What Is Machine Intelligence?

Machine intelligence (MI) is like the weather in San Francisco: it's unpredictable. There are two main types of MI: Machine Learning and Deep Learning. Machine learning algorithms are trained on a set of existing data to find patterns that can be used to make predictions. In contrast, deep learning algorithms are trained on multiple layers of hierarchical features that combine to form a single output. ML and DL are used in many industries, including healthcare, manufacturing, finance, retail, etc. If you're a business-to-business (B2B) marketer, you've probably heard the term "machine learning" thrown around a lot. If you're not a B2B marketer, here's the short version: Machine learning is artificial intelligence (AI) that allows computers to learn from data without being programmed. This is important because it will enable companies to use big data more effectively. For example, suppose your company sells products to other businesses and has access to their purchasing history. In that case, machine learning can help you predict what products they'll be interested in buying next—and ensure that the product is ready for them when they want it. In addition, many IT vendors are now offering "machine learning as a service" (MLaaS). This means they're providing software programs that help businesses use machine learning on their behalf. Machine intelligence is a machine's ability to learn, act and make decisions autonomously. That is, the machine can learn through its own experience or via the experiences of other machines, or it can be programmed to use algorithms to make its own decisions based on data it has collected. To illustrate, imagine a robot in a factory tasked with welding parts together to do this task. Well, the robot must learn how to perform the task? What angle to weld at? What pressure to apply when welding and so on? This information can be taught directly by humans or gathered from other robots who have performed similar tasks successfully. Once these processes are learned and stored by the robot's memory bank (or "brain"), they can be used for future tasks without needing to be taught each time again.