Artificial Intelligence (AI) has made a splash in recent years for its ability to disrupt virtually any industry by removing human error with computer-performed tasks.
Within the field of AI, various subtopics and buzzwords can muddy the water. To remedy this, we’ve broken down one facet, deep learning, and its effect on business security.
What is Deep Learning?
AI is characterized in part by machine learning. Machine learning is the science of making computers “smarter.” As Tech Emergence puts it, “Getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion by feeding them data and information…”
Deep learning, then, is a specialized technique of machine learning in which computers learn by example. Computers analyze labeled data, pass that data through a neural network, and then use the output to make decisions and predictions about other data.
Deep learning is used to improve technologies, such as self-driving cars and Netflix show recommendations. But, it can also be used to improve business security.
Deep Learning in Business Security
One of the top uses for deep learning in business security is to analyze video security footage. In most cases, 98% of security footage is never seen by anyone. Due to the sheer volume of most businesses’ video footage and the chance of human error, important incidents can be missed–or false alarms reported.
Deep learning offers a solution to these video surveillance analytics problems by training computers to spot certain factors within recorded video. Benefits include:
- Face recognition and object detection. Once computers access deep learning processes to learn what a person’s face looks like, they can identify faces with extreme accuracy, just like Facebook identifies people in photos you upload. Furthermore, the computers can learn to identify certain objects–like the form of a person–within a video.
- Accuracy. The more labeled data computers can process, the more accurate the deep learning. Humans, on the other hand, are always prone to human error.
- Fewer false alarms. Thanks to deep learning, computers can be better equipped to identify when something is out of place and flag it for human review, a process that takes humans far longer and opens the doors to more error.
Video Surveillance with Deep Learning Has Drawbacks
The most substantial challenge of deep learning is the large amount of labeled video footage needed to teach machines the skills mentioned above.
And, because deep learning is a relatively new phenomenon in the business security space, it could be some time before the necessary talent and resources are allocated to improving video analytics.
In the meantime, expect deep learning to continue making strides across industries, and read AI business security news so you’re ready to implement the latest technology.