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How AI Software is Changing the Future of the Automotive Industry

Smart Data Collective

Artificial intelligence technology is changing the future of many industries. The automotive industry is among those investing in AI the most. The automotive industry is among those investing in AI the most. The industry is going to increase expenditures on AI technology for the foreseeable future.

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Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation

Flipboard

A typical RAG solution for knowledge retrieval from documents uses an embeddings model to convert the data from the data sources to embeddings and stores these embeddings in a vector database. In this post, we demonstrate how to use Amazon SageMaker Studio to build a RAG question answering solution. embeddings.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning Blog

However, when building generative AI applications, you can use an alternative solution that allows for the dynamic incorporation of external knowledge and allows you to control the information used for generation without the need to fine-tune your existing foundational model. Before you get started with the solution, create an AWS account.

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IBM Cloud delivers enterprise sovereign cloud capabilities

IBM Journey to AI blog

As we see enterprises increasingly face geographic requirements around sovereignty, IBM Cloud® is committed to helping clients navigate beyond the complexity so they can drive true transformation with innovative hybrid cloud technologies. We believe this is particularly important with the rise of generative AI.

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Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning Blog

We describe how the solution and Amazon Bedrock consumption plans map to the general SaaS journey framework. The code for the solution and an AWS Cloud Development Kit (AWS CDK) template is available in the GitHub repository. For simplicity, we do not include these in this solution.

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Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model

AWS Machine Learning Blog

For example, in the financial services industry, applications include extracting insights from earnings reports, searching for information from financial statements, and analyzing sentiment about stocks and markets found in financial news. They provide ease of use and strong security and privacy controls.

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Meet the winners of the Research Rovers: AI Research Assistants for NASA Challenge

DrivenData Labs

Results ¶ For their final submission, participants provided a 5-10 minute video demonstration and short writeup describing their solution and its potential for assisting NASA researchers in their work. Paper recommendations from Google Scholar, arXiv and PubMed in the 1st place winners solution (NASAPalooza). bge-small-en-v1.5

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