This post is co-written with Vladimir Turzhitsky, Varun Kumar Nomula and Yezhou Sun from MSD. Generative AI is transforming the way healthcare organizations interact with their data. Large language models (LLMs) can help uncover insights from structured data such as a relational database management system (RDBMS) by generating complex SQL queries from natural language questions, …
Resilient architectures are the foundation upon which successful businesses are built. However, keeping up with the latest advancements and making sure your systems are resilient can be a daunting task. Between monitoring, analyzing, and documenting architectural findings, a lack of crucial information can leave your organization vulnerable to potential risks and inefficiencies. Even when architectural …
Generate AWS Resilience Hub findings in natural language using Amazon Bedrock Read More »
Recent enhancements in the field of generative AI, such as media generation technologies, are rapidly transforming the way businesses create and manipulate visual content. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, …
This post is co-authored with Nishant Gupta from InsuranceDekho. The insurance industry is complex and overwhelming, with numerous options that can be hard for consumers to understand. This complexity hinders customers from making informed decisions. As a result, customers face challenges in selecting the right insurance coverage, while insurance aggregators and agents struggle to provide …
Google.org announced a $20 million commitment to support AI for scientific breakthroughs. Learn more about what the commitment entails
Google DeepMind and the Royal Society are co-hosting the AI for Science Forum to explore how AI is rapidly accelerating science.
A recap of the some of the biggest scientific breakthroughs over the past two years.
The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development. Responsible AI is a practice of designing, developing, and operating AI systems guided by a set of dimensions …
In Part 1 of this series, we defined the Retrieval Augmented Generation (RAG) framework to augment large language models (LLMs) with a text-only knowledge base. We gave practical tips, based on hands-on experience with customer use cases, on how to improve text-only RAG solutions, from optimizing the retriever to mitigating and detecting hallucinations. This post …
From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2 Read More »
