Task automation that frees people up for complex thinking

Here come the robots! The truth is AI isn't here to take away jobs — but to assist humans in undertaking very specific tasks, more efficiently and effectively than we ever could.

Task automation is key to freeing up the potential of your resources. AI and deep learning can automate many tasks and processes across almost any industry or business. Where there are repetitive and manual tasks, there is the potential to improve efficiency and accuracy and free up resources to focus on higher-value areas.

An elevated level of quality and efficiency, thanks to task automation

Key tasks for automation include the ability to enhance quality control across a range of applications — including solar-panel status, road conditions and manufacturing floors — by automatically detecting flaws, abnormalities or outright failures from image or video data. With automated and continuous monitoring, you can achieve an elevated level of quality.

Automation is also ideal for field inspections, particularly where manual inspections are risky, expensive or just ineffective. For example, bridge inspections can be done using drones equipped with cameras and a deep learning model that is able to detect rust or large cracks from images of the structure. Robots can automate routine tasks in a predictable and structured environment, running large operations at scale.

I think one of the most interesting things about automation isn't on the practical side. I think it's about creating magic and wonder and moments of splendor.

Genevieve Bell

AI can also help automate inventory processes that have typically been fraught with error, reducing the gap between data and physical inventory. Applications for logistics management include the ability to scan, sort and place parcels automatically.

Any time repetitive manual tasks can be automated, it saves human time for more complex thinking and reduces bias as well. For instance, the insurance claims process is an area that stands to benefit enormously from automation. Insurance companies can automatically classify damages seen in an image of a car to reduce the bias and increase the time it currently takes claim handlers to process.

Get more insight into how Peltarion supports task automation

The Peltarion Platform supports deep learning methods and replicates groundbreaking research results, while enabling non-experts to both apply and better understand the deep learning process. To gain more insight into how Peltarion can help with task automation, try our tutorial Classifying car damages, which lets you get hands-on with a pretrained snippet in a classification model designed to detect different types of car damages.

02/ Read about industries using task automation