Join us for an in-depth live coding session where we’ll explore building powerful, domain-agnostic assistants using fine-tuned smaller models and Rasa’s CALM paradigm. This session will focus on creating efficient conversational AI assistants that are both cost-effective and reliable.
What You’ll Learn:
- Using Fine-Tuned Models: Learn how to fine-tune smaller models and self-host them to enhance the performance of your conversational assistant.
- Cost-Efficiency & Reliability: Optimize your assistant for latency, token usage, and overall performance while keeping costs under control.
- Rasa’s CALM Paradigm: Master Rasa’s advanced approach to building robust assistants without needing large, resource-intensive models.
- Advanced Deployment: Get insights into seamlessly deploying fine-tuned models into production environments.
Who Should Attend:
- AI developers and practitioners interested in building scalable, fine-tuned AI assistants.
- Enterprise users looking to leverage AI for cost-effective and reliable solutions.
- Anyone eager to dive deep into advanced conversational AI techniques using smaller, more efficient models.
Session Details:
- Hands-On Approach: This isn’t a full code-along, but we’ll walk through the practical steps to fine-tune, deploy, and evaluate your own conversational AI assistant.
- Expert Guidance: Led by Daksh Varshneya, Senior Product Manager at Rasa, and Hugo Bowne-Anderson, independent data and AI scientist.
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