AI technology has been a part of the larger tech narrative, and fear has also been a part of that conversation. One of the biggest reasons for this fear is the unknown as we don’t know exactly what implications this tech will have in the long run, and most people don’t understand what the tech is capable of. However, AI was never intended to be something to fear or to be a replacement for human work but rather was created to be a tool meant to augment humans in all aspects of life, from work to home and everywhere in between.
AI as a Tool
AI was developed to serve each industry (and each individual) in order to maximize results, reallocate existing resources, and, ultimately, increase efficiency for all. As businesses move to adopt AI models, it will help streamline workflows and allow us to do more, even when resources are tight. In addition, with the skilled tech worker shortage remaining a pertinent issue, AI is more critical than ever. What’s important to know is that with the massive strides made in AI capabilities, technical professionals can “train” your AI to work better to solve and serve your unique business challenges.
AI models are already being used in different sectors such as self-driving cars, healthcare settings, the finance industry, retail spaces, and social media. Some simple and recognizable examples of the ways people already use AI daily include customer service chatbots, Siri, and Alexa, and shipping logistics. The key to using AI models is to find one that works and that applies best to your business needs. Once you’ve located the model that works best for you, then you train it to specifically augment your business.
Training AI
Training AI is a straightforward process where you’re teaching it how to interpret data and what you want it to learn from that data. This won’t happen instantly but rather follows the pattern of all learning. Though it may fail or be incomplete at first, it will strengthen over time with more and more learning and data.
One very applicable example of using AI technology to help streamline workflows and strengthen results lies with forensic video analytics. Video data is one of the largest categories of data growth globally, and it would take a person countless hours to go through video footage and document everything of importance, whether it’s being used for security, loss prevention, or other business needs. However, going through video data takes AI a fraction of the time, not as a replacement for that human, but as a tool for us to use so we aren’t wasting our precious time on a menial task.
To train your AI for a specific task, you’ll show it the type of data it’s interpreting and then tell it what you want it to do with that data. In the case of video forensics, there’s a difference between simply having AI sift through footage and having AI intentionally sift through footage with a goal in mind, like asking it to find all the blue cars in video footage of your parking lot. In this case, you may just be asking it to document every time a blue car appears, but down the road, you can have it instantly notify you, set off an alarm, or otherwise communicate seeing a blue car.
The fear of AI is largely due to misrepresentation and misunderstanding, which isn’t uncommon when it comes to new technology. However, AI has been around for years, whether we see and realize it or not, which means we already use and trust AI. Finding the AI model that works for your business and training it to do tasks that augment your human staff and improve your products and services will become more important as the technology becomes more prevalent across all industries. AI was not developed by accident, but rather as a key piece of technology integral to the progress of humanity. AI requires training, and that’s what makes the possibilities it holds as a tool endless.
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