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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Flipboard

Recent advances in generative AI have led to the rapid evolution of natural language to SQL (NL2SQL) technology, which uses pre-trained large language models (LLMs) and natural language to generate database queries in the moment.

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Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning Blog

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. By setting up automated policy enforcement and checks, you can achieve cost optimization across your machine learning (ML) environment.

ML 109
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AWS at Databricks Data + AI Summit 2025

databricks

AWS’ Legendary Presence at DAIS: Customer Speakers, Featured Breakouts, and Live Demos! Amazon Web Services (AWS) returns as a Legend Sponsor at Data + AI Summit 2025 , the premier global event for data, analytics, and AI.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning Blog

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. These components are illustrated in the following diagram.

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Introduction to BigQuery ML

Analytics Vidhya

The post Introduction to BigQuery ML appeared first on Analytics Vidhya. These webinars are hosted by top industry experts and they teach and democratize data science knowledge. Here is the knowledge session by Shanthababu Pandian […].

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HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

AWS Machine Learning Blog

Powered by generative AI services on AWS and large language models (LLMs) multi-modal capabilities, HCLTechs AutoWise Companion provides a seamless and impactful experience. This seamless process is facilitated by Retrieval Augmentation Generation (RAG) and a text-to-SQL framework.

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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Basic knowledge of a SQL query editor.