Deep learning, a subset of machine learning, uses a web of artificial neural networks to process unstructured data
The term deep learning is often used when talking about neural learning or artificial neural networks and artificial intelligence. It is a subset of machine learning.
Artificial neural networks are a set of algorithms inspired by the human brain designed to recognize patterns. These neural networks use examples to “learn” to perform tasks instead of being programmed to do them.
Deep learning occurs when you have a web of artificial neural networks interconnected. Instead of analyzing data in a linear format, deep learning processes analyze unstructured and unlabeled data in a nonlinear way, much like the human brain.
While neural networks are “like” the human brain, in many ways, they surpass humans. We are only able to process so many things at once. This limit is why we have problems such as distracted driving. Self-driving car companies are betting on deep learning to eliminate that problem.
Sensors on a self-driving car collect data points from the environment. Then deep learning and artificial intelligence immediately get to work, processing more data than a human brain could ever hope to manage. The car can quickly recognize a stop sign or traffic signal, but that’s easy. When it sees a human, its interconnected neural networks quickly go about analyzing what they are seeing and sift through trends. Is it likely the person at the crosswalk will wait for an all-clear? Or perhaps that child with the ball will run into traffic?
Construction sites are one key place for deep learning, and where AI can have a significant impact. One way deep learning is implemented in construction sites is through its alliance with risk management, the management of schedules and subcontractors, safety, and site monitoring, among others.
For example, deep learning can use input from cameras on the job site, as well as drone images, and photos snapped by smartphones to scan for potential safety issues and prioritize those issues based on likely outcomes. Not only would it alert safety managers in areas where to focus training efforts, but it could potentially prevent a fatality.
Health and safety is a critical factor for achieving operational excellence. This is why we continuously strive to create risk-free workplaces for everyone and one of the many reasons our Digital Hub is studying deep learning to find ways to improve operations on all of our projects around the globe.