Get notified when Mark publishes

Receive a notification each time a new blog post is published. You will receive a confirmation email to approve your email. Unsubscribe anytime.

Mark Smith

Mark Smith

· 1 min read

AI can find a needle in a haystack

AI can find a needle in a haystack
Share

This post was originally published in 2023. Some details may have changed since then.

AI can find a needle in a haystack.

Here’s 3 examples:

1. Market Trend Analysis in Retail

AI can sift through vast consumer data to identify emerging market trends. A retail company could use it to pinpoint a sudden spike in demand for a specific product in a particular region, enabling them to adjust their supply chain and marketing strategy accordingly.

2. Predictive Maintenance in Manufacturing

AI analyzes equipment data to predict failures before they occur. For example, in an automotive factory, AI could detect subtle signs of wear in a crucial machine part, alerting maintenance teams to prevent costly production stoppages.

3. Healthcare Patient Risk Assessment

AI can analyze patient data to identify individuals at high risk for specific conditions. In a hospital setting, AI could examine patient records to flag those at imminent risk of cardiac events, allowing for preemptive care and potentially saving lives.

The ability to extract critical insights from extensive datasets, allows for more informed and timely decision-making.

Want to apply AI to your organization?

Get in touch to find out how I can help.

Mark Smith

Mark Smith

Principal AI Strategist · Microsoft MVP

Helping people build practical AI skill in the Intelligence Age.

Discussion

Comments

Loading the discussion for this post.

Loading

Leave a comment

Your email stays private. If it matches a Gravatar account, your public avatar can appear after the comment is approved.

Used only for reply notifications and optional Gravatar matching. Never displayed publicly.

Max 2000 characters0/2000

More from nz365guy

Artificial Intelligence

Building a DevOps team from AI agents on OpenCLAW

Ten AI agents, each owning a phase of the DevOps infinity loop, coordinated by an engineering-manager agent. How I built a development team that plans, builds, codes, tests, releases, deploys, operates, and monitors continuously.

· 15 min read
Artificial Intelligence

Hardening OpenCLAW on Azure after a live audit

A live audit of my OpenCLAW Azure VM found two critical gaps: no Azure-native VM backup and no Azure Monitor Agent. Here is what I fixed, what it cost, and what is still unproven.

· 13 min read
Artificial Intelligence

I found 268 plaintext secrets in my AI stack

Six weeks ago a security audit told me I had 268 plaintext secrets scattered across my AI agent platform. This week I closed out the migration that fixed it. Here is what I learned about credentials, AI agents, and the gap between what we build and what we secure.

· 15 min read