Would Artificial Intelligence by Any Other Name Smell as Sweet?: Terms You Should Know

There are a lot of new terms buzzing around the topic of AI. Let's look over a few of them.

Would Artificial Intelligence by Any Other Name Smell as Sweet?: Terms You Should Know

There are a lot of new terms buzzing around the topic of AI. Each one may take on a specific meaning with subtle differences or describe the research or specific type of AI, but nevertheless is covered under the umbrella term of AI or Artificial Intelligence. There are different levels of awareness or abilities:

  • Type I: Reactive Machines — As the name states, they are "reactive" only. They have no ability to form memories or make informed decisions.
  • Type II: Limited Memory — These intelligent machines are able to form "limited memories." Think of an automated vehicle needing to observe and remember the behavior of vehicles around it.
  • Type III: Theory of Mind — These machines will be able to form understandings of the world around them, such as other machines, objects, animals, and humans.
  • Type IV: Self-Aware — In order for this stage of machine learning to come to fruition, humans would actually need to understand consciousness in sentient beings. This is obviously a long way down the road since we are only beginning to really study the functions of the brain in-depth.

OK, we now understand the different types of AI and we can safely say we are getting more comfortable with Types I & II. But, Types III & IV are still in the works and will be for quite some time. As the industry grows, there is no doubt that new categories and sub-categories will emerge. So, let's explore a few terms used to describe AI that you may come across while you're surfing the neural network innovation ocean (I am sure I have missed quite a few, though!):

  • Thinking Computer/Computational Thinking — The thought processes (comprising of four processes: decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design) involved in formulating a problem and figuring out the solution.
  • Neural Network — An interconnected group of nodes, similar to the connections of neurons in the brain.
  • Machine Learning — Uses statistics to teach a program how to "learn" from data, without having the solutions explicitly programmed into the system.
  • Deep Learning / Deep Structured Learning / Hierarchical Learning / Deep Neural Learning / Deep Neural Network — General term used to describe machine learning of unstructured data, as opposed to task-specific algorithms.
  • Intelligent Retrieval — Describes the process of pulling information stored in a database.
  • Electronic Brain / Artificial Brain / Artificial Mind — The software and hardware components that make up an AI network.
  • Cybernetics — The study of the structures that relate to communications and automatic control systems, both in machines and living organisms.
  • Strong AI — Used to describe the goal of getting AI to be as intelligent as a human.
  • Autonetics — Deals with the development and use of machines for automated control and guidance of devices.
  • Natural Language Processing (NLP) / Natural Language Learning (NLL) / Natural Language Interpretation (NLI) — All of these terms deal with how machines learn to interact with us using natural human languages.
  • Affective Computing / Artificial Emotional Intelligence (Emotion AI) — This describes how machines can learn from and interact with human emotions.
  • Expert Systems / Cognitive Expert Advisor / Cognitive Computing — AI-based systems with expert knowledge that can perform tasks such as medical diagnosis or stock trading. Operates primarily on "If-Then" algorithms.
  • Virtual Personal Assistant / Digital Assistant — Although this can refer to a human working remotely as a personal assistant, for the purposes of this article, think more along the lines of Alexa and Google Home.
  • Knowledge Engineering / Knowledge-Based Systems — A knowledge engineer is responsible for building the framework for knowledge-based systems.
  • Synthetic Intelligence / Artificial General Intelligence (AGI) / General Purpose Machine Intelligence — A general term to describe AI, but places a heavier emphasis on the AI not actually being "artificial," an honestly true and pure form of intelligence.
  • Weak/Narrow AI — AI built to focus on one specific, narrow area. Does not demonstrate broad knowledge into other areas.
  • Super Intelligence — Refers to AI that has intelligence that is far superior to humans. This is often the basis of many dystopian future sci-fi stories, where AI enslaves humanity.
  • Technological Singularity -—The proverbial point in AI development where AI will "explode" and accelerate technological advancement that will dramatically change the way humans live.
  • Artificial / Machine / Synthetic Consciousness — Another way of saying Artificial Intelligence.
  • Brain-Machine Interface (BMI)/ Brain-Computer Interface (BCI)/ Mind-Machine Interface (MMI)/ Direct-Neural Interface (DNI)/ Neural-Control Interface (NCI) — Not to be confused with AI terminology. These terms refer to machines that are directly interacting with a living brain, and receiving input from the brain (human or animal). I only added them to highlight the distinction.

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