, “We expect that most enterprises in the future will create individualized models that are tailored to their sector, business, or use case.” Corporations can create customized models using a range of available building methodologies, enabling them to get more targeted and significant outcomes from their machine-learning applications.
OpenAI is allegedly getting nearly an incredible $2 billion in income annually. However, there is undoubtedly internal pressure to keep up the pace, especially as the business plans to co-develop a one-hundred billion cloud computing facility with Microsoft (if rumors are being followed). After all, the price of developing and maintaining signature generative artificial intelligence models will be around for a while. Therefore, consulting services like custom model training may be the key to keeping revenue growth until OpenAI decides what to do.
Optimized and personalized models may relieve OpenAI’s model servicing framework burden. As the need for artificial intelligence that is generative grows more intense, customized models—which are frequently more compact and practical compared to their universal counterparts—undoubtedly provide an alluring alternative to OpenAI, which has traditionally struggled with computing power.
Today, OpenAI announced additional model fine-tuning capabilities for developers using GPT-3.5 and the broadened Custom Model system and custom model creation. These features include an updated dashboard for evaluating model performance and quality, assistance with combinations using third-party applications (beginning with the artificial intelligence creator platform Weights & Biases), and improvements to equipment. However, GPT-4, which debuted in the early stages during DevDay, is still being fine-tuned.
