In this episode, we explore how TileDB, an innovative data system originally developed at MIT and Intel Labs, is revolutionizing healthcare and life sciences data management. We'll dive deep into how TileDB's universal data engine efficiently handles complex scientific data - from genomic sequences to medical imaging - in a unified format, and learn how healthcare organizations can leverage TileDB on AWS to accelerate research, improve collaboration, and reduce infrastructure costs. Join host AWS Solutions Architect for HCLS Gokhul Srinivasan and guest Devika Garg form TileDB as they discuss real-world applications in precision medicine, genomic analysis, and how TileDB is transforming the way healthcare providers manage and analyze patient data.

To Learn More:

https://www.tiledb.com/

AWS Hosts: Nolan Chen & Gokhul Srinivasan

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AI can still sometimes hallucinate and give less than optimal answers. To address this, we are joined by Arize AI’s Co-Founder a Aparna Dhinakaran for a discussion on Observability and Evaluation for AI. We begin by discussing the challenges AI Observability and Evaluation. For example, how does “LLM as a Judge” work? We conclude with some valuable advice from Aparna for first time entrepreneurs.

Begin Observing and Evaluating your AI Applications with Open Source Phoenix:

https://phoenix.arize.com/

AWS Hosts: Nolan Chen & Malini Chatterjee

Email Your Feedback: rethinkpodcast@amazon.com

In this episode we are going to discuss Model Context Protocol (MCP) in context of Agentic architecture with Mona - Gen AI Specialist Solutions Architect at AWS.

We will cover the challenges of implementing Agents and how MCP can help. We will try to simplify it with an example of MCP with Agents and further delve deep into LangGraph adapters such as FastMCP and FastAPI.

You will also learn about implementing MCP architecture on AWS.

Apart from her daily job, Mona has published two books Natural Language Processing with AWS AI Services: Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend and Google Cloud Certified Professional Machine Learning Study Guide. She has authored multiple on AI/ML and cloud technology and a co-author on a research paper on CORD19 Neural Search. She is also a frequent speaker at multiple conferences such as ISMB 2022, AWS Re:Invent.

Links https://www.amazon.com/Natural-Language-Processing-AWS-Services/dp/1801812535

https://a.co/d/7rlkZwn

Blog - Implement MCP in SageMaker AI https://aws.amazon.com/blogs/machine-learning/extend-large-language-models-powered-by-amazon-sagemaker-ai-using-model-context-protocol/

Blog - Implement MCP with Bedrock Agents https://aws.amazon.com/blogs/machine-learning/harness-the-power-of-mcp-servers-with-amazon-bedrock-agents/

AWS Hosts: Nolan Chen & Malini Chatterjee

Email Your Feedback: rethinkpodcast@amazon.com

Join Jobi George and Tony Le from Weaviate as we discuss how their AI Native Vector Database is powering modern AI applications. We begin with an intro to Vector Databases followed by common use cases, and how they fit into Agentic Workflows. We also talk about the advantages of using an AI Native Database from the Open Source community.

To learn more:

Website - www.weaviate.io

Linkedin - https://www.linkedin.com/company/weaviate-io/

AWS Marketplace - https://aws.amazon.com/marketplace/seller-profile?id=seller-jxgfug62rvpxs

Developer Community - https://weaviate.io/developers/weaviate/model-providers/aws

Instagram - https://www.instagram.com/weaviate.io/

Youtube - https://www.youtube.com/@Weaviate

AWS Hosts: Nolan Chen & Malini Chatterjee

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Join Julien Simon, Chief Evangelist of Arcee AI, as we discuss how Model Merging can help us build more versatile and cost effective AI models. Hear him explain the different methods for Model Merging while comparing it with other techniques for building better models such as Model Distillation and Transfer Learning.

To learn more about Model Merging:

Arcee AI Website

https://arcee.ai

Arcee’s MergeKit: A Toolkit for Merging Large Language Models

https://arxiv.org/abs/2403.13257

Deep dive: model merging on YouTube:

https://youtu.be/cvOpX75Kz4M?si=nT2U7Fe8oLNRSy0u

Try MergeKit:

https://github.com/arcee-ai/mergekit

AWS Hosts: Nolan Chen & Malini Chatterjee

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Your AI is only as good as the data its trained on. In this episode we talk to Krishna Subramaniam, Co-Founder and President of Komprise, a provider of intelligent Data Management. We discuss both the importance and challenge of unlocking the value unstructured data for AI pipelines.

For more info on Komprise’s Intelligent Data Management Platform:

www.komprise.com

AWS Hosts: Nolan Chen & Malini Chatterjee

Email Your Feedback: rethinkpodcast@amazon.com

"2025 is the year of inference." Todd Pond, AWS Director of Strategic Sales, is out in the field with commercial customers every day, helping them leverage technology to solve their biggest problems, accelerate innovation and transform their businesses with AI. He and his team have a deep understanding of these companies - the challenges they're up against, their limited resources, their unique value propositions, and how to enable their growth with maximum ROI. In this episode, we are happy to have Todd back again to discuss what were the 2024 trends, what were the pleasant surprises, his actionable insights and some recipe for success in 2025 and beyond.

Join AWS Head of AI and Modern Data Strategy Business Development Ben Schreiner for a recap of re:Invent 2024. Ben share his top 5 themes from the conference as well as what surprised him in 2024 and what he thinks lies ahead in tech in 2025.

AWS Hosts: Nolan Chen & Malini Chatterjee

Top Announcements from re:Invent 2024:

https://aws.amazon.com/blogs/aws/top-announcements-of-aws-reinvent-2024/

https://aws.amazon.com/blogs/machine-learning/aws-reinvent-2024-highlights-top-takeaways-from-swami-sivasubramanian-to-help-customers-manage-generative-ai-at-scale/

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