The following is an excerpt from our Enriching Data, Empowering Action whitepaper. You can access the full report here.
What Is Artificial Intelligence?
While there’s some debate over the exact definition, AI can be thought of as smart machines performing tasks that a human has to apply intelligence to perform. These might involve planning, problem solving, or manipulation.
When Siri gives you driving directions, your favorite online store suggests a product you might like to buy, or you get a text from your bank that they detected a fraudulent charge—AI is at work.
What Is Machine Learning?
ML is a subset of AI. ML is the process of feeding data to a machine and letting the machine learn how to accomplish that task. As the algorithms adapt to new data, they’re able to learn through experience and eventually make predictions or decisions.
For example, some grocery stores are now using ML to develop touch-free self-checkout stations. Data engineers train the model with images of, for example, oranges until the ML can recognize an orange when a customer puts one on a scale. The model becomes more and more accurate as more data is fed into it in real-world use.
How Do AI and ML Work Together in PrecisionAnalytics?
To train the model, the team annotates images of blown fuses and feeds them into the model so it learns how to identify blown fuses on different backgrounds, in varying types of light, and from different angles.
Over time, the data engineer will be able to input any image and the model will be able to tell them if the image contains a blown fuse. The model continues to refine its abilities as more data is fed into it in real-life situations.
The bottom line: by deploying PrecisionHawk’s data solution, enterprises can improve every step of their inspection process—from collecting data to deploying repair crews.
Download the full Enriching Data, Empowering Action whitepaper today to learn how data-powered decision-making can help you reduce downtime, increase safety, and lower costs.