Flipboard

APRIL 13, 2023

At AWS, we have played a key role in democratizing ML and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. AWS has the broadest and deepest portfolio of AI and ML services at all three layers of the stack.

AWS 182

AWS AI AI ML 182

AWS Machine Learning Blog

SEPTEMBER 19, 2023

Implementing a multi-modal agent with AWS consolidates key insights from diverse structured and unstructured data on a large scale. All this is achieved using AWS services, thereby increasing the financial analyst’s efficiency to analyze multi-modal financial data (text, speech, and tabular data) holistically.

AWS 118

AWS AI AI ML 118

AWS Machine Learning Blog

MARCH 14, 2024

We formulated a text-to-SQL approach where by a user’s natural language query is converted to a SQL statement using an LLM. The SQL is run by Amazon Athena to return the relevant data. Our final solution is a combination of these text-to-SQL and text-RAG approaches. The following table contains some example responses.

SQL 118

SQL AWS AI AI 118

AWS Machine Learning Blog

MARCH 8, 2023

In this post, you will learn how Marubeni is optimizing market decisions by using the broad set of AWS analytics and ML services, to build a robust and cost-effective Power Bid Optimization solution. AWS Step Functions to orchestrate both the data and ML pipelines. One function to consolidate and prepare the data for training.

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AWS Machine Learning Machine Learning Analytics 84

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

Database 158

Database AWS ETL SQL 158

AWS Machine Learning Blog

JUNE 26, 2024

This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. Analysts need to learn new tools and even some programming languages such as SQL (with different variations). Delete the S3 buckets created by AWS CloudFormation and then delete the CloudFormation stack.

AWS 118

AWS AI AI Database 118

IBM Journey to AI blog

JANUARY 10, 2023

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Figure 7 – Initial query using the historical data (2003 – 2018).

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Data Warehouse Data Analysis Data Analysis SQL 52