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Mighty Minions: Unleashing domain-specific GenAI via SLMs

URN M24.0.620
Topics AI (Artificial Intelligence), Data management, Sustainability

CSP GenAI revolution - establishing a seamless and accessible pathway for enterprises to harness the power of pre-trained small language models.

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LLMs like OpenAI's ChatGPT have gained attention for their capabilities, but the associated expenses and challenges have fueled interest in alternatives. Smaller Language Models (SLMs) offer cost efficiency, deployment flexibility, and enhanced privacy control. Enterprises are shifting to domain-specific SLMs, extracting maximum value by tailoring models to their needs. CSPs, with vast datasets, can construct personalized SMLs, that can be used in conjunction with their network and edge ecosystem offerings supporting enterprises and exploring new revenue streams both for CSPs and their customers (B2B2X) across diverse sectors. Communication Service Providers (CSPs) possess multiple data sources within their environments, encompassing customer data, network data, and OSS/BSS data. These extensive datasets can serve as valuable resources for generating clean and structured data, ideal for pre-training language models. Many GenAI use cases necessitate a fusion of data from diverse systems. The proposed Catalyst solution introduces an architectural framework wherein all Telco data is centralized on a single platform. This consolidated platform enables unified access to unstructured data, facilitating the creation of clean and pre-processed datasets. Moreover, the architecture prioritizes addressing risks and security implications, including considerations for outcome accuracy, data protection, cyber risks, and privacy. The GenAI Framework we propose is designed for CSPs to harness existing pre-trained data and develop their own language models using Small Language Models. This initiative specifically targets domain-specific use cases , allowing CSPs to tailor solutions according to the unique needs of various industries. One key aspect of this framework is its capability to empower CSPs to extend this service to other enterprises. By doing so, enterprises gain the ability to efficiently and effectively create their own General AI (GenAI) models, leveraging their proprietary data. The framework spans the entire lifecycle of model development, encompassing crucial stages from initial training to the ultimate deployment of models. This comprehensive approach ensures that CSPs and enterprises utilizing the framework have the necessary tools and capabilities to navigate each phase seamlessly. Finally, CSPs are envisioned to expose some of the models generated within the GenAI Framework as APIs to enterprises. This strategic move allows enterprises to access and utilize pre-trained small language models seamlessly.

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Team members

AXIATA DIGITAL LABS (Pvt) Ltd logo
Amazon Web Services, Inc. logo
Deutsche Telekom AG logo
Champion
Dialog Axiata PLC logo
Champion
EZECOM Co., Ltd. logo
Champion
Econet Wireless Zimbabwe logo
Champion
Infosys logo
Philippine Long Distance Telephone Company (PLDT) logo
Champion
SMART COMMUNICATIONS, INC. logo
Champion
Sri Lanka Telecom PLC logo
Champion
Tata Consultancy Services logo
Verizon Communications logo
Champion

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