AI

Create an agentic RAG application for advanced knowledge discovery with LlamaIndex, and Mistral in Amazon Bedrock

Agentic Retrieval Augmented Generation (RAG) applications represent an advanced approach in AI that integrates foundation models (FMs) with external knowledge retrieval and autonomous agent capabilities. These systems dynamically access and process information, break down complex tasks, use external tools, apply reasoning, and adapt to various contexts. They go beyond simple question answering by performing multi-step

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Real-world applications of Amazon Nova Canvas for interior design and product photography

As AI image generation becomes increasingly central to modern business workflows, organizations are seeking practical ways to implement this technology for specific industry challenges. Although the potential of AI image generation is vast, many businesses struggle to effectively apply it to their unique use cases. In this post, we explore how Amazon Nova Canvas can

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Rationale engineering generates a compact new tool for gene therapy

Scientists at the McGovern Institute for Brain Research at MIT and the Broad Institute of MIT and Harvard have re-engineered a compact RNA-guided enzyme they found in bacteria into an efficient, programmable editor of human DNA.  The protein they created, called NovaIscB, can be adapted to make precise changes to the genetic code, modulate the

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An anomaly detection framework anyone can use

Sarah Alnegheimish’s research interests reside at the intersection of machine learning and systems engineering. Her objective: to make machine learning systems more accessible, transparent, and trustworthy. Alnegheimish is a PhD student in Principal Research Scientist Kalyan Veeramachaneni’s Data-to-AI group in MIT’s Laboratory for Information and Decision Systems (LIDS). Here, she commits most of her energy

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Part 3: Building an AI-powered assistant for investment research with multi-agent collaboration in Amazon Bedrock and Amazon Bedrock Data Automation

In the financial services industry, analysts need to switch between structured data (such as time-series pricing information), unstructured text (such as SEC filings and analyst reports), and audio/visual content (earnings calls and presentations). Each format requires different analytical approaches and specialized tools, creating workflow inefficiencies. Add on top of this the intense time pressure resulting

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A generative AI prototype with Amazon Bedrock transforms life sciences and the genome analysis process

It takes biopharma companies over 10 years, at a cost of over $2 billion and with a failure rate of over 90%, to deliver a new drug to patients. The Market to Molecule (M2M) value stream process, which biopharma companies must apply to bring new drugs to patients, is resource-intensive, lengthy, and highly risky. Nine

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