Artificial Intelligence (AI) is no longer the buzzword that gets marketers excited. These days, the ad-tech community is rather more interested in Machine Learning (ML) — as you’ve probably noticed. So what’s the difference?
In broad terms, AI is the process of a computer “learning to learn”, so that it can complete a given task faster and more efficiently than humans. ML, on the other hand, involves special purpose machines designed to solve a specific problem by learning from a structured data set. In this article, we take a closer look at both approaches and how they differ.
A typical AI system learns by iteration. It begins with little or no prior knowledge of its environment. In every interaction with the outside world, the AI gathers feedback and adjusts its course of action. Over time, as the system learns more about its environment, it becomes proficient at its given task. Soon enough, the AI can outperform its human counterparts.
This kind of AI system is equipped with a set of tools for exploring the environment, discovering the challenges, and analyzing possible solutions. Once the AI has performed an action, it can evaluate the consequences and adjust its plan accordingly. Analogous to the central nervous system in a human body, the AI takes input from a wide range of sensory organs and uses this information to guide its decision making.
At Simplaex, our core AI uses a Bayesian decision system to evaluate its options and make the smartest choice. The AI works under constantly changing conditions, monitoring user behavior in real time while minimizing its exploration costs. Ours is just one of many applications for AI. In the past decade, this technology has given us AlphaGo, IBM Watson, and autonomous cars.
An ML system is designed to extract critical insights from vast troves of data. Once the desired information has been collected and properly structured, it can be used to guide decisions, or it can be fed into another AI algorithm in a process called Transfer Learning.
You may not realize it, but you use ML systems every day. Combined with statistical analytics, ML has delivered remarkable progress in such fields as automatic speech recognition, predictive text, web search, content recommendations – even our understanding of the human genome.
What Does This Mean for App Retargeting?
As we’ve written before, the application of AI to App-Retargeting progressively brings incredible value and precision to a campaign. Using machine learning to extract essential information from huge data sets, learning user preferences and discovering behavioural patterns creates a level of efficiency and specificity which humans alone can’t compete with.
At Simplaex, we augment our human creativity and as well as our autonomous systems with machine learning to provide the best solutions for our clients looking for a personalized and precise marketing campaign.