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Harness the Power of Pinecone with Cloudera’s New Applied Machine Learning Prototype

Cloudera

This AMP is built on the foundation of one of our previous AMP s, with the additional enhancement of enabling customers to create a knowledge base from data on their own website using Cloudera DataFlow (CDF) and then augment questions to the chatbot from that same knowledge base in Pinecone.

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Accelerating Cost Reduction: AI Making an Impact on Financial Services

Cloudera

Historically, firms have relied on high-cost, third-party solutions to help identify savings opportunities, however, the landscape is rapidly changing, and the emergence of AI and machine learning (ML) has ushered in a new era of possibilities. Quickest wins!

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Incorporate offline and online human – machine workflows into your generative AI applications on AWS

AWS Machine Learning - AI

Recent advances in artificial intelligence have led to the emergence of generative AI that can produce human-like novel content such as images, text, and audio. An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF).

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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning - AI

In part 1 of this blog series, we discussed how a large language model (LLM) available on Amazon SageMaker JumpStart can be fine-tuned for the task of radiology report impression generation. You can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

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Best practices to build generative AI applications on AWS

AWS Machine Learning - AI

Generative AI applications driven by foundational models (FMs) are enabling organizations with significant business value in customer experience, productivity, process optimization, and innovations. In this post, we explore different approaches you can take when building applications that use generative AI.

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Announcing Cloudera’s Enterprise Artificial Intelligence Partnership Ecosystem

Cloudera

In a stack including Cloudera Data Platform the applications and underlying models can also be deployed from the data management platform via Cloudera Machine Learning. Customers can quickly and easily build generative AI applications using these new features available in Cloudera.

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Deploy foundation models with Amazon SageMaker, iterate and monitor with TruEra

AWS Machine Learning - AI

This blog is co-written with Josh Reini, Shayak Sen and Anupam Datta from TruEra Amazon SageMaker JumpStart provides a variety of pretrained foundation models such as Llama-2 and Mistal 7B that can be quickly deployed to an endpoint. Vivek Gangasani is a AI/ML Startup Solutions Architect for Generative AI startups at AWS.