Artificial intelligence (AI) is an interdisciplinary science with multiple approaches concerned with building varied kinds of smart machines capable of performing tasks that typically require human intelligence. Its advancements in machine learning and deep learning are shifting a paradigm in almost every sector of the tech industry.
Can machines think? – Alan Turing, Mechanical Intelligence: Collected Works of A.M. Turing (1950)
About 70 years ago, A.Turing asked this simple question and made a U-turn in history with his paper and Turing Test establishing the fundamentals and vision of AI. AI aims to answer Turing question affirmatively, as AI is a try to replicate (or simulate) human intelligence in machines.
The comprehensive goal of artificial intelligence raised a lot of questions and debates, insomuch that there is still no singular definition of the field universally accepted. The major limitation of defining AI as ‘building intelligent machines’ is that it doesn’t even explain what artificial intelligence is, and what makes a machine intelligent?
Jeremy Achin, the DataRobot CEO, gave the following definition of AI and its applying when gave his speech at Japan AI Experience in 2017:
How AI works
Some go even further and split artificial intelligence into a narrow and general category.
Narrow AI (or Weak AI)
This type operates within a limited context. It is a simple simulation of human intelligence. Narrow AI usually focuses on performing some single task but exceptionally well.
While machines with such type of algorithm may seem intelligent, they are operating under far more limitations than the most basic human intelligence.
Here are a few examples of narrow AI:
- IBM Watson
- Tesla Autopilot AI (self-driving cars)
- Google search (BERT and latest core updates)
- Smart assistants (Siri, Alexa, Cortana)
- Image Recognition software
- Weather apps
- Business Intelligence Apps (software that analyzes data to optimize any given function)
- Healthcare AI (Disease mapping and prediction tools; Optimized, personalized healthcare treatment recommendations)
- Drone robots
- Conversational bots for marketing and customer support
- Robo-advisors for stock trading
- Spam filters on email
- Social media monitoring tools for dangerous content or fake news
- Song or TV show recommendations from Spotify and Netflix (recommendation engines)
These systems are robust. Still, their playing field is narrow, and their focus is driving efficiencies.
But, with the right application, weak AI technologies have the vast power of transformation of how we work and live on a global scale.
General AI (or Strong AI)
This type of artificial intelligence we may see in TV series like Westworld or Mr. Robot.
General AI is a machine with general intelligence. It can apply its intelligence to solve any problem just like a human – thinking strategically, abstractly, and creatively.
Also, general AI has long been the number-one topic of dystopian sci-fi, in which hyper-intelligent machines overrun humanity (as seen in the Terminator franchise movie, for instance). But, experts are pretty sure there is no need to worry about anytime soon.
For sure, machines can perform some tasks better than humans (for example, big data processing and analyzing).
Still, this vision of general AI does not yet exist outside the screen. That is why human-machine interaction is crucial. Nowadays, AI remains an extension of human capabilities, not a replacement.
- Artificial Intelligence is the machines’ intelligence. Unlike humans, a machine can’t demonstrate strategical, abstract, and creative thinking.
- Currently, AI is split into two categories: narrow (weak) and general (strong) AI.
- All existing artificial intelligence systems belong to the Narrow AI category.
- Human-machine interaction remains the key since AI is still just an extension of human capabilities.