Transforming Scientific Research and Innovation in the AWS Cloud

Generative AI is projected as having the potential to revolutionize the field of life sciences and healthcare such as Protein Sequence Design, Protocol Optimization, Medical Legal Review, Diagnostic Accuracy, Synthetic Data Generation and Sales Force Training. However, the successful integration of Large Language Models requires addressing challenges and considerations specific to the life sciences domain and ensuring utilization of best practices such as Prompt Engineering, Fine Tuning and Reinforcement Learning from Human Feedback. By adopting a multifaceted approach, usage of domain specific data and fostering interdisciplinary collaboration, Generative AI can be developed, validated, and integrated into life sciences value chain, effectively. Ultimately, these mechanisms can ensure that LLMs enhance patient care and improve overall outcomes from bench to bedside.
From this session you will learn
• The Overview of Generative AI
• Generative AI Use Cases for Life Sciences
• Generative AI Approach from AWS
• How to take next steps in deploying Generative AI Use Cases