Artificial intelligence can be seen in various applications all over the world, but generally, these can all be divided into three very loose categories: Transformative AI, DIY (Do It Yourself) AI, and Faux AI. While the latter two are the most common of them, according to experts it’s transformative AI that holds the most potential.
AI applications that are used on a daily basis are primarily aimed at the accessing and processing of data. For example, Alexa will turn on your music, give you a rundown of what’s happening in your day ahead, while advising on the weather outside. But these are all relatively simple tasks, and nothing too dramatic that will change the world anytime soon.
Transformative AI, on the other hand, is different as this transforms data insights into real instructions that the AI proceeds to carry out. The most obvious example of this type of AI is the self-driving car. In this type of technology, the AI must be able to absorb all the information that’s presented to it, make a decision based upon what it sees, and act just a human would. But, this is just one example of transformative AI and as more people learn about the great benefits of it and how to adapt it to best suit their needs it will become a lot more popular.
But for now, most of the changes that we will see in AI will be relating to DIY or Faux AI. DIY AI basically includes any AI platform that allows the user to become more informed and educated so that they can better perform the task themselves. This type of AI can be extremely useful in companies that have large amounts of data in which to process and analyze. One such example is a DIY AI is Salesforce’s, Einstein. This AI “qualifies leads, predicts when customers are ready to buy, and helps close more deals,” according to the company. DIY AI is often a bolt-on application that’s added to existing technology and not usually a stand-alone AI driven product.
Last but not least we have Faux AI. This type of AI involves AI that pretends to be something it’s not. Unfortunately, while the general society is still finding their feet when it comes to AI, some companies are taking advantage of this and labeling things incorrectly. For example, often companies are re-labeling their predictive and automation technologies as AI when really they aren’t AI based at all. There’s also some chatbots that may look and sound like they’re AI, but again, they’re just fakes and aren’t using any machine learning at all.
Just as most other things in this world today, AI is evolving all the time. Some of the better, more robust AI out there currently is “Transformative AI in training,” so it won’t be long before we see more of these applications appearing all over and hopefully changing the world for the better. But for that, only time will tell.
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