Deep Learning is a technology that can be brought much closer to our everyday lives than conventional IT can. In fact, Deep Learning can predict human behaviour. Here is how.
Conventional IT systems are designed as math and logic-based tool. For them to work, they assume that mathematical formulas can describe the environment they are looking at. It is a useful approach if you develop spreadsheets or design a banking system.
But if you want to make services that interact with people on our terms. That is, speech, text, and visual communication than the mathematical problem-solving approach will give you problems.
Deep Learning is already technologically superior to all conventional IT systems in such areas. This is a core area that we will get back to later in the book.
Deep Learning can predict human intentions.
Deep Learning can be made so advanced it could make predictions about human intentions and rational behavior. Think about it and its significance. That’s a big deal. There are various examples in the book of how it would be practically possible to work with technology that way for you.
AI looks for patterns
The AI will look for significant patterns in how the customer behaves. The system will then make predictions based upon this knowledge. Such forecasts could include an expected output of your relationship with this customer. Such as how many visits you need before he buys from you. If you can make upsells or if he is sensitive to price or not.
This means that we can create a set-up where we are more knowledgeable of a specific customer’s buying preferences are than he is aware of himself. So we know more about how he will react to the meeting with us than he might have thought.
Your employees would thus be able to know which products the specific customer prefers without necessarily talking to the customer before.
This will change the premises for the level of customer service that you could provide. For example, your sales reps will be able to zoom in to your client’s needs quickly, and you will appear professional in the client’s eyes. Or maybe you could offer a digital sales experience that matched the level of service that personal sales could provide.
It is because of examples like this that some conceptually describe Deep Learning as systems with intuition. The system cannot explain why it thinks a given customer will be interested in a given product. However, if the system has enough data to learn, it will be able to predict a given customer’s behaviour with consistent accuracy.
So that AI can learn the meaning of behaviour, and make qualified proposals for actions based on the knowledge acquired is a big thing.
But before we open up to that talk, you need to understand the very central premise of why AI is fundamentally different from anything you’ve experienced in technical solutions before.
It starts a little abstract in the way we deal with knowledge in general. However, the description opens up the understanding of the most central AI characteristic, namely that AI automates the processing of knowledge.
Knowledge can be described hierarchically in levels as a pyramid, and it helps to understand what AI can do for us.