IBM Journey to AI blog

OCTOBER 30, 2024

The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets. The platform incorporates the innovative Prompt Lab tool, specifically engineered to streamline prompt engineering processes.

Prompt Engineering 238

Prompt Engineering Prompt Engineer ETL Machine Learning 238

AWS Machine Learning Blog

JUNE 25, 2024

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. Prerequisites This post is intended for developers with a basic understanding of LLM and prompt engineering. A prompt is natural language text describing the task that an AI should perform.

Automation 118

Automation Prompt Engineering Prompt Engineer Categorization 118

IBM Journey to AI blog

JULY 17, 2023

offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting. These Slate models are fine-tuned via Jupyter notebooks and APIs. To bridge the tuning gap, watsonx.ai

Machine Learning 186

Machine Learning Metadata Automation AI 186

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

Generative AI 122

Generative AI Prompt Engineering Prompt Engineer AI 122

AWS Machine Learning Blog

APRIL 16, 2024

You can use these connections for both source and target data, and even reuse the same connection across multiple crawlers or extract, transform, and load (ETL) jobs. Text to SQL: Using natural language to enhance query authoring SQL is a complex language that requires an understanding of databases, tables, syntaxes, and metadata.

Data Scientist 108

Data Scientist Generative AI Machine Learning Auto-complete 108

The MLOps Blog

AUGUST 3, 2023

At a high level, we are trying to make machine learning initiatives more human capital efficient by enabling teams to more easily get to production and maintain their model pipelines, ETLs, or workflows. We have someone from Adobe using it to help manage some prompt engineering work that they’re doing, for example.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

Flipboard

NOVEMBER 24, 2023

By analyzing millions of metadata elements and data flows, Iris could make intelligent suggestions to users, democratizing data integration and allowing even those without a deep technical background to create complex workflows. The example in the following prompt shows a fictitious schema that matches the expected output.

ETL 158

ETL Prompt Engineering Prompt Engineer Generative AI 158