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Taking a Data-Driven and Model-Driven Approach to AI

Taking a Data-Driven and Model-Driven Approach to AI

Taking the first step toward more data-centric AI is as simple as recognizing the immense value your data holds and the value inherent in curating it carefully. But centralizing and systematizing your approach to AI isn’t enough—nor is it enough to focus on updating and testing the models you deploy at the expense of data quality. Even better than a data-centric approach to AI is a data-driven approach, one that focuses on both the quality of the data collected and the efficacy of the models this data is used to train.

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Vision AI for Fighting and Preventing Wildfires

Vision AI for Fighting and Preventing Wildfires

By enhancing their computer vision technology and applying AI to visual data like satellite imagery and drone feeds, public and private sector organizations can better recognize wildfire risks, predict the likely path of blazes, and coordinate their fire-fighting efforts to protect communities.

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Object Detection: An Introduction

Object Detection: An Introduction

Spotting relevant information in an image or video feed can feel a little like looking for a needle in a haystack, but it doesn’t have to require so much time and effort. Training AI to detect objects can help by streamlining and automating the process of generating insights from visual data.

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