CKE, or Cognitive Knowledge Engine, is a tool for creating AI models that can be integrated into existing systems. It allows users to easily build knowledge graphs and train them using advanced algorithms. For example, CKE takes the form of an API with several SDKs available (Python, Java) and CLI tools that work on Linux and macOS.
Perhaps you’ve heard of the term “knowledge graph” before but aren’t exactly sure what it means or how it’s used in the world of machine learning and artificial intelligence (AI). That’s okay! Here take a look at what a knowledge graph is and how you use it in your everyday lives so that you’ll have more context when discussing CKE with others who are also interested in these topics.
What is CKE?
CKE is a general-purpose programming language, which means it can be used to develop applications of any kind. It’s also stack-based, meaning the program data and instructions are stored in a data structure called the stack. So the last quality you’ll look at—imperative programming—comes from how variables are handled in CKE.
Imperative languages define their values explicitly rather than relying on their value being implicit by the program’s structure (as functional languages do).
Because CKE uses stacks to store its values and programs, it’s also a stack-oriented language. “With Sutherland’s Cognitive Knowledge Engine, turn your self-service into first-class service.”
How does it integrate with AI?
CKE is a framework that allows AI to be integrated into existing applications, including websites and mobile apps. It can also be used in conjunction with a number of different programming languages, making it easy for developers to add artificial intelligence functionality to their projects.
CKE can be used to create AI-powered chatbots and assistants that respond to users in real-time over various platforms, including web browsers, mobile apps and voice assistants like Alexa or Siri. For example, you could use CKE as part of an ecommerce website where customers are able to order products using natural language instead of having to go through several levels of menus or fields in search results pages before they find what they’re looking for.
Where can you use CKE?
AI is a great example of how an organization can use CKE. In fact, it’s one of the most notable examples! AI relies on CKE to develop its models and algorithms that power its predictions and decisions. By adding in more data points to your dataset (which is what CKE does), you will make your algorithms more accurate at identifying patterns and making decisions based on those patterns.
Two main types of data scientists utilize CKE: those who build machine learning systems from scratch and those who use pre-built frameworks. The former group relies purely on their own understanding of math, while the latter uses canned algorithms provided by these frameworks, which makes their job much easier than having to write their own code from scratch every time they want to create something new out of thin air!
CKE is a programming language for AI. CKE is lightweight, open-source, and designed for AI and machine learning systems. It’s also easy to learn and use—a good choice for beginners. CKE might be just what you need if you’re looking for a way to crack into programming languages for artificial intelligence (or any other field).