At NetoAI, we excel in telecom AI and voice AI, focusing on unique data challenges within the telecommunications sector. Traditional AI models struggle with the specialized datasets generated by telecom networks, prompting the need for a dedicated, open-source Telecom Large Language Model (TSLAM). Using AWS Trainium and Amazon SageMaker, we developed TSLAM to deliver precise, scalable AI solutions for telecom operators.
AWS Trainium enhanced our model training by accelerating processes, reducing costs, and providing a secure, managed environment. Utilizing the LoRA method, we fine-tuned TSLAM efficiently, achieving significant performance improvements. Upon deployment, TSLAM demonstrated rapid inference capabilities, with latencies between 300-500 ms. It’s now integral to our VING platform, powering applications like network diagnostics and customer support.
Looking ahead, we plan to leverage Amazon EC2 Trn2 instances for further advancements in generative AI for telecommunications, thus redefining industry-specific AI applications and maintaining a competitive edge.
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