IE University, Calle de María de Molina, 31, Madrid, 28006
This workshop is a masterclass in leveraging the power of RAG for combining the raw power of LLMs with the specificity of information retrieval. This session aims to bridge the gap between academic knowledge and practical skills in cloud-based AI.
🚀 Launch into the forefront of cloud computing and AI with our hands-on workshop on deploying a large language model (LLM) on Google Cloud Platform (GCP) using Retrieval-Augmented Generation (RAG).
This workshop is a masterclass in leveraging the power of RAG for combining the raw power of LLMs with the specificity of information retrieval. This session aims to bridge the gap between academic knowledge and practical skills in cloud-based AI.
🌟 Session Highlights:
- Model Deployment: Receive step-by-step guidance on deploying LLMs to GCP, with a focus on integrating RAG for heightened performance.
- API Connectivity: Engage in practical demonstrations on API integration to facilitate real-time AI interactions.
- Optimization Techniques: Discover methods for fine-tuning your LLM and RAG setup, optimizing for both efficiency and cost.
🧠 Why Attend?
- Transition from theory to practice with immersive, hands-on experiences in cloud AI deployments.
- Acquire forward-thinking skills pivotal for the emerging landscape of cloud services and AI technologies.
👥 Who Should Attend?
- Master’s students and aspiring professionals in Computer Science, AI, and related disciplines looking to advance their practical skill set.
- Developers and future cloud engineers aiming to deepen their expertise in AI model deployment.
- Innovators seeking to understand the synergy between AI and cloud platforms.
🎯 **Join us and connect academic learning with real-world applications. Stand at the forefront of the AI and cloud computing revolution!**
Wednesday, May 8, 2024
2:00 PM – 3:15 PM UTC
GDSC Lead
GDSC Lead
GDSC Lead
Tech Lead
Tech Lead
Tech Lead
Micromanagement Lead
Communications Lead
Tech Lead
Tech Lead
Managerial Lead
Communications Manager
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