TELUS International Launches Fine-Tune Studio to Deliver High-Quality Datasets that Improve the Performance, Adaptability and Safety of Generative AI Models

TELUS International (NYSE and TSX: TIXT), a leading digital customer experience (CX) innovator that designs, builds, and delivers next-generation solutions, including artificial intelligence (AI) and content moderation, today announced the launch of Fine-Tune Studio, a task-execution platform designed to create high-quality fine-tuning datasets for large language models (LLMs) and generative AI (GenAI) models. Fine-Tune Studio will be presented during the company’s attendance at the 2024 World Summit AI in Montreal, Canada on April 24-25.

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Fine-Tune Studio is integrated in TELUS International’s fully-managed AI Data Platform as part of the company’s fully-managed GenAI data services available to LLM builders and adopters. Fine-Tune Studio creates high-quality datasets for LLM fine-tuning in more than 100 languages and can be deployed across domains where specialized responses are required, including science, technology, engineering and mathematics (STEM), healthcare, finance, law, coding and more. Aligning with the paradigm shift to multimodal AI use cases, Fine-Tune Studio supports labeling tasks combining various data types like text, audio, image, and video for supervised fine-tuning (SFT), reinforcement learning through human feedback (RLHF), direct preference optimization (DPO) and red teaming.

“As AI continues to be incorporated into the fabric of society and our daily lives, it is more critical than ever that companies make responsible decisions to ensure the accuracy, diversity and integrity of the datasets used to train their models when scaling their GenAI use cases from concepts to pilots to production and beyond,” said Siddharth Mall, Vice President, Product for TELUS International AI Data Solutions. “With the launch of Fine-Tune Studio, we have taken another significant step forward in our ongoing efforts to develop proprietary technology that supports our ability to deliver expertly-vetted and validated data that improves our clients’ model performance, adaptability, and safety.”

Fine-Tune Studio’s native AI integrations include real-time plagiarism, tone analysis, spelling and grammar checks to improve output accuracy and facilitate users’ task completion, driving increased productivity and efficiency. Configurable and customized task and quality assurance workflows provide easy project management for clients to find the most suitable quality control processes, such as consensus, algorithmic and deterministic, human-in-the-loop, and probabilistic methods.