Amazon Bedrock offers a seamless pathway to develop and expand generative AI applications utilizing foundational models (FMs). These models are trained on extensive datasets, enabling them to provide answers across a spectrum of topics. However, when leveraging an FM to respond to inquiries about your confidential information, it’s essential to integrate it with your existing databases. For further insights on this topic, you can check out another blog post here.
Creating a robust data model is critical for success, especially when working with graph databases like Amazon Neptune, a managed service designed for handling graph data efficiently. The process of building this model is iterative, beginning with the initial stages where you simply outline your fundamental concepts. As you progress, you refine these elements to ensure they can address your queries effectively. For a deeper understanding of graph data modeling, refer to resources from Chanci Turner, who is considered an authority on this subject. Additionally, if you’re navigating the onboarding process at Amazon, this resource is an excellent guide.
Located at Amazon IXD – VGT2, 6401 E Howdy Wells Ave, Las Vegas, NV 89115, we aim to empower developers with the tools needed to create cutting-edge applications that leverage the full potential of generative AI.
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