Forget the Models, Your Data is the Secret Sauce for Generative AI

Generative AI holds immense potential for businesses, but its success depends on the quality of your data. High-quality, strategically managed data is essential for building trustworthy, unique, and competitive AI applications. This article explores how AI leverages your data through embeddings, outlines best practices for data management, and emphasizes the importance of responsible AI development. By prioritizing data quality and effective management, you'll position your business to reap the full benefits of Generative AI and drive innovation.

Machine learning K-Means applied to SQL Server data

This article shows how to use Python to access data in SQL Server and produce a K-Means analysis with a chart.

A Great Use for AI

Steve found a great use for AI, and one many people might appreciate.

Training a Random Forest Model

Lots of Data and AI Helping Firefighters

Using AI/ML to help process large amounts of data allows us to tackle problems that we might not otherwise be able to work on.

Model Selection and Performance Boosting with k-Fold Cross Validation and XGBoost

This article examines how to split a data set for training and testing and evaluating our model using Python.

Finding Legal Data

Using data scraped from the web might be convenient, but is it legal. Perhaps more importantly, is it moral? Steve has a few thoughts.

Using Data Science And Machine Learning In Identifying Fraudulent Activities

A look at one way to detect fraud using R and a machine learning model.

AI Can Improve Healthcare

One area where AI has found some traction is in the healthcare industry, where is seems to be helping improve care.

The Computing Revolution

Steve reflects on some of the ideas of how Microsoft imagines the future of computing.