

As artificial intelligence continues to evolve, organizations are finding out that bigger isn't always better when it comes to language models. This webinar will help business owners learn how to turn large language models (LLMs) into smaller, specialized models that deliver targeted performance at a fraction of the cost.
In this session, we'll explore techniques like knowledge distillation and model pruning to create more efficient AI solutions for your business. We'll discuss how these streamlined models can run more effectively on your devices, reducing costs while maintaining the intelligence and accuracy your business requires.
Learning Objectives:
- Understanding the business case for model distillation versus large-scale deployments
- Mastering knowledge distillation and pruning techniques for your specific use cases
- Implementing specialized AI solutions within existing infrastructure constraints
- Building a distributed AI strategy that scales across workstations

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