AI/ML 101.0: a quick background on AI/ML

The introduction of artificial intelligence (AI) and machine learning (ML) (we will explain the difference below) has and will continue to change the world as we know it. Being on the forefront of this change can be exciting as AI/ML development offers limitless possibilities in creativity and innovation. Traditionally, AI has come with a high barrier to entry. However, our goal is to make AI accessible to developers, even those with no prior AI/ML experience. We will explain what AI/ML is used for and how it can impact your life.

AI is the engineering and science of making machines that can understand human intelligence with the goal of making computer programs smart enough to mimic human behavior. Machine learning is a subset of AI that builds algorithms to train machines how to learn from past data to predict future events. The more data that AI/ML algorithms collect, the more accurate it will be in predicting the future or performing better than a human can at a specific task.

Nearly all computerized learning and problem solving falls under the category of AI: machine learning, robotics, neural networks, language processing. AI of the future is portrayed as the super-human robots we see in film. Today’s AI is still in its infancy and can’t yet harness the power of science fiction robots; nevertheless, AI today is quite powerful.

There are two types of AI: narrow AI is programmed to solve a single task and general AI goes past what it is programmed to do by exhibiting human-like intelligence. All of the AI that exists today is narrow AI. Virtual assistants, vacuum robots, and automated language translators all function by processing a human input, executing a given task based on their algorithm, and delivering the desired output.

AI is built upon computer science, math, and engineering. Python is the most popular language for writing AI code as it offers a large library of open source modules that make building AI models easier and faster. Mathematically, AI is operated based on probability, linear algebra, calculus, and statistics.

Using these mathematical principles, developers input data into coded algorithms specifically created to execute a certain task. Like humans, machines need to learn from something. They learn by reading past data, estimating potential outcomes, fixing their mistakes, improving on the next prediction, and continuing this process until it’s done “training”. Once it’s done training, AI/ML models can be used to make predictions on future unseen data.

An example of how AI is used in our everyday lives is object detection. Developers first gather a large dataset of thousands of images, then uses it to train an AI model. The more data that is gathered, the better AI becomes in accurately classifying these images.

Apple and Google Photos use AI to sort pictures. When someone takes a photo of their cat, AI can quickly identify the image as a cat based on thousands of cat images it has already seen and classified. The user then has an automatically curated album of cat photos without ever having to sort through photos themselves. On a greater level, this software is being applied to medical devices to more accurately identify terminal disease at much earlier stages than could be done with the human eye.

Another AI algorithm that makes our lives easier is recommendation engines. Recommendation engines are integrated into a variety of platforms to allow the algorithm to feed users content they’re more likely to engage with. The more users interact with the platform, the more data the AI collects, and the more accurate it becomes.

In the same way a wand gives a wizard the power to access their magical ability,

gives developers the power to access the magic of AI.

is a tool that helps developers use AI and their data to make predictions.

Developers are using

to identify high value customers, predicting their customer’s lifetime value, and many other use cases. The possibilities of using

to apply AI are vast. Companies we serve range from health care, to fintech, to SaaS businesses, and beyond.

AI can improve the way individuals and businesses make decisions, operate, and interact with one another. As AI/ML integrates itself into nearly every aspect of life, we aim to make it accessible for developers who are building businesses and products for the world.