For as long as AI technology has been a part of the larger tech narrative, fear has also been a part of that conversation. Part of that is simply the common, ever-present fear of the unknown — 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, contrary to those existing fears, 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 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.
In fact, AI is already all around us. One of the biggest tech stories of the past year was about AI: self-driving cars. We also see AI making itself known in healthcare settings, the finance industry, retail spaces, and of course, in social media. Here are a few simple and recognizable examples of the ways people already use AI daily: customer service chatbots, our friends Siri and Alexa, and shipping logistics.
AI models are also readily available from multiple sources, the key 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. So how can the business world use AI technology to help streamline workflows and strengthen results?
One very applicable example lies with forensic video analytics. Video data is one of the largest categories of data growth globally, and as such, 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.
AI was not developed by accident, but rather as a key piece of technology integral to the progress of humanity. AI was crafted intentionally and carefully, like all tools meant to propel us to the next level, and tools we take for granted were scary when they were first invented. Take fire, which is arguably the most important tool humans created — fire is scary when left unattended. Like fire, though, AI does not operate without human oversight but rather with careful cultivation to augment and improve the capacity of human work.
AI requires training, and that’s what makes the possibilities it holds as a tool endless. Training AI might seem like a vague and difficult task, but it’s fairly straightforward: to train your AI, 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, and though it may fail or be incomplete at first, it will strengthen over time with more and more learning and data.
With our example 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. To train your AI for this 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 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.
Plamen Minev is technical director, AI and cloud at Quantum.
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For as long as AI technology has been a part of the larger tech narrative, fear has also been a part of that conversation. Part of that is simply the common, ever-present fear of the unknown — 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, contrary to those existing fears, 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 is already all around us
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.
In fact, AI is already all around us. One of the biggest tech stories of the past year was about AI: self-driving cars. We also see AI making itself known in healthcare settings, the finance industry, retail spaces, and of course, in social media. Here are a few simple and recognizable examples of the ways people already use AI daily: customer service chatbots, our friends Siri and Alexa, and shipping logistics.
AI models are also readily available from multiple sources, the key 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. So how can the business world use AI technology to help streamline workflows and strengthen results?
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AI for business: A carefully cultivated tool
One very applicable example lies with forensic video analytics. Video data is one of the largest categories of data growth globally, and as such, 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.
AI was not developed by accident, but rather as a key piece of technology integral to the progress of humanity. AI was crafted intentionally and carefully, like all tools meant to propel us to the next level, and tools we take for granted were scary when they were first invented. Take fire, which is arguably the most important tool humans created — fire is scary when left unattended. Like fire, though, AI does not operate without human oversight but rather with careful cultivation to augment and improve the capacity of human work.
AI requires training, and that’s what makes the possibilities it holds as a tool endless. Training AI might seem like a vague and difficult task, but it’s fairly straightforward: to train your AI, 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, and though it may fail or be incomplete at first, it will strengthen over time with more and more learning and data.
With our example 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. To train your AI for this 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 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.
Beyond the fear of the unknown
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.
Plamen Minev is technical director, AI and cloud at Quantum.
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Author: Plamen Minev, Quantum
Source: Venturebeat