AI or artificial intelligence is an often misapplied term. Artificial Intelligence simply means intelligence in machines. This contrasts with natural intelligence, which originates in humans and other natural organisms.
AI gained its name and became a formal field of research in 1956. Initial work led to new tools for solving mathematical problems. However, early researchers discovered that conceiving artificial intelligence was incredibly difficult and progress slowed in the 1970s.
Recently, AI development has risen exponentially due to huge increases in computing power and availability of massive data sets. AI scientific, engineering, IT (information technology), R&D (research and development), technical and
manufacturing innovations have all advanced. Three prominent, growing artificial intelligence applications that stand out are machine learning, deep learning, and robotic vision systems.
What Is Machine Learning?
Machine learning is an AI application based upon systems automatically learning from the data they analyze and the results they obtain to improve their ability to work with that data in the future. For example, machine learning powers applications that estimate how long a trip will take and then provide guidance on the route.
Applications such as Google Maps use machine learning to analyze shifting traffic conditions and incorporate user-reported data to reduce travel times and suggest fuel-efficient routes. Machine learning is best for these types of specific, well-defined tasks that can be broken down into logical steps.
What Is Deep Learning?
Another major AI application is known as deep learning. Deep learning involves complex tasks with many hard to nail down variables. It makes use of neural networks, which seek to build computers that operate like our brains.
Deep learning leverages many neural networks stacked on top of each other to create a large, complex neural network. Deep learning demands a lot of computing power to both train the model from copious amounts of data and use the trained models to make decisions.
One example is digital assistants like Amazon Alexa, Apple Siri, and Google Assistant. Deep learning is what allows these assistants to listen to you and figure out what information you want or task you need them to perform.
Robotic Vision Systems
As artificial intelligence progresses, robotic vision systems more closely emulate human vision and brain processing. As a result, autonomous vehicles are becoming more likely. For example, Tesla claims that their cars will soon demonstrate full self-driving capabilities. Others like Waymo, GM and Apple will soon follow suit with fully autonomous vehicles.
Additionally, recent technological innovations in robotic vision systems allow robots to take care of senior patients more regularly, reduce the costs of care, raise patient satisfaction, and compensate for the lack of social interaction and attention.
For example, Irish start-up Akara Robotics offers senior care robot, Stevie, to live and work in retirement communities to complement the role of caregivers rather than replace them.
Artificial Intelligence Facts
One of the ways we can truly appreciate AI advances is how well it performs in games.
In 2011, IBM’s Watson won the U.S. game show Jeopardy!
In 2016, the Google DeepMind AlphaGo AI beat a human grandmaster at the complex Chinese game of Go.
But humans say AI isn’t so good at games involving teamwork.
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